CN109118348A - Automobile carbon tax method of commerce, cloud platform and computer readable storage medium - Google Patents
Automobile carbon tax method of commerce, cloud platform and computer readable storage medium Download PDFInfo
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Abstract
The invention discloses a kind of automobile carbon tax method of commerce, cloud platform and computer readable storage mediums, this method comprises: obtaining training sample, the training sample is the vehicle exhaust data for training carbon emission Calculating model；According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, to obtain the group based on different carbon emission amount ranges, and determine that each group corresponds to the carbon tax of automobile.The present invention provides relatively simple mode for the transaction of automobile carbon tax, there is good feasibility and operability.
Description
Technical field
The present invention relates to carbon emission reduction technical field more particularly to a kind of automobile carbon tax method of commerce, cloud platform and computer
Readable storage medium storing program for executing.
Background technique
With the rapid development of economy, the people's lives level of consumption is significantly promoted, also with total energy consumption
Constantly soaring, the great amount of carbon dioxide discharged in people's production and living is the primary factor that global climate persistently rises, greenhouse
Effect is inseparable with carbon dioxide.Wherein, as the continuous of automobile is popularized, the CO2 emission problem of automobile is by pass
Note, imposing carbon tax to automobile is the effective behave for cutting down automobile CO2 emission, however, to implement carbon tax friendship to a large amount of automobiles
Easily, feasibility and operability are lower.
Above content is only used to facilitate the understanding of the technical scheme, and is not represented and is recognized that above content is existing skill
Art.
Summary of the invention
The main purpose of the present invention is to provide a kind of automobile carbon tax method of commerce, cloud platform and computer-readable storage mediums
Matter, it is intended to provide relatively simple mode for the transaction of automobile carbon tax, improve the feasibility and operability of the transaction of automobile carbon tax.
To achieve the above object, the present invention provides a kind of automobile carbon tax method of commerce, which comprises
Training sample is obtained, the training sample is the vehicle exhaust data for training carbon emission Calculating model；
According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；
Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, to show that being based on different carbon arranges
The high-volume group of range, and determine that each group corresponds to the carbon tax of automobile.
Optionally, described according to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method
The step of include:
According to the training sample, carbon emission Calculating model is obtained by the training of K-means algorithm.
Optionally, described according to the training sample, the step of carbon emission Calculating model is obtained by the training of K-means algorithm
Suddenly include:
The training sample is clustered by K-means algorithm, the training sample is divided into based on difference
The group of carbon emission amount range, to obtain carbon emission Calculating model.
Optionally, described that the training sample is clustered by K-means algorithm, the training sample is divided
For the group based on different carbon emission amount ranges, so that the step of obtaining carbon emission Calculating model includes:
A, arbitrarily select k carbon emission amount data as initial cluster center from the training sample；
B, the distance between each carbon emission amount data and each initial cluster center in the training sample are calculated；
C, carbon emission amount data each in the training sample are distributed to away from nearest initial cluster center, works as institute
When stating whole carbon emission amount data in training sample and being assigned, the k groups based on different carbon emission amount ranges are obtained；
D, the cluster centre of each group is recalculated according to carbon emission amount data existing in each group, described in calculating
Each carbon emission amount data are at a distance from the cluster centre in training sample, and by carbon emission amount each in the training sample
Data are distributed to away from nearest cluster centre, when whole carbon emission amount data in the training sample are assigned,
Obtain the k groups based on different carbon emission amount ranges；
E, step D is repeated, until meeting preset termination condition, obtains carbon emission Calculating model.
Optionally, described according to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, to obtain base
Include: in the step of group of different carbon emission amount ranges
By the vehicle exhaust data to be measured, the carbon emission Calculating model is substituted into, is obtained based on different carbon emission amounts
The group of range.
Optionally, the step of each group of the determination corresponds to the carbon tax of automobile include:
According to the corresponding carbon emission amount range of each group, the corresponding carbon tax grade of each group is determined；
According to the corresponding carbon tax grade of each group, the carbon tax that each group corresponds to automobile is settled accounts.
Optionally, described according to the corresponding carbon emission amount range of each group, determine the corresponding carbon tax grade of each group
The step of include:
Respectively by the corresponding carbon emission amount range of each group carbon emission amount model corresponding with each carbon tax grade prestored
It encloses and is matched, with the corresponding carbon tax grade of each group of determination.
