CN112732846A - Water affair operation analysis system, method, electronic equipment and storage medium - Google Patents
Water affair operation analysis system, method, electronic equipment and storage medium Download PDFInfo
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
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Abstract
The invention relates to the technical field of water treatment, and provides a water service operation analysis system, a water service operation analysis method, electronic equipment and a storage medium. The method comprises the steps of copying original water affair data to generate first copied data, second copied data, third copied data and fourth copied data; inputting the first copied data into a first preset identification model, and outputting water service production data after identification and screening; inputting the second copied data into a second preset identification model, and outputting water service safety data after identification and screening; inputting the third copied data into a third preset identification model, and outputting the water business operation data after identification and screening; inputting the fourth copied data into a fourth preset identification model, and outputting the water service customer service data after identification and screening; and storing the four output data into a preset database. The method and the system automatically classify according to the original water service data to obtain water service production data, water service safety data, water service management data and water service customer service data.
Description
Technical Field
The invention relates to the technical field of water treatment, in particular to a water service operation analysis system, a water service operation analysis method, electronic equipment and a storage medium.
Background
At present, water companies such as raw water supply, tap water, sewage treatment companies, etc. generate raw data during production and operation, and the raw data includes various types of data such as production data, safety data, operation data, customer service data, and other useless data. In general, production data, safety data, business data, customer service data and other useless data are often mixed together, and staff of a water service company needs to manually classify original data to further analyze the classified data, which is very labor-consuming.
Disclosure of Invention
In view of the above, the present invention provides a water service operation analysis system, method, electronic device and storage medium.
The invention provides a water service operation analysis method, which comprises the following steps:
acquiring original water affair data, copying the original water affair data to generate first copied data, second copied data, third copied data and fourth copied data;
inputting the first copied data into a first pre-set recognition model trained in advance, and outputting water production data after the first pre-set recognition model is recognized and screened;
inputting the second copied data into a second pre-set recognition model trained in advance, and outputting water service safety data after the second pre-set recognition model is recognized and screened;
inputting the third copied data into a third pre-set recognition model trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened;
inputting the fourth copied data into a pre-trained fourth preset recognition model, and outputting the water service customer service data after the fourth preset recognition model is recognized and screened;
and storing the water service production data, the water service safety data, the water service operation data and the water service customer service data into a preset database.
In one embodiment, the method further comprises:
and copying the original water affair data to generate backup data, and storing the backup data to a preset storage address.
In one embodiment, the method further comprises:
and responding to a backup data query instruction sent by a user, taking out the backup data from the preset storage address, and pushing the backup data to the user.
In one embodiment, the method further comprises:
and counting the number of the water affair safety data, judging whether the number of the water affair safety data is multiple, and combining all the water affair safety data to obtain water affair safety summarized data when the number of the water affair safety data is multiple.
In one embodiment, the method further comprises:
and counting the quantity of the water affair production data, judging whether the quantity of the water affair production data is multiple, and merging all the water affair production data to obtain water affair production summarized data when the quantity of the water affair production data is multiple.
In one embodiment, the method further comprises:
and counting the number of the water business operation data, judging whether the number of the water business operation data is multiple, and combining all the water business operation data to obtain water business operation summary data when the number of the water business operation data is multiple.
In one embodiment, the method further comprises:
and counting the number of the water service customer service data, judging whether the number of the water service customer service data is multiple, and combining all the water service customer service data to obtain the water service customer service summary data when the number of the water service customer service data is multiple.
The invention also provides a water service operation analysis system, which comprises:
the acquisition module is used for acquiring original water service data, copying the original water service data and generating first copied data, second copied data, third copied data and fourth copied data;
the first output module is used for inputting the first copied data into a first pre-set recognition model which is trained in advance, and outputting the water production data after the first pre-set recognition model is recognized and screened;
the second output module is used for inputting the second copied data into a second preset recognition model trained in advance and outputting water service safety data after the second preset recognition model is recognized and screened;
the third output module is used for inputting the third copied data into a third pre-set recognition model which is trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened;
the fourth output module is used for inputting the fourth copied data into a pre-trained fourth preset recognition model and outputting the water service customer service data after the fourth preset recognition model is recognized and screened;
and the storage module is used for storing the water service production data, the water service safety data, the water service operation data and the water service customer service data to a preset database.
The present invention also provides an electronic device, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a water service operation analysis method as described above.
The present invention also provides a computer readable storage medium, in which a water service operation analysis program is stored, and when the water service operation analysis program is executed by a processor, the steps of the water service operation analysis method are implemented.
