CN115169779A - Enterprise safety risk early warning prediction system and method - Google Patents
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Abstract
The invention provides an enterprise safety risk early warning prediction system and method. The system analyzes and calculates based on the monitoring data of the Internet of things and the safety production data generated by the related business system, and uniformly processes a plurality of source data to form safety risk early warning information, so that the identification of various risks is more comprehensive and accurate, and the risk misjudgment or omission caused by the incomplete monitoring data is prevented. The risk trend prediction is displayed by mining, analyzing and sorting various types of data obtained by remote, real-time and dynamic monitoring of the safety production, so that early discovery, early prevention and early correction of hidden dangers, violation and unsafe behaviors are realized, and the management efficiency is improved.
Description
Technical Field
The invention belongs to the field of risk early warning prediction, and particularly relates to an enterprise safety risk early warning prediction system and method.
Background
The risk potential safety hazard prediction and risk early warning prevention and control of enterprises are a process of carrying out prejudgment, identification and investigation on various risk sources in an enterprise daily production system and in the operation process, carrying out comprehensive evaluation on the risk potential prediction by combining the conditions of the existing conditions, construction natural conditions, equipment level, safety field management and the like, and carrying out risk early warning by generally adopting the rationality, feasibility and pertinence of classification, early warning and the like so as to reduce the enterprise production potential safety hazard and construction risk to controllable safety management.
At present, the state vigorously promotes dual prevention management construction, and the early warning prediction management is urgently needed in the daily operation process of enterprise, but in the existing system, daily safety management data and Internet of things equipment monitoring data are not reasonably and uniformly analyzed, and accurate risk early warning cannot be formed by utilizing multi-source detection monitoring data. Meanwhile, the future safe production trend cannot be directly and effectively predicted.
Disclosure of Invention
The invention aims to overcome the defects that the conventional enterprise risk early warning system cannot perform unified analysis on multi-source data and cannot perform risk trend prediction.
In order to achieve the above object, the present invention provides an enterprise security risk early warning and prediction system, which is characterized in that the system comprises: the system comprises an early warning parameter configuration module 1, a risk early warning prediction analysis and processing module 2, an early warning information display module 3 and an early warning query module 4; wherein:
the early warning parameter configuration module 1: the system is used for maintaining early warning prediction related parameters and index information;
risk early warning, predicting, analyzing and processing module 2: the system is used for analyzing and calculating the safety risk condition of an enterprise, recording the risk and sending out early warning to form an early warning index graph; forming a safe production trend in a certain future interval;
early warning information display module 3: the system is used for displaying the safety risk early warning conditions of the current level unit and the lower level unit in a graphic mode and refreshing the safety risk early warning conditions at regular time; displaying a risk trend prediction result;
the early warning and alarming inquiry module 4: the method is used for checking the reminding content of the early warning prediction.
As an improvement of the above system, the early warning parameter configuration module 1 includes a parameter configuration sub-module 101, an index maintenance sub-module 102, and a clustering threshold weight sub-module 103; wherein:
the parameter configuration sub-module 101: the system is used for early warning configuration at company level, plant level, department level and team level and maintenance of early warning state values;
the index maintenance submodule 102: the system is used for maintaining the early warning indexes, and comprises index items and calculation rules;
the clique threshold weight submodule 103: the method is used for carrying out weight division according to the clique threshold information and filling safety, attention, warning and danger upper and lower limit values.
As an improvement of the above system, the risk early warning, predicting, analyzing and processing module 2 analyzes and calculates based on the monitoring data of the internet of things and the safety production data generated by the related business system, and performs unified processing on a plurality of source data to form an early warning index map; forming a safe production trend in a certain interval in the future.
As an improvement of the above system, the early warning information display module 3 includes a company-level early warning indication map sub-module 301, a plant-level early warning indication map sub-module 302, a department-level early warning indication map sub-module 303, a team-level early warning indication map sub-module 304, and an index trend map sub-module 305; wherein:
company-level warning indication map sub-module 301: the early warning system is used for reflecting real-time early warning indexes and the states of companies in a code table mode, and displaying the specific early warning index conditions of each affiliated unit through a chart;
the plant and mine level early warning indication map sub-module 302: the early warning system is used for reflecting real-time early warning indexes and states of units of factories and mines in a code table mode and displaying specific early warning index conditions of each unit through a chart;
department level early warning indication map sub-module 303: the early warning system is used for reflecting the real-time early warning index and the state of a department in a code table form and displaying the specific early warning index condition of the department in a chart form;
class group level warning indication map sub-module 304: the early warning system is used for reflecting the real-time early warning indexes and the states of the teams and groups to which the departments belong in a code table mode, and displaying the specific early warning index conditions of the teams and groups through a chart;
indicator trend graph sub-module 305: the method is used for displaying the specific index trend conditions of companies, factories and mines, departments or teams in the form of line graphs and reports.