Optionally, the method also includes:
The carbon tax of clearing is fed back into corresponding automobile, so that corresponding car owner pays carbon tax.
In addition, to achieve the above object, the present invention also provides a kind of cloud platform, the cloud platform includes: memory, processing
Device and the automobile carbon tax transaction program that is stored on the memory and can run on the processor, the automobile carbon tax are handed over
Easy program realizes following steps when being executed by the processor:
Training sample is obtained, the training sample is the vehicle exhaust data for training carbon emission Calculating model；
According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；
Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, to show that being based on different carbon arranges
The high-volume group of range, and determine that each group corresponds to the carbon tax of automobile.
In addition, to achieve the above object, it is described computer-readable the present invention also provides a kind of computer readable storage medium
It is stored with automobile carbon tax transaction program on storage medium, following step is realized when the automobile carbon tax transaction program is executed by processor
It is rapid:
Training sample is obtained, the training sample is the vehicle exhaust data for training carbon emission Calculating model；
According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；
Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, to show that being based on different carbon arranges
The high-volume group of range, and determine that each group corresponds to the carbon tax of automobile.
The present invention obtains training sample first, and the training sample is the vehicle exhaust for training carbon emission Calculating model
Data；Then according to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；Calculate currently
In time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；Calculated according to the carbon emission
Model is analyzed the vehicle exhaust data to be measured, is realized based on carbon emission Calculating model to a large amount of vehicle exhaust data
It is analyzed, to obtain the group based on different carbon emission amount ranges, and then determines that each group corresponds to the carbon tax of automobile, be
The transaction of automobile carbon tax provides relatively simple mode, there is good feasibility and operability.
Detailed description of the invention
Fig. 1 is the terminal structure schematic diagram for the hardware running environment that the embodiment of the present invention is related to；
Fig. 2 is the flow diagram of automobile carbon tax method of commerce first embodiment of the present invention；
Fig. 3 is the refinement flow diagram of automobile carbon tax method of commerce first embodiment of the present invention；
Fig. 4 is another refinement flow diagram of automobile carbon tax method of commerce first embodiment of the present invention；
Fig. 5 is group's schematic diagram that vehicle exhaust data to be measured obtain after the analysis of carbon emission Calculating model.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
The primary solutions of the embodiment of the present invention are: obtaining training sample, the training sample is for training carbon to arrange
Put the vehicle exhaust data of Calculating model；According to the training sample, carbon emission is obtained using the training of unsupervised learning method and is surveyed
Calculate model；Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；Root
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, to obtain based on different carbon emission amount ranges
Group, and determine that each group corresponds to the carbon tax of automobile.
As shown in Figure 1, Fig. 1 is the terminal structure schematic diagram for the hardware running environment that the embodiment of the present invention is related to.
The terminal of that embodiment of the invention is cloud platform.
As shown in Figure 1, the terminal may include: processor 1001, such as CPU, communication bus 1002, user interface
1003, network interface 1004, memory 1005.Wherein, communication bus 1002 is for realizing the connection communication between these components.
User interface 1003 may include display screen (Display), input unit such as keyboard (Keyboard), optional user interface
1003 can also include standard wireline interface and wireless interface.Network interface 1004 optionally may include that the wired of standard connects
Mouth, wireless interface (such as WI-FI interface).Memory 1005 can be high speed RAM memory, be also possible to stable memory
(non-volatile memory), such as magnetic disk storage.Memory 1005 optionally can also be independently of aforementioned processor
1001 storage device.
It will be understood by those skilled in the art that the restriction of the not structure paired terminal of terminal structure shown in Fig. 1, can wrap
It includes than illustrating more or fewer components, perhaps combines certain components or different component layouts.
As shown in Figure 1, as may include that operating system, network are logical in a kind of memory 1005 of computer storage medium
Believe module, Subscriber Interface Module SIM and automobile carbon tax transaction program.
In terminal shown in Fig. 1, network interface 1004 is mainly used for connecting background server, carries out with background server
Data communication；User interface 1003 is mainly used for connecting client (user terminal), carries out data communication with client；And processor
1001 can be used for calling the automobile carbon tax transaction program stored in memory 1005, and execute following operation:
Training sample is obtained, the training sample is the vehicle exhaust data for training carbon emission Calculating model；
According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；
Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, to show that being based on different carbon arranges
The high-volume group of range, and determine that each group corresponds to the carbon tax of automobile.