Since production data, security data, business data, customer service data and other useless data are usually mixed together in the related art, staff of the water service company needs to manually classify the original data to further analyze the classified data. In the embodiment of the invention, the original water affair data is obtained and copied to generate first copied data, second copied data, third copied data and fourth copied data; inputting the first copied data into a first pre-set recognition model trained in advance, and outputting water production data after the first pre-set recognition model is recognized and screened; inputting the second copied data into a second pre-set recognition model trained in advance, and outputting water service safety data after the second pre-set recognition model is recognized and screened; inputting the third copied data into a third pre-set recognition model trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened; inputting the fourth copied data into a pre-trained fourth preset recognition model, and outputting the water service customer service data after the fourth preset recognition model is recognized and screened; and storing the water service production data, the water service safety data, the water service operation data and the water service customer service data into a preset database. The invention automatically classifies the water service production data, the water service safety data, the water service management data and the water service customer service data according to the water service original data, thereby reducing the labor burden.
Drawings
FIG. 1 is a diagram of an electronic device according to a preferred embodiment of the present invention;
FIG. 2 is a flow chart of a preferred embodiment of a water service operation analysis method according to the present invention;
FIG. 3 is a block diagram of a water service operation analysis system according to a preferred embodiment of the present invention;
the objects, features and advantages of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Fig. 1 is a schematic diagram of an electronic device 1 according to a preferred embodiment of the invention.
The electronic device 1 includes but is not limited to: memory 11, processor 12, display 13, and network interface 14. The electronic device 1 is connected to a network through a network interface 14 to obtain raw data. The network may be a wireless or wired network such as an Intranet (Internet), the Internet (Internet), a Global System for mobile communications (GSM), Wideband Code Division Multiple Access (WCDMA), a 4G network, a 5G network, Bluetooth (Bluetooth), Wi-Fi, or a communication network.
The memory 11 includes at least one type of readable storage medium including a flash memory, a hard disk, a multimedia card, a card type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a Read Only Memory (ROM), an Electrically Erasable Programmable Read Only Memory (EEPROM), a Programmable Read Only Memory (PROM), a magnetic memory, a magnetic disk, an optical disk, etc. In some embodiments, the storage 11 may be an internal storage unit of the electronic device 1, such as a hard disk or a memory of the electronic device 1. In other embodiments, the memory 11 may also be an external storage device of the electronic device 1, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like equipped with the electronic device 1. Of course, the memory 11 may also comprise both an internal memory unit and an external memory device of the electronic device 1. In this embodiment, the memory 11 is generally used for storing an operating system installed in the electronic device 1 and various application software, such as program codes of the water service operation analysis program 10. Further, the memory 11 may also be used to temporarily store various types of data that have been output or are to be output.
Processor 12 may be a Central Processing Unit (CPU), controller, microcontroller, microprocessor, or other data Processing chip in some embodiments. The processor 12 is typically used for controlling the overall operation of the electronic device 1, such as performing data interaction or communication related control and processing. In this embodiment, the processor 12 is configured to run the program code stored in the memory 11 or process data, for example, run the program code of the water service operation analysis program 10.
The display 13 may be referred to as a display screen or display unit. The display 13 may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, a screen, an Organic Light-Emitting Diode (OLED) touch panel, and the like in some embodiments. The display 13 is used for displaying information processed in the electronic device 1 and for displaying a visualization of a work page, e.g. displaying the results of data statistics. The electronic device 1 may include a first display unit and a second display unit.
The network interface 14 may optionally comprise a standard wired interface, a wireless interface (e.g. WI-FI interface), the network interface 14 typically being used for establishing a communication connection between the electronic device 1 and other electronic devices.
Fig. 1 shows only the electronic device 1 with the components 11-14 and the water service operation analysis program 10, but it is to be understood that not all of the shown components are required to be implemented, and that more or fewer components may be implemented instead.
Optionally, the electronic device 1 may further comprise a user interface, the user interface may comprise a Display (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface may further comprise a standard wired interface and a wireless interface. The electronic device 1 may further comprise an alarm.
The electronic device 1 may further include a Radio Frequency (RF) circuit, a sensor, an audio circuit, and the like, which are not described in detail herein.