The invention also provides an enterprise safety risk early warning and forecasting method, which comprises the following steps:
acquiring monitoring data of the Internet of things and safety production data generated by a related business system, analyzing and calculating, uniformly processing a plurality of source data, judging a risk condition according to early warning configuration, recording risks and sending early warning; and calculating the safe production trend in a certain future interval.
As an improvement of the above method, further comprising: and displaying the safety risk early warning condition of the unit at the current level and/or the lower level in a graphic mode, and displaying the risk trend prediction result.
As an improvement of the above method, further comprising: and maintaining early warning and predicting related parameters and index information.
As an improvement of the above method, further comprising: and screening and checking specific early warning content information through conditions.
The invention also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor executes the computer program to perform the method according to any of the preceding claims.
The invention also provides a computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to carry out the method according to any one of the preceding claims.
Compared with the prior art, the invention has the advantages that:
1. the data sources comprise remote video monitoring, equipment comprehensive parameters and other related service systems, and the data from the multiple sources are processed in a unified manner, so that the identification of various risks is more comprehensive and accurate, and the risk misjudgment or omission caused by incomplete monitoring data is prevented.
2. The risk trend prediction is displayed by mining, analyzing and sorting various types of data obtained by remote, real-time and dynamic monitoring of the safety production, so that early discovery, early prevention and early correction of hidden dangers, violation and unsafe behaviors are realized, supervision is advanced by one kilometer, and the management efficiency is improved.
Drawings
FIG. 1 is a block diagram of an enterprise security risk early warning prediction system;
FIG. 2 is a functional block diagram of an enterprise security risk early warning prediction system;
FIG. 3 is a schematic diagram of a parameter configuration sub-module page design;
FIG. 4 is a schematic diagram of a page design of an indicator maintenance submodule;
FIG. 5 is a schematic view of a group threshold weight maintenance submodule page design;
FIG. 6 is a schematic view of a design of a company-level warning indication map sub-module page;
FIG. 7 is a diagram illustrating a design of a page of an indicator trend graph sub-module;
fig. 8 is a schematic diagram showing a page design of an early warning query module.
Detailed Description
The contents of the enterprise safety risk early warning prediction management mainly comprise risk early warning system establishment, process risk management, risk early warning rule customization, risk early warning prediction analysis and processing, various emergency disposal schemes, early warning prediction summary and the like.
(1) The establishment of a risk early warning system is the basis of early warning prediction management, and generally comprises the aspects of hidden danger, violation of regulations, risks, problems, accident events, intelligent application, operation and the like. An example of a system model is as follows:
(2) The process risk management is early warning application in the whole process of executing various businesses in daily safety production of enterprises. For example, before operation, early warning is carried out according to operation risks, so that the technical background before operation is convenient for team managers to carry out according to the operation risks; in the operation, the safety management personnel can organize effective safety inspection, side station supervision and the like according to the operation risk distribution area; after operation, operation and maintenance personnel can conveniently carry out filing and summarizing according to the risk level. In the field monitoring process, the device can pass back in real time based on the Internet of things such as a sensor, the early warning information is displayed on a monitoring picture in real time, and monitoring personnel acquire operation measures according to the early warning information.
(3) The risk early warning rule customization is mainly based on the fact that the early warning model is set systematically and in a customized mode, for example, threshold values can be set according to various indexes and calculation types, early warning states are formed according to the threshold values, safety production management process data are processed through big data acquisition and screening, the cloud computing technology is used for conducting visual and systematic display through an early warning index diagram.