Further, processor 1001 can call the automobile carbon tax transaction program stored in memory 1005, also execute
It operates below:
According to the training sample, carbon emission Calculating model is obtained by the training of K-means algorithm.
Further, processor 1001 can call the automobile carbon tax transaction program stored in memory 1005, also execute
It operates below:
The training sample is clustered by K-means algorithm, the training sample is divided into based on difference
The group of carbon emission amount range, to obtain carbon emission Calculating model.
Further, processor 1001 can call the automobile carbon tax transaction program stored in memory 1005, also execute
It operates below:
A, arbitrarily select k carbon emission amount data as initial cluster center from the training sample；
B, the distance between each carbon emission amount data and each initial cluster center in the training sample are calculated；
C, carbon emission amount data each in the training sample are distributed to away from nearest initial cluster center, works as institute
When stating whole carbon emission amount data in training sample and being assigned, the k groups based on different carbon emission amount ranges are obtained；
D, the cluster centre of each group is recalculated according to carbon emission amount data existing in each group, described in calculating
Each carbon emission amount data are at a distance from the cluster centre in training sample, and by carbon emission amount each in the training sample
Data are distributed to away from nearest cluster centre, when whole carbon emission amount data in the training sample are assigned,
Obtain the k groups based on different carbon emission amount ranges；
E, step D is repeated, until meeting preset termination condition, obtains carbon emission Calculating model.
Further, processor 1001 can call the automobile carbon tax transaction program stored in memory 1005, also execute
It operates below:
By the vehicle exhaust data to be measured, the carbon emission Calculating model is substituted into, is obtained based on different carbon emission amounts
The group of range.
Further, processor 1001 can call the automobile carbon tax transaction program stored in memory 1005, also execute
It operates below:
According to the corresponding carbon emission amount range of each group, the corresponding carbon tax grade of each group is determined；
According to the corresponding carbon tax grade of each group, the carbon tax that each group corresponds to automobile is settled accounts.
Further, processor 1001 can call the automobile carbon tax transaction program stored in memory 1005, also execute
It operates below:
Respectively by the corresponding carbon emission amount range of each group carbon emission amount model corresponding with each carbon tax grade prestored
It encloses and is matched, with the corresponding carbon tax grade of each group of determination.
Further, processor 1001 can call the automobile carbon tax transaction program stored in memory 1005, also execute
It operates below:
The carbon tax of clearing is fed back into corresponding automobile, so that corresponding car owner pays carbon tax.
Based on above-mentioned terminal hardware structure, the embodiment of automobile carbon tax method of commerce of the present invention is proposed.
The present invention provides a kind of automobile carbon tax method of commerce.
It is the flow diagram of automobile carbon tax method of commerce first embodiment of the present invention referring to Fig. 2, Fig. 2.
In the present embodiment, the automobile carbon tax method of commerce is applied to cloud platform, and the cloud platform is handed over as automobile carbon
Easy settlement platform, establishing with each automobile for being under the jurisdiction of carbon transaction range has communication connection, such as cloud platform can be with a city
The ECU (Electronic Control Unit, electronic control unit) or control loop of each automobile in city establish communication and connect
It connects.The automobile includes tail gas monitoring modular, which can be monitored in real time vehicle exhaust data, and pass through automobile
ECU (Electronic Control Unit, electronic control unit) or control loop send the vehicle exhaust data monitored
To cloud platform.Certainly, cloud platform directly can also establish communication connection with each vehicle exhaust monitoring modular.
The automobile carbon tax method of commerce the following steps are included:
Step S10, obtains training sample, and the training sample is the car tail destiny for training carbon emission Calculating model
According to；；
In the present embodiment, before the step S10, include the steps that acquiring training sample, which is history
Vehicle exhaust data can be acquired by environmental protection administration or Tail gas measuring department, or be acquired by each car OBD interface
The history emission data of automobile ECU storage.Vehicle exhaust data include carbon emission amount, sulfide emission amount, discharged nitrous oxides
Amount and other discharge amount of exhaust gas.It is understood that the training sample is a set, the element for gathering the inside is one by one
Emission data sample, such as:
Training sample=1 emission data sample 1 of automobile, 2 emission data sample 2 of automobile ... automobile n emission data sample
n}
=(1 carbon emission amount 1 of automobile, sulfide emission amount 1, nitrogen oxides carbon emission amount 1, other discharge amount of exhaust gas 1),
(2 carbon emission amount 2 of automobile, sulfide carbon emission amount 2, nitrogen oxides carbon emission amount 2, other discharge amount of exhaust gas 1) ... (automobile n
Carbon emission amount n, sulfide emission amount n, amount of nitrogen oxides n, other discharge amount of exhaust gas n) }.The training sample does not have data
Label, for training carbon emission Calculating model.