In the above embodiment, the processor 12, when executing the water service operation analysis program 10 stored in the memory 11, may implement the following steps:
acquiring original water affair data, copying the original water affair data to generate first copied data, second copied data, third copied data and fourth copied data;
inputting the first copied data into a first pre-set recognition model trained in advance, and outputting water production data after the first pre-set recognition model is recognized and screened;
inputting the second copied data into a second pre-set recognition model trained in advance, and outputting water service safety data after the second pre-set recognition model is recognized and screened;
inputting the third copied data into a third pre-set recognition model trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened;
inputting the fourth copied data into a pre-trained fourth preset recognition model, and outputting the water service customer service data after the fourth preset recognition model is recognized and screened;
and storing the water service production data, the water service safety data, the water service operation data and the water service customer service data into a preset database.
For detailed description of the above steps, please refer to the following description of fig. 2 regarding a flowchart of an embodiment of the water service operation analysis method and fig. 3 regarding a functional block diagram of an embodiment of the water service operation analysis system 100.
Fig. 2 is a flowchart of a water service operation analysis method according to an embodiment of the present invention.
The embodiment of the invention discloses a water service operation analysis method, which can be applied to electronic equipment and comprises the following steps:
step S10, acquiring the original water affair data, and copying the original water affair data to generate first copied data, second copied data, third copied data, and fourth copied data.
In this embodiment, for example, a worker who manages the rules and regulations clicks the corresponding control on the electronic device to upload the raw water service data, and the electronic device obtains the raw water service data. The water service original data comprises water service production data, water service safety data, water service management data and water service customer service data. Wherein, the water affair production data is a related table file generated in the production process of the water affair company. The water affair safety data is a table file of the safety aspect of the water affair company. The water business management data is a table file of the water business company in management. The water service customer service data is a relevant table file of the water service company customer service.
The original water affair data is copied for four times to obtain first copied data, second copied data, third copied data and fourth copied data. It is understood that the first copied data, the second copied data, the third copied data and the fourth copied data are all the same as the water service original data.
And step S20, inputting the first copied data into a first pre-set recognition model trained in advance, and outputting the water production data after the first pre-set recognition model is recognized and screened.
In this embodiment, the first preset identification model is trained in advance, the first copied data is input into the first preset identification model, and the first preset identification model outputs the water production data. The training process of the first preset recognition model is as follows: s1, preparing a preset number of file samples marked with corresponding water affair production data for the water affair production data; s2, dividing the file samples into a training subset with a first proportion and a verification subset with a second proportion, mixing the file samples in each training subset to obtain a training set, and mixing the file samples in each verification subset to obtain a verification set; s3, training the first preset identification model by using the training set, and verifying the accuracy of the first preset identification model after training by using the verification set; s4, if the accuracy is higher than the preset accuracy, ending the training; if the accuracy is less than or equal to the preset accuracy, increasing the number of the file samples corresponding to the water production data, and re-executing S2 and S3.
Optionally, the method further comprises: and counting the quantity of the water affair production data, judging whether the quantity of the water affair production data is multiple, and merging all the water affair production data to obtain water affair production summarized data when the quantity of the water affair production data is multiple.
It can be understood that, after the first copied data is input into a first pre-set recognition model trained in advance and the water business production data is output after the first pre-set recognition model is recognized and screened, at least one water business production data exists, the number of the water business production data is counted to determine the specific number of the water business production data, whether the number of the water business production data is greater than or equal to two or not is judged, and when the number of the water business production data is greater than or equal to two, all the water business safety data are combined to obtain the water business safety summary data. The format of each water affair production data is the same, namely the column names of each water affair production data are the same, the arrangement sequence of the column names is the same, and the number of columns of each water affair production data is the same, so that one water affair production data can be used as a basic table, and other water affair production data except the basic table are correspondingly transferred to the basic table, thereby realizing data combination.
And step S30, inputting the second copied data into a second pre-set recognition model trained in advance, and outputting water service safety data after the second pre-set recognition model is recognized and screened.
In this embodiment, the second preset recognition model is trained in advance, the second copied data is input into the second preset recognition model, and the second preset recognition model outputs the water safety data. The training process of the second preset recognition model is as follows: s1, preparing a preset number of file samples marked with corresponding water affair safety data for the water affair safety data; s2, dividing the file samples into a training subset with a first proportion and a verification subset with a second proportion, mixing the file samples in each training subset to obtain a training set, and mixing the file samples in each verification subset to obtain a verification set; s3, training a second preset identification model by using the training set, and verifying the accuracy of the second preset identification model after training by using the verification set; s4, if the accuracy is higher than the preset accuracy, ending the training; if the accuracy is less than or equal to the preset accuracy, increasing the number of file samples corresponding to the water safety data, and re-executing S2 and S3.