(4) The risk early warning prediction analysis and processing is to analyze, calculate and form an early warning index graph on the basis of safe production data and monitoring data of the Internet of things; and (4) quantitatively forming a safe production trend in a certain future interval by utilizing the neural network model, and warning the possible risks in the future interval. The early warning rule customized early warning of the safety risk can prompt safety management personnel at all levels, and the safety management personnel can take different measures, corrections and preventions for the early warning predicted trend or symptom. For example, if the monitoring data of the unit A is lower than a threshold value, abnormal alarm is pushed to a shift keeper to arrange a shift keeper for directional inspection processing according to the formation condition; danger alarm is pushed to a manager of a power generation department, so that effective supervision on the field condition is facilitated, and emergency treatment can be performed according to the field condition.
(5) Various emergency disposal schemes are mainly used for fusing emergency management and early warning prediction functions in an intelligent safety and environmental protection supervision platform. According to the early warning prediction information, the method is associated with site emergency disposal and special emergency disposal schemes, and therefore effective guidance can be provided for managers and site operators at all levels when accidents occur.
(6) And early warning prediction summary, which provides early warning prediction summary reports for personnel at all levels of companies, departments and teams, and can be made, audited and issued in a grading manner and at intervals of time. After the early warning prediction summary report at each level is issued, self-checking, rectification and modification are convenient to carry out from top to bottom, and guarantee is provided for the safe production of subsequent companies.
With the enterprise safety risk early warning and forecasting theory as guidance, as shown in fig. 1 and fig. 2, the invention provides an enterprise safety risk early warning and forecasting system, computer equipment and storage medium, which are based on industrial internet and internet of things technology, integrate an intelligent safety management platform, build an early warning and forecasting management system, quantify the enterprise safety production state, and provide direct, effective, stable and reliable supervision means for safety managers at all levels.
The enterprise safety risk early warning prediction system comprises an early warning parameter configuration module 1, a risk early warning prediction analysis and processing module 2, an early warning information display module 3, an early warning alarm query module 4 and four functional modules.
1. The early warning parameter configuration module 1 is used for maintaining information such as early warning prediction related parameters and indexes, and comprises a parameter configuration submodule 101, an index maintenance submodule 102 and a clustering threshold weight maintenance submodule 103.
(1) And the parameter configuration submodule 101 is used for realizing early warning configuration of unit company level, plant level, department level and team level and maintenance of early warning state values. The method comprises the selection of early warning indexes, the selection of lower-level units and the maintenance of early warning reminding personnel.
The parameter configuration submodule 101 includes:
A. the configuration of early warning parameter information is realized;
B. and the selection of the early warning index and the selection of the reminding personnel are realized.
The parameter configuration submodule 101 maintains the data set as follows:
the parameter configuration sub-module 101 is page designed as shown in FIG. 3.
(2) And the index maintenance submodule 102 is used for maintaining the early warning indexes, and comprises index items, calculation rules and the like.
The index maintenance submodule 102 functions:
A. the maintenance of the early warning index information is realized;
B. and realizing formula configuration of the early warning index.
The metric maintenance submodule 102 maintains the data set as follows:
the page design of the index maintenance sub-module 102 is shown in fig. 4.
(3) And the group threshold weight maintenance submodule 103 is used for carrying out weight division according to the group threshold information and filling safety, attention, warning and upper and lower danger limit values.
The group threshold weight maintenance submodule 103 includes:
A. the safety, attention, warning and the input of upper and lower dangerous limit values are realized;
B. the division of the unit weights is realized, and the total weight is equal to 100%.
The clique threshold weight maintenance submodule 103 maintains the data set as follows:
the clique threshold weight maintenance submodule 103 page design is shown in fig. 5.
2. The risk early warning, predicting, analyzing and processing module 2 is used for analyzing and calculating the safety production data generated by the related business system and the monitoring data of the Internet of things to form an early warning index map; and forming a safe production trend in a certain future interval and warning the possible risks in the future interval. Through carrying out unified processing to different source data, make the discernment to all kinds of risks more comprehensive accurate, prevent because of the risk erroneous judgement or the omission that the monitoring data is incomplete to cause. The early warning information can prompt safety management personnel at all levels, and the safety management personnel can take different measures, corrections and preventions for the early warning predicted trend or symptom. For example, when the safety data of the unit A is lower than a threshold value, an abnormal alarm is pushed to a shift leader, and a shift worker is arranged to perform directional inspection processing according to the formation condition; the danger alarm is pushed to a manager of a power generation department, so that the on-site situation can be effectively monitored, and emergency treatment can be performed according to the on-site situation.