Step S20, according to the training sample, using unsupervised learning method training carbon emission Calculating model；Step
S20 may include: to pass through K-means algorithm training carbon emission Calculating model according to the training sample.Wherein, the basis
The step of training sample, carbon emission Calculating model trained by K-means algorithm, may include: by K-means algorithm
The training sample is clustered, the training sample is divided into the group based on different carbon emission amount ranges, thus
Obtain carbon emission Calculating model.
It is described that the training sample is clustered by K-means algorithm referring to Fig. 3, the training sample is drawn
It is divided into the group based on different carbon emission amount ranges, so that the step for obtaining carbon emission Calculating model may include:
Step A, arbitrarily select k carbon emission amount data as initial cluster center from the training sample；
Step B, the distance between each carbon emission amount data and each initial cluster center in the training sample are calculated；
Step C, carbon emission amount data each in the training sample are distributed to away from nearest initial cluster center,
When whole carbon emission amount data in the training sample are assigned, the k groups based on different carbon emission amount ranges are obtained
Group；
Step D, the cluster centre of each group is recalculated according to carbon emission amount data existing in each group, is calculated
Each carbon emission amount data are arranged at a distance from the cluster centre, and by carbon each in the training sample in the training sample
High-volume data are distributed to away from nearest cluster centre, when whole carbon emission amount data in the training sample are assigned
When, obtain the k groups based on different carbon emission amount ranges；
Step E, step D is repeated, until meeting preset termination condition, obtains carbon emission Calculating model.
In the present embodiment, carbon emission Calculating model is obtained using the training of unsupervised learning method, specifically, can passed through
K-means algorithm is trained.K-means algorithm belongs to unsupervised learning, is to adopt typically based on the clustering algorithm of distance very much
Distance is used to think that the distance of two objects is closer, similarity is bigger, which thinks as the evaluation index of similitude
Cluster apart from close object by forming, therefore obtaining compact and independent cluster as final goal.It is calculated by K-means
The process that method training obtains carbon emission Calculating model is as follows:
Arbitrarily select k carbon emission amount data as initial cluster center from n emission data sample of training sample,
The distance between each carbon emission amount data and each initial cluster center in training sample are calculated, carbon each in training sample
Discharge amount data distribute to the cluster centre nearest apart from it, and (cluster centre and the object for distributing to them just represent one and gather
Class), once whole carbon emission amount data in training sample are all assigned, the cluster centre of each cluster can be according in cluster
Existing carbon emission amount data are recalculated, this process is repeated continuous until meeting some termination condition, termination condition
Are as follows: (1) different clusters is reassigned to without object, (2) change again without cluster centre, (3) error sum of squares
Local Minimum, the optional one of three.In this way, the training sample is clustered by K-means algorithm, it can be by training sample
Originally the k groups distinguished with carbon emission amount range are divided into, to obtain carbon emission Calculating model.It is of course also possible to use nothing
Other clustering algorithms training carbon emission Calculating model of supervised learning, the present invention calculate the cluster of training carbon emission Calculating model
Method is not construed as limiting.
Step S30 obtains the car tail to be measured that each vehicle exhaust monitoring module monitors arrive within the currently measuring and calculating time
Destiny evidence；
Step S40 analyzes the vehicle exhaust data to be measured, is based on obtaining according to the carbon emission Calculating model
The group of different carbon emission amount ranges, and determine that each group corresponds to the carbon tax of automobile.
Wherein, described that the vehicle exhaust data to be measured are analyzed according to the carbon emission Calculating model referring to Fig. 4, with
The step of obtaining the group based on different carbon emission amount ranges includes: step S41, by the vehicle exhaust data to be measured, generation
Enter the carbon emission Calculating model, obtains the group based on different carbon emission amount ranges.
The step of each group of determination corresponds to the carbon tax of automobile include:
Step S42 determines the corresponding carbon tax grade of each group according to the corresponding carbon emission amount range of each group；
Step S43 settles accounts the carbon tax that each group corresponds to automobile according to the corresponding carbon tax grade of each group.