Optionally, the method further comprises: and counting the number of the water affair safety data, judging whether the number of the water affair safety data is multiple, and combining all the water affair safety data to obtain water affair safety summarized data when the number of the water affair safety data is multiple.
It can be understood that after the second copied data are input into a second pre-set recognition model which is trained in advance and the water safety data are output after the recognition and screening of the second pre-set recognition model, at least one water safety data exists, the number of the water safety data is counted to determine the specific number of the water safety data, whether the number of the water safety data is greater than or equal to two or not is judged, and when the number of the water safety data is greater than or equal to two, all the water safety data are combined to obtain water safety summarized data. The formats of each water affair safety data are the same, namely the column names of each water affair safety data are the same, the arrangement sequence of the column names is the same, and the number of the columns of each water affair safety data is the same, so that one water affair safety data can be used as a basic table, and other water affair safety data except the basic table are correspondingly transferred to the basic table, so that data combination can be realized.
And step S40, inputting the third copied data into a third pre-set recognition model trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened.
In this embodiment, the third preset identification model is trained in advance, and the third copied data is input into the third preset identification model, and the third preset identification model outputs the water business operation data. The training process of the third preset recognition model is as follows: s1, preparing a preset number of file samples marked with corresponding water business operation data for the water business operation data; s2, dividing the file samples into a training subset with a first proportion and a verification subset with a second proportion, mixing the file samples in each training subset to obtain a training set, and mixing the file samples in each verification subset to obtain a verification set; s3, training a third preset identification model by using the training set, and verifying the accuracy of the third preset identification model after training by using the verification set; s4, if the accuracy is higher than the preset accuracy, ending the training; and if the accuracy is less than or equal to the preset accuracy, increasing the number of the file samples corresponding to the water business data, and executing S2 and S3 again.
Optionally, the method further comprises: and counting the number of the water business operation data, judging whether the number of the water business operation data is multiple, and combining all the water business operation data to obtain water business operation summary data when the number of the water business operation data is multiple.
It can be understood that, after the third duplicated data is input into a third pre-set recognition model trained in advance and the water business operation data is output after the third pre-set recognition model is recognized and screened, at least one water business operation data exists, the number of the water business operation data is counted to determine the specific number of the water business operation data, whether the number of the water business operation data is greater than or equal to two or not is judged, and when the number of the water business operation data is greater than or equal to two, all the water business operation data are combined to obtain the water business operation summary data. The formats of all the water business operation data are the same, namely the column names of all the water business operation data are the same, the arrangement sequence of the column names is the same, and the number of the columns of all the water business operation data is the same, so that one of the water business operation data can be used as a basic table, and other water business operation data except the basic table are correspondingly transferred to the basic table, so that data combination can be realized.
And step S50, inputting the fourth copied data into a pre-trained fourth preset recognition model, and outputting the water service customer service data after the fourth preset recognition model is recognized and screened.
In this embodiment, the fourth preset recognition model is trained in advance, and the fourth copied data is input into the fourth preset recognition model, and the fourth preset recognition model outputs the water service customer service data. The training process of the fourth preset recognition model is as follows: s1, preparing a preset number of file samples marked with corresponding water service customer service data for the water service customer service data; s2, dividing the file samples into a training subset with a first proportion and a verification subset with a second proportion, mixing the file samples in each training subset to obtain a training set, and mixing the file samples in each verification subset to obtain a verification set; s3, training a fourth preset identification model by using the training set, and verifying the accuracy of the fourth preset identification model after training by using the verification set; s4, if the accuracy is higher than the preset accuracy, ending the training; and if the accuracy is less than or equal to the preset accuracy, increasing the number of the file samples corresponding to the water service customer service data, and executing S2 and S3 again.
Optionally, the method further comprises: and counting the number of the water service customer service data, judging whether the number of the water service customer service data is multiple, and combining all the water service customer service data to obtain the water service customer service summary data when the number of the water service customer service data is multiple.
It can be understood that, after the fourth copied data is input into a fourth pre-set recognition model trained in advance and the water service data is output after the fourth pre-set recognition model is recognized and screened, at least one piece of water service data exists, the number of the water service data is counted to determine the specific number of the water service data, whether the number of the water service data is greater than or equal to two or not is judged, and when the number of the water service data is greater than or equal to two, all the water service data are combined to obtain the water service summary data. The formats of all the water service customer service data are the same, namely the column names of all the water service customer service data are the same, the arrangement sequence of the column names is the same, and the number of the columns of all the water service customer service data is the same, so that one of the water service customer service data can be used as a basic table, and other water service customer service data except the basic table are correspondingly transferred to the basic table, so that data combination can be realized.