3. The early warning information display module 3 is used for graphically displaying the safety risk early warning conditions of the current-level unit and the lower-level unit and refreshing the safety risk early warning conditions at regular time; and risk trend prediction is displayed, so that related personnel can take preventive measures in advance. The module comprises a company-level early warning indication diagram sub-module 301, a plant-level early warning indication diagram sub-module 302, a department-level early warning indication diagram sub-module 303, a team-level early warning indication diagram sub-module 304 and an index trend diagram sub-module 305.
(1) The company-level early warning indication graph sub-module 301 is used for reflecting real-time early warning indexes and the states of companies in a code table mode and displaying specific early warning index conditions of each affiliated unit through a graph.
Company-level warning indication map sub-module 301 function points:
A. the code table graph reflects the real-time early warning index and the state of the current day (the index is refreshed every half hour);
B. the bar graph is that the early warning indexes and states of the belonged units are arranged from high to low, and the early warning indexes can be traced back to a plant and mine level early warning index graph through clicking of the bar graph;
C. the trend graph is the early warning value trend of 17 days before, the same day and two days in the future of the company.
Company level warning indication map sub-module 301 page layout is shown in fig. 6.
(2) And the plant-level early warning indication graph submodule 302 is used for reflecting the real-time early warning indexes and the states of the units to which the plants belong in a code table mode and displaying the specific early warning index conditions of each unit through a graph.
Factory and mine level early warning indication diagram submodule 302 function points:
A. the code table graph reflects the real-time early warning index and the state of the unit on the same day (the index is refreshed every half hour);
B. the histogram is that all index values forming the unit early warning index belong to are sorted from high to low, and the indexes can be traced back to an index trend graph through the indexes of the histogram;
C. the trend graph is the early warning value trend of the unit for 15 days;
D. the report chart is the calculation description of the index name and the index value.
(3) And the department-level early warning indication graph sub-module 303 is used for reflecting the real-time early warning indexes and the located states of departments in a code table mode and displaying the specific early warning index conditions of the departments through graphs.
Department level early warning indication map module 303 function points:
A. the code table graph reflects the real-time early warning index and the state of the department on the same day (the code table graph is refreshed every half hour);
B. the histogram is that all index values forming the department early warning index are sorted from high to low, and the indexes can be traced back to an index trend graph through the indexes of the histogram;
C. the trend chart is the early warning value trend of the department for 15 days;
D. and the report chart is the calculation description of the index name and the index value.
(4) And the team-level early warning indication map sub-module 304 is used for reflecting the real-time early warning indexes and the states of the teams belonging to the department in a code table mode and displaying the specific early warning index conditions of the teams belonging to the department in a chart mode.
The team class warning indication map sub-module 304 function points:
A. the code table graph reflects the real-time early warning index and the state of the team on the same day (the index is refreshed every half hour);
B. the histogram is that all index values forming the early warning index of the belonging team are sorted from high to low, and the indexes can be traced back to an index trend graph through the indexes of the histogram;
C. the trend graph is the early warning value trend of the team in 15 days;
D. and the report chart is the calculation description of the index name and the index value.
(5) The index trend graph sub-module 305 is used for displaying specific index trend conditions of companies, factories and mines, departments or teams and groups in the form of line graphs and reports, so that problems can be found in advance for rectification, and safe production is guaranteed.
The indicator trend graph sub-module 305 functional points:
A. the discount graph is the value of each time point forming the early warning index of the company, department or group to which the company, department or group belongs;
B. the report chart is the comparison between the statement index value of the index and the early warning alarm value;
C. the report chart is the index name and index value calculation description of the index.
The indicator trend graph sub-module 305 page design is shown in FIG. 7.
4. And the early warning and alarming inquiry module 4 is used for screening and checking specific reminding contents by conditions aiming at the generated index early warning and alarming information.
The early warning and alarming module 4 has the following functional points: and the inquiry of early warning alarm information is realized.
The design of the page of the early warning and alarm query module 4 is shown in fig. 8.
The enterprise safety risk early warning prediction data source comprises remote video monitoring, equipment comprehensive parameters and other related business systems, and the data from different sources are processed in a unified mode, so that various risks are identified more comprehensively and accurately, and risk misjudgment or omission caused by incomplete monitoring data is prevented.