Wherein, step S42 may include: each carbon that each will group corresponding carbon emission amount range and prestore respectively
The corresponding carbon emission amount range of tax grade is matched, with the corresponding carbon tax grade of each group of determination.
In the present embodiment, when the automobile for being under the jurisdiction of carbon transaction range belongs to operating status, the tail gas of corresponding automobile at this time
Monitoring modular work, real-time monitoring vehicle emission data, and the vehicle exhaust data monitored (are defined as vapour to be measured
Tail gas data) it is sent directly to cloud platform, or the vehicle exhaust that will be monitored by corresponding automobile ECU or control loop
Data are sent directly to cloud platform.Cloud platform substitutes into the vehicle exhaust data to be measured received within the currently measuring and calculating time
The carbon emission Calculating model that training obtains obtains the group distinguished with carbon emission amount range, can refer to Fig. 5, and Fig. 5 is vapour to be measured
Group's schematic diagram that tail gas data obtain after the analysis of carbon emission Calculating model.Later, according to the corresponding carbon of each group
Discharge amount range determines the corresponding carbon tax grade of each group.In the present embodiment, different carbon taxs are previously stored in cloud platform
Grade and its corresponding tax rate and carbon emission amount range, such as:
| Carbon tax grade | The tax rate | Carbon emission amount range |
| Level-one | x | 0~30 ㎏ |
| Second level | y | 30~80 ㎏ |
| Three-level | z | 80 ㎏ or more |
Specifically, the corresponding carbon emission amount range of each group carbon corresponding with each carbon tax grade prestored is arranged respectively
High-volume range is matched, with the corresponding carbon tax grade of each group of determination, later, according to corresponding carbon tax of each group etc.
Grade, determines the corresponding tax rate, to settle accounts the carbon tax that each group corresponds to automobile.For example, the carbon emission amount range of some group
It for 0~10 ㎏, falls within the scope of the carbon emission amount of level-one carbon tax grade, thus can determine that the carbon tax grade of the group is level-one,
The carbon tax that automobile need to be paid in the group is settled accounts according to the tax rate of level-one.The calculation formula of clearing carbon tax can refer to existing carbon tax meter
Formula is calculated, details are not described herein again.
The carbon tax of clearing is fed back to corresponding automobile, for paying carbon tax for car owner accordingly by step S50.
In the present embodiment, the carbon tax cleared out can also be sent to control loop or the car owner of corresponding automobile by cloud platform
Terminal, so that corresponding car owner pays carbon tax.
The present embodiment obtains training sample first, and the training sample is the car tail for training carbon emission Calculating model
Destiny evidence；Then according to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；It is surveyed currently
In evaluation time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；It is surveyed according to the carbon emission
Model is calculated, the vehicle exhaust data to be measured is analyzed, realizes based on carbon emission Calculating model to a large amount of car tail destiny
According to being analyzed, to obtain the group based on different carbon emission amount ranges, and then determine that each group corresponds to the carbon tax of automobile,
Relatively simple mode is provided for the transaction of automobile carbon tax, there is good feasibility and operability.
In addition, the embodiment of the present invention also proposes a kind of computer readable storage medium.
Automobile carbon tax transaction program, the automobile carbon tax transaction journey are stored on institute's computer readable storage medium of the present invention
Following operation is realized when sequence is executed by processor:
Training sample is obtained, the training sample is the vehicle exhaust data for training carbon emission Calculating model；
According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；
Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, to show that being based on different carbon arranges
The high-volume group of range, and determine that each group corresponds to the carbon tax of automobile.
The specific embodiment of computer readable storage medium of the present invention and each embodiment base of above-mentioned automobile carbon tax method of commerce
This is identical, and therefore not to repeat here.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the system that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or system.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that terminal device (it can be mobile phone,
Computer, server, air conditioner or network equipment etc.) execute method described in each embodiment of the present invention.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of automobile carbon tax method of commerce, which is characterized in that the described method includes:
Training sample is obtained, the training sample is the vehicle exhaust data for training carbon emission Calculating model；
According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；
Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, are based on different carbon emission amounts to obtain
The group of range, and determine that each group corresponds to the carbon tax of automobile.
2. automobile carbon tax method of commerce as described in claim 1, which is characterized in that it is described according to the training sample, it uses
Unsupervised learning method training the step of obtaining carbon emission Calculating model includes:
According to the training sample, carbon emission Calculating model is obtained by the training of K-means algorithm.