And step S60, storing the water service production data, the water service safety data, the water service operation data and the water service customer service data into a preset database.
In this embodiment, the preset database may be a local database or a cloud database. The water service production data, the water service safety data, the water service operation data and the water service customer service data can be stored in different preset databases, and the water service production data, the water service safety data, the water service operation data and the water service customer service data can also be stored in the same preset database.
In one embodiment, the method further comprises: and copying the original water affair data to generate backup data, and storing the backup data to a preset storage address.
In this embodiment, the preset storage address may be a local folder or a cloud database.
Optionally, the method further comprises: and responding to a backup data query instruction sent by a user, taking out the backup data from the preset storage address, and pushing the backup data to the user.
For example, a worker who manages the rules and regulations clicks a corresponding control on the electronic device to send a command for inquiring the backup data, the electronic device receives the command for inquiring the backup data, the backup data is taken out from the preset storage address, and the display unit is controlled to display the backup data.
Since production data, security data, business data, customer service data and other useless data are usually mixed together in the related art, staff of the water service company needs to manually classify the original data to further analyze the classified data. In the embodiment of the invention, the original water affair data is obtained and copied to generate first copied data, second copied data, third copied data and fourth copied data; inputting the first copied data into a first pre-set recognition model trained in advance, and outputting water production data after the first pre-set recognition model is recognized and screened; inputting the second copied data into a second pre-set recognition model trained in advance, and outputting water service safety data after the second pre-set recognition model is recognized and screened; inputting the third copied data into a third pre-set recognition model trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened; inputting the fourth copied data into a pre-trained fourth preset recognition model, and outputting the water service customer service data after the fourth preset recognition model is recognized and screened; and storing the water service production data, the water service safety data, the water service operation data and the water service customer service data into a preset database. The invention automatically classifies the water service production data, the water service safety data, the water service management data and the water service customer service data according to the water service original data, thereby reducing the labor burden.
Referring to fig. 3, the present invention further provides a water service operation analysis system corresponding to the method embodiment, and the water service operation analysis system 100 according to the present invention may be installed in an electronic device. According to the implemented functions, the water service operation analysis system 100 may include an obtaining module 110, a first output module 120, a second output module 130, a third output module 140, a fourth output module 150, and a storage module 160. The module in the present invention may also be referred to as a unit, and refers to a series of computer program segments that can be executed by a processor of an electronic device and can perform a fixed function, and are stored in a memory of the electronic device.
In the present embodiment, the functions regarding the respective modules/units are as follows:
the obtaining module 110 is configured to obtain the original water service data, copy the original water service data, and generate first copied data, second copied data, third copied data, and fourth copied data.
In this embodiment, for example, a worker who manages the rules and regulations clicks the corresponding control on the electronic device to upload the raw water service data, and the electronic device obtains the raw water service data. The water service original data comprises water service production data, water service safety data, water service management data and water service customer service data. Wherein, the water affair production data is a related table file generated in the production process of the water affair company. The water affair safety data is a table file of the safety aspect of the water affair company. The water business management data is a table file of the water business company in management. The water service customer service data is a relevant table file of the water service company customer service.
The original water affair data is copied for four times to obtain first copied data, second copied data, third copied data and fourth copied data. It is understood that the first copied data, the second copied data, the third copied data and the fourth copied data are all the same as the water service original data.
The first output module 120 is configured to input the first copied data into a first pre-set recognition model trained in advance, and output the water production data after the first pre-set recognition model is recognized and screened.
In this embodiment, the first preset identification model is trained in advance, the first copied data is input into the first preset identification model, and the first preset identification model outputs the water production data. The training process of the first preset recognition model is as follows: s1, preparing a preset number of file samples marked with corresponding water affair production data for the water affair production data; s2, dividing the file samples into a training subset with a first proportion and a verification subset with a second proportion, mixing the file samples in each training subset to obtain a training set, and mixing the file samples in each verification subset to obtain a verification set; s3, training the first preset identification model by using the training set, and verifying the accuracy of the first preset identification model after training by using the verification set; s4, if the accuracy is higher than the preset accuracy, ending the training; if the accuracy is less than or equal to the preset accuracy, increasing the number of the file samples corresponding to the water production data, and re-executing S2 and S3.