The risk trend prediction is displayed by mining, analyzing and sorting various types of data obtained by remote, real-time and dynamic monitoring of the safety production, so that early discovery, early prevention and early correction of hidden dangers, violation and unsafe behaviors are realized, supervision is advanced by one kilometer, and the management efficiency is improved.
The present invention may also provide a computer apparatus comprising: at least one processor, memory, at least one network interface, and a user interface. The various components in the device are coupled together by a bus system. It will be appreciated that a bus system is used to enable communications among the components. The bus system includes a power bus, a control bus, and a status signal bus in addition to a data bus.
The user interface may include, among other things, a display, a keyboard or a pointing device (e.g., a mouse, track ball), a touch pad or touch screen, etc.
It will be appreciated that the memory in the embodiments disclosed herein can be either volatile memory or nonvolatile memory, or can include both volatile and nonvolatile memory. The non-volatile Memory may be a Read-Only Memory (ROM), a Programmable ROM (PROM), an Erasable PROM (EPROM), an Electrically Erasable PROM (EEPROM), or a flash Memory. Volatile Memory can be Random Access Memory (RAM), which acts as external cache Memory. By way of illustration and not limitation, many forms of RAM are available, such as Static random access memory (Static RAM, SRAM), dynamic Random Access Memory (DRAM), synchronous Dynamic random access memory (Synchronous DRAM, SDRAM), double Data Rate Synchronous Dynamic random access memory (ddr Data Rate SDRAM, ddr SDRAM), enhanced Synchronous SDRAM (ESDRAM), synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The memory described herein is intended to comprise, without being limited to, these and any other suitable types of memory.
In some embodiments, the memory stores elements, executable modules or data structures, or a subset thereof, or an expanded set thereof as follows: an operating system and an application program.
The operating system includes various system programs, such as a framework layer, a core library layer, a driver layer, and the like, and is used for implementing various basic services and processing hardware-based tasks. And the application programs, including various application programs such as a Media Player (Media Player), a Browser (Browser), etc., for implementing various application services. The program for implementing the method of the embodiment of the present disclosure may be included in the application program.
In the above embodiment, the processor is further configured to call a program or an instruction stored in the memory, specifically, a program or an instruction stored in the application program, and is configured to: the functions of the system of embodiment 1 are performed.
The above method may be applied in or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The Processor may be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic device, or discrete hardware components. The methods, steps, and logic blocks disclosed above may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with embodiment 1 may be directly implemented by a hardware decoding processor, or may be implemented by a combination of hardware and software modules in the decoding processor. The software modules may be located in ram, flash, rom, prom, or eprom, registers, etc. as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
It is to be understood that the embodiments described herein may be implemented in hardware, software, firmware, middleware, microcode, or any combination thereof. For a hardware implementation, the Processing units may be implemented within one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), digital Signal Processing Devices (DSPDs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), general purpose processors, controllers, micro-controllers, microprocessors, other electronic units configured to perform the functions described herein, or a combination thereof.
For a software implementation, the techniques of the present invention may be implemented by executing the functional blocks (e.g., procedures, functions, and so on) of the present invention. The software codes may be stored in a memory and executed by a processor. The memory may be implemented within the processor or external to the processor.
The present invention may also provide a non-volatile storage medium for storing a computer program. The computer program may realize the steps of the above-described method embodiments when executed by a processor.
Finally, it should be noted that the above embodiments are only used for illustrating the technical solutions of the present invention and are not limited. Although the present invention has been described in detail with reference to the embodiments, it should be understood by those skilled in the art that the technical solutions of the present invention may be modified or substituted with equivalents without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered by the scope of the claims of the present invention.
Claims (10)
1. An enterprise security risk early warning prediction system, the system comprising: the system comprises an early warning parameter configuration module (1), a risk early warning prediction analysis and processing module (2), an early warning information display module (3) and an early warning alarm query module (4); wherein:
early warning parameter configuration module (1): the system is used for maintaining early warning prediction related parameters and index information;
a risk early warning, predicting, analyzing and processing module (2): the system is used for analyzing and calculating the safety risk condition of an enterprise, recording the risk and sending out early warning to form an early warning index graph; forming a safe production trend in a certain future interval;
early warning information display module (3): the system is used for displaying the safety risk early warning conditions of the current-level unit and the lower-level unit in a graphic mode and refreshing the safety risk early warning conditions at regular time; displaying a risk trend prediction result;
early warning and alarming inquiry module (4): and the method is used for displaying the reminding content of the early warning prediction.