3. automobile carbon tax method of commerce as claimed in claim 2, which is characterized in that it is described according to the training sample, pass through
K-means algorithm training the step of obtaining carbon emission Calculating model includes:
The training sample is clustered by K-means algorithm, the training sample is divided into and is arranged based on different carbon
The high-volume group of range, to obtain carbon emission Calculating model.
4. automobile carbon tax method of commerce as claimed in claim 3, which is characterized in that it is described by K-means algorithm to described
Training sample is clustered, and the training sample is divided into the group based on different carbon emission amount ranges, to obtain carbon
Discharge Calculating model the step of include:
A, arbitrarily select k carbon emission amount data as initial cluster center from the training sample；
B, the distance between each carbon emission amount data and each initial cluster center in the training sample are calculated；
C, carbon emission amount data each in the training sample are distributed to away from nearest initial cluster center, when the instruction
When whole carbon emission amount data in white silk sample are assigned, the k groups based on different carbon emission amount ranges are obtained；
D, the cluster centre that each group is recalculated according to carbon emission amount data existing in each group, calculates the training
Each carbon emission amount data are at a distance from the cluster centre in sample, and by carbon emission amount data each in the training sample
It distributes to away from nearest cluster centre, when whole carbon emission amount data in the training sample are assigned, obtains k
A group based on different carbon emission amount ranges；
E, step D is repeated, until meeting preset termination condition, obtains carbon emission Calculating model.
5. automobile carbon tax method of commerce as described in claim 1, which is characterized in that described to calculate mould according to the carbon emission
Type analyzes the vehicle exhaust data to be measured, includes: the step of the group based on different carbon emission amount ranges to obtain
By the vehicle exhaust data to be measured, the carbon emission Calculating model is substituted into, is obtained based on different carbon emission amount ranges
Group.
6. automobile carbon tax method of commerce as claimed in claim 5, which is characterized in that each group of determination corresponds to automobile
The step of carbon tax includes:
According to the corresponding carbon emission amount range of each group, the corresponding carbon tax grade of each group is determined；
According to the corresponding carbon tax grade of each group, the carbon tax that each group corresponds to automobile is settled accounts.
7. automobile carbon tax method of commerce as claimed in claim 6, which is characterized in that described to be arranged according to the corresponding carbon of each group
High-volume range, the step of determining each group corresponding carbon tax grade include:
Respectively by the corresponding carbon emission amount range of each group carbon emission amount range corresponding with each carbon tax grade prestored into
Row matching, with the corresponding carbon tax grade of each group of determination.
8. automobile carbon tax method of commerce as claimed in claim 6, which is characterized in that the method also includes:
The carbon tax of clearing is fed back into corresponding automobile, so that corresponding car owner pays carbon tax.
9. a kind of cloud platform, which is characterized in that the cloud platform includes: memory, processor and is stored on the memory
And the automobile carbon tax transaction program that can be run on the processor, the automobile carbon tax transaction program are executed by the processor
Shi Shixian following steps:
Training sample is obtained, the training sample is the vehicle exhaust data for training carbon emission Calculating model；
According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；
Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, are based on different carbon emission amounts to obtain
The group of range, and determine that each group corresponds to the carbon tax of automobile.
10. a kind of computer readable storage medium, which is characterized in that be stored with automobile carbon on the computer readable storage medium
Tax transaction program, the automobile carbon tax transaction program realize following steps when being executed by processor:
Training sample is obtained, the training sample is the vehicle exhaust data for training carbon emission Calculating model；
According to the training sample, carbon emission Calculating model is obtained using the training of unsupervised learning method；
Within the currently measuring and calculating time, the vehicle exhaust data to be measured that each vehicle exhaust monitoring module monitors arrive are obtained；
According to the carbon emission Calculating model, the vehicle exhaust data to be measured are analyzed, are based on different carbon emission amounts to obtain
The group of range, and determine that each group corresponds to the carbon tax of automobile.
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| CN201810841266.7A CN109118348A (en) | 2018-07-26 | 2018-07-26 | Automobile carbon tax method of commerce, cloud platform and computer readable storage medium |
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| CN201810841266.7A CN109118348A (en) | 2018-07-26 | 2018-07-26 | Automobile carbon tax method of commerce, cloud platform and computer readable storage medium |
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