Optionally, the system further includes a first merging module, configured to count the number of the water production data, determine whether the number of the water production data is multiple, and merge all the water production data when the number of the water production data is multiple, to obtain the summarized water production data.
It can be understood that, after the first copied data is input into a first pre-set recognition model trained in advance and the water business production data is output after the first pre-set recognition model is recognized and screened, at least one water business production data exists, the number of the water business production data is counted to determine the specific number of the water business production data, whether the number of the water business production data is greater than or equal to two or not is judged, and when the number of the water business production data is greater than or equal to two, all the water business safety data are combined to obtain the water business safety summary data. The format of each water affair production data is the same, namely the column names of each water affair production data are the same, the arrangement sequence of the column names is the same, and the number of columns of each water affair production data is the same, so that one water affair production data can be used as a basic table, and other water affair production data except the basic table are correspondingly transferred to the basic table, thereby realizing data combination.
And a second output module 130, configured to input the second copied data into a second pre-set recognition model trained in advance, and output the water safety data after the second pre-set recognition model is recognized and screened.
In this embodiment, the second preset recognition model is trained in advance, the second copied data is input into the second preset recognition model, and the second preset recognition model outputs the water safety data. The training process of the second preset recognition model is as follows: s1, preparing a preset number of file samples marked with corresponding water affair safety data for the water affair safety data; s2, dividing the file samples into a training subset with a first proportion and a verification subset with a second proportion, mixing the file samples in each training subset to obtain a training set, and mixing the file samples in each verification subset to obtain a verification set; s3, training a second preset identification model by using the training set, and verifying the accuracy of the second preset identification model after training by using the verification set; s4, if the accuracy is higher than the preset accuracy, ending the training; if the accuracy is less than or equal to the preset accuracy, increasing the number of file samples corresponding to the water safety data, and re-executing S2 and S3.
Optionally, the system further includes a second merging module, configured to count the number of the water service safety data, determine whether the number of the water service safety data is multiple, and merge all the water service safety data when the number of the water service safety data is multiple, so as to obtain water service safety summarized data.
It can be understood that after the second copied data are input into a second pre-set recognition model which is trained in advance and the water safety data are output after the recognition and screening of the second pre-set recognition model, at least one water safety data exists, the number of the water safety data is counted to determine the specific number of the water safety data, whether the number of the water safety data is greater than or equal to two or not is judged, and when the number of the water safety data is greater than or equal to two, all the water safety data are combined to obtain water safety summarized data. The formats of each water affair safety data are the same, namely the column names of each water affair safety data are the same, the arrangement sequence of the column names is the same, and the number of the columns of each water affair safety data is the same, so that one water affair safety data can be used as a basic table, and other water affair safety data except the basic table are correspondingly transferred to the basic table, so that data combination can be realized.
And a third output module 140, configured to input the third copied data into a third pre-set recognition model trained in advance, and output the water business operation data after the third pre-set recognition model is recognized and screened.
In this embodiment, the third preset identification model is trained in advance, and the third copied data is input into the third preset identification model, and the third preset identification model outputs the water business operation data. The training process of the third preset recognition model is as follows: s1, preparing a preset number of file samples marked with corresponding water business operation data for the water business operation data; s2, dividing the file samples into a training subset with a first proportion and a verification subset with a second proportion, mixing the file samples in each training subset to obtain a training set, and mixing the file samples in each verification subset to obtain a verification set; s3, training a third preset identification model by using the training set, and verifying the accuracy of the third preset identification model after training by using the verification set; s4, if the accuracy is higher than the preset accuracy, ending the training; and if the accuracy is less than or equal to the preset accuracy, increasing the number of the file samples corresponding to the water business data, and executing S2 and S3 again.
Optionally, the system further includes a third merging module, configured to count the number of the water business operation data, determine whether the number of the water business operation data is multiple, and merge all the water business operation data when the number of the water business operation data is multiple, to obtain the summarized water business operation data.
It can be understood that, after the third duplicated data is input into a third pre-set recognition model trained in advance and the water business operation data is output after the third pre-set recognition model is recognized and screened, at least one water business operation data exists, the number of the water business operation data is counted to determine the specific number of the water business operation data, whether the number of the water business operation data is greater than or equal to two or not is judged, and when the number of the water business operation data is greater than or equal to two, all the water business operation data are combined to obtain the water business operation summary data. The formats of all the water business operation data are the same, namely the column names of all the water business operation data are the same, the arrangement sequence of the column names is the same, and the number of the columns of all the water business operation data is the same, so that one of the water business operation data can be used as a basic table, and other water business operation data except the basic table are correspondingly transferred to the basic table, so that data combination can be realized.