2. The enterprise security risk early warning prediction system according to claim 1, wherein the early warning parameter configuration module (1) comprises a parameter configuration sub-module (101), an index maintenance sub-module (102) and a clustering threshold weight sub-module (103); wherein:
a parameter configuration submodule (101): the system is used for early warning configuration at company level, plant level, department level and team level and maintenance of early warning state values;
an index maintenance submodule (102): the system is used for maintaining early warning indexes, and comprises index items and calculation rules;
clique threshold weight submodule (103): the method is used for carrying out weight division according to the clique threshold information and filling safety, attention, warning and danger upper and lower limit values.
3. The enterprise security risk early warning and forecasting system according to claim 1, wherein the risk early warning, forecasting, analyzing and processing module (2) analyzes and calculates based on internet of things monitoring data and security production data generated by related business systems, and performs unified processing on a plurality of source data to form an early warning index map; forming a safe production trend in a certain interval in the future.
4. The enterprise security risk early warning prediction system according to claim 1, wherein the early warning information display module (3) comprises a company-level early warning indication map sub-module (301), a plant-and-mine-level early warning indication map sub-module (302), a department-level early warning indication map sub-module (303), a team-level early warning indication map sub-module (304) and an index trend map sub-module (305); wherein:
company-level early warning indication map sub-module (301): the early warning system is used for reflecting real-time early warning indexes and the states of companies in a code table mode and displaying the specific early warning index conditions of each affiliated unit through a chart;
factory and mine level early warning indication map sub-module (302): the early warning system is used for reflecting real-time early warning indexes and states of units of factories and mines in a code table mode and displaying specific early warning index conditions of each unit through a chart;
department level early warning indication map sub-module (303): the early warning system is used for reflecting the real-time early warning index and the state of a department in a code table form and displaying the specific early warning index condition of the department in a chart form;
a team class warning indication map sub-module (304): the system is used for reflecting the real-time early warning indexes and the states of the teams and groups to which the departments belong in a code table mode, and displaying the specific early warning index conditions of the teams and groups through a chart;
indicator trend graph submodule (305): the method is used for displaying the specific index trend conditions of companies, factories and mines, departments or teams in the form of line graphs and reports.
5. An enterprise security risk early warning prediction method based on the enterprise security risk early warning prediction system of claim 1, comprising:
the method comprises the steps of obtaining monitoring data of the Internet of things and safety production data generated by a related business system, analyzing and calculating the monitoring data, uniformly processing a plurality of source data, judging a risk condition according to early warning configuration, recording risks and sending early warning; and calculating the safe production trend in a certain interval in the future.
6. The enterprise security risk early warning prediction method of claim 5, further comprising:
and displaying the safety risk early warning condition of the unit at the current level and/or the lower level in a graphic mode, and displaying the risk trend prediction result.
7. The enterprise security risk early warning prediction method of claim 5, further comprising:
and maintaining early warning and predicting related parameters and index information.
8. The enterprise security risk early warning prediction method of claim 5, further comprising:
and screening and checking specific early warning content information through conditions.
9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the method according to any of claims 5 to 8 when executing the computer program.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program which, when executed by a processor, causes the processor to carry out the method of any one of claims 5 to 8.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115729186A (en) * | 2022-11-17 | 2023-03-03 | 华中科技大学 | Safety state multi-mode real-time intelligent control master machine, method and system |
| CN116976547A (en) * | 2023-06-19 | 2023-10-31 | 珠海盈米基金销售有限公司 | Financial report analysis processing method, system, device and medium |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115729186A (en) * | 2022-11-17 | 2023-03-03 | 华中科技大学 | Safety state multi-mode real-time intelligent control master machine, method and system |
| CN115729186B (en) * | 2022-11-17 | 2023-08-25 | 华中科技大学 | Multi-mode real-time intelligent control host machine, method and system for safety state |
| CN116976547A (en) * | 2023-06-19 | 2023-10-31 | 珠海盈米基金销售有限公司 | Financial report analysis processing method, system, device and medium |
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