And a fourth output module 150, configured to input the fourth copied data into a fourth pre-set recognition model trained in advance, and output the customer service data after the fourth pre-set recognition model is recognized and screened.
In this embodiment, the fourth preset recognition model is trained in advance, and the fourth copied data is input into the fourth preset recognition model, and the fourth preset recognition model outputs the water service customer service data. The training process of the fourth preset recognition model is as follows: s1, preparing a preset number of file samples marked with corresponding water service customer service data for the water service customer service data; s2, dividing the file samples into a training subset with a first proportion and a verification subset with a second proportion, mixing the file samples in each training subset to obtain a training set, and mixing the file samples in each verification subset to obtain a verification set; s3, training a fourth preset identification model by using the training set, and verifying the accuracy of the fourth preset identification model after training by using the verification set; s4, if the accuracy is higher than the preset accuracy, ending the training; and if the accuracy is less than or equal to the preset accuracy, increasing the number of the file samples corresponding to the water service customer service data, and executing S2 and S3 again.
Optionally, the system further includes a fourth merging module, configured to count the number of the water service customer service data, determine whether the number of the water service customer service data is multiple, and merge all the water service customer service data when the number of the water service customer service data is multiple, so as to obtain water service customer service summary data.
It can be understood that, after the fourth copied data is input into a fourth pre-set recognition model trained in advance and the water service data is output after the fourth pre-set recognition model is recognized and screened, at least one piece of water service data exists, the number of the water service data is counted to determine the specific number of the water service data, whether the number of the water service data is greater than or equal to two or not is judged, and when the number of the water service data is greater than or equal to two, all the water service data are combined to obtain the water service summary data. The formats of all the water service customer service data are the same, namely the column names of all the water service customer service data are the same, the arrangement sequence of the column names is the same, and the number of the columns of all the water service customer service data is the same, so that one of the water service customer service data can be used as a basic table, and other water service customer service data except the basic table are correspondingly transferred to the basic table, so that data combination can be realized.
The storage module 160 is configured to store the water service production data, the water service safety data, the water service operation data, and the water service customer service data in a preset database.
In this embodiment, the preset database may be a local database or a cloud database. The water service production data, the water service safety data, the water service operation data and the water service customer service data can be stored in different preset databases, and the water service production data, the water service safety data, the water service operation data and the water service customer service data can also be stored in the same preset database.
In one embodiment, the system further includes a copying module, configured to copy the original water service data, generate backup data, and store the backup data in a preset storage address.
In this embodiment, the preset storage address may be a local folder or a cloud database.
Optionally, the system further includes a query module, configured to respond to a query backup data instruction sent by a user, take out the backup data from the preset storage address, and push the backup data to the user.
For example, a worker who manages the rules and regulations clicks a corresponding control on the electronic device to send a command for inquiring the backup data, the electronic device receives the command for inquiring the backup data, the backup data is taken out from the preset storage address, and the display unit is controlled to display the backup data.
Since production data, security data, business data, customer service data and other useless data are usually mixed together in the related art, staff of the water service company needs to manually classify the original data to further analyze the classified data. In the embodiment of the invention, the original water affair data is obtained and copied to generate first copied data, second copied data, third copied data and fourth copied data; inputting the first copied data into a first pre-set recognition model trained in advance, and outputting water production data after the first pre-set recognition model is recognized and screened; inputting the second copied data into a second pre-set recognition model trained in advance, and outputting water service safety data after the second pre-set recognition model is recognized and screened; inputting the third copied data into a third pre-set recognition model trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened; inputting the fourth copied data into a pre-trained fourth preset recognition model, and outputting the water service customer service data after the fourth preset recognition model is recognized and screened; and storing the water service production data, the water service safety data, the water service operation data and the water service customer service data into a preset database. The invention automatically classifies the water service production data, the water service safety data, the water service management data and the water service customer service data according to the water service original data, thereby reducing the labor burden.
Furthermore, the embodiment of the present invention also provides a computer-readable storage medium, which may be any one or any combination of a hard disk, a multimedia card, an SD card, a flash memory card, an SMC, a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a portable compact disc read only memory (CD-ROM), a USB memory, and the like. The computer-readable storage medium includes a storage data area and a storage program area, the storage data area stores data created according to the use of the blockchain node, the storage program area stores a water service operation analysis program 10, and when executed by the processor, the water service operation analysis program 10 implements the following operations:
acquiring original water affair data, copying the original water affair data to generate first copied data, second copied data, third copied data and fourth copied data;
inputting the first copied data into a first pre-set recognition model trained in advance, and outputting water production data after the first pre-set recognition model is recognized and screened;
inputting the second copied data into a second pre-set recognition model trained in advance, and outputting water service safety data after the second pre-set recognition model is recognized and screened;
inputting the third copied data into a third pre-set recognition model trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened;
inputting the fourth copied data into a pre-trained fourth preset recognition model, and outputting the water service customer service data after the fourth preset recognition model is recognized and screened;
and storing the water service production data, the water service safety data, the water service operation data and the water service customer service data into a preset database.
It should be emphasized that the embodiment of the computer-readable storage medium of the present invention is substantially the same as the embodiment of the water service operation analysis method, and will not be described herein again.
The specific implementation of the computer readable storage medium of the present invention is substantially the same as the specific implementation of the water service operation analysis method described above, and will not be described herein again.
It should be noted that the above-mentioned numbers of the embodiments of the present invention are merely for description, and do not represent the merits of the embodiments. And the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, system, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, system, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, system, article, or method that includes the element.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) as described above and includes instructions for enabling a terminal device (such as a mobile phone, a computer, an electronic system, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A water service operation analysis method is characterized by comprising the following steps:
acquiring original water affair data, copying the original water affair data to generate first copied data, second copied data, third copied data and fourth copied data;
inputting the first copied data into a first pre-set recognition model trained in advance, and outputting water production data after the first pre-set recognition model is recognized and screened;
inputting the second copied data into a second pre-set recognition model trained in advance, and outputting water service safety data after the second pre-set recognition model is recognized and screened;
inputting the third copied data into a third pre-set recognition model trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened;
inputting the fourth copied data into a pre-trained fourth preset recognition model, and outputting the water service customer service data after the fourth preset recognition model is recognized and screened;
and storing the water service production data, the water service safety data, the water service operation data and the water service customer service data into a preset database.
2. The water service operation analysis method of claim 1, wherein the method further comprises:
and copying the original water affair data to generate backup data, and storing the backup data to a preset storage address.
3. The water service operation analysis method of claim 2, wherein the method further comprises:
and responding to a backup data query instruction sent by a user, taking out the backup data from the preset storage address, and pushing the backup data to the user.
4. The water service operation analysis method of claim 1, wherein the method further comprises:
and counting the number of the water affair safety data, judging whether the number of the water affair safety data is multiple, and combining all the water affair safety data to obtain water affair safety summarized data when the number of the water affair safety data is multiple.
5. The water service operation analysis method of claim 1, wherein the method further comprises:
and counting the quantity of the water affair production data, judging whether the quantity of the water affair production data is multiple, and merging all the water affair production data to obtain water affair production summarized data when the quantity of the water affair production data is multiple.
6. The water service operation analysis method of claim 1, wherein the method further comprises:
and counting the number of the water business operation data, judging whether the number of the water business operation data is multiple, and combining all the water business operation data to obtain water business operation summary data when the number of the water business operation data is multiple.
7. The water service operation analysis method of claim 1, wherein the method further comprises:
and counting the number of the water service customer service data, judging whether the number of the water service customer service data is multiple, and combining all the water service customer service data to obtain the water service customer service summary data when the number of the water service customer service data is multiple.
8. A water service operation analysis system, the system comprising:
the acquisition module is used for acquiring original water service data, copying the original water service data and generating first copied data, second copied data, third copied data and fourth copied data;
the first output module is used for inputting the first copied data into a first pre-set recognition model which is trained in advance, and outputting the water production data after the first pre-set recognition model is recognized and screened;
the second output module is used for inputting the second copied data into a second preset recognition model trained in advance and outputting water service safety data after the second preset recognition model is recognized and screened;
the third output module is used for inputting the third copied data into a third pre-set recognition model which is trained in advance, and outputting the water business operation data after the third pre-set recognition model is recognized and screened;
the fourth output module is used for inputting the fourth copied data into a pre-trained fourth preset recognition model and outputting the water service customer service data after the fourth preset recognition model is recognized and screened;
and the storage module is used for storing the water service production data, the water service safety data, the water service operation data and the water service customer service data to a preset database.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the water service operation analysis method of any one of claims 1 to 7.
10. A computer-readable storage medium, in which a water service operation analysis program is stored, and when the water service operation analysis program is executed by a processor, the steps of the water service operation analysis method according to any one of claims 1 to 7 are implemented.
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