CN107730425A - Carbon emission amount computational methods, device and storage medium - Google Patents
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Abstract
The invention discloses a kind of carbon emission amount computational methods, device and storage medium, methods described includes：Target vehicle is obtained in history driving information at different moments, historical external environmental information and corresponding actual carbon emission amount, preset relation function is established according to the history driving information, historical external environmental information and corresponding actual carbon emission amount；Obtain the current driving information and environment nowadays information of the target vehicle；Using the current driving information and environment nowadays information as current signature parameter；The current carbon emission amount of the vehicle, the corresponding relation between the preset relation function reflection characteristic parameter and carbon emission amount are calculated by preset relation function according to the current signature parameter.The present invention is calculated the current carbon emission amount of the vehicle by preset relation function, realizes the accurate calculating of the carbon emission amount of vehicle according to the current driving information and environment nowadays information of the vehicle of acquisition.
Description
Technical field
The present invention relates to automobile carbon emission field, more particularly to a kind of carbon emission amount computational methods, device and storage medium.
Background technology
With sharply increasing for urban automobile, traffic pollution turns into the more and more prominent factor of municipal pollution.Traffic is produced
The pollution to urban air, waters and soil such as raw harmful exhaust, flue dust and carbon emission is on the rise.Motor vehicle nytron
Thing, the discharge capacity of carbon monoxide persistently rise, and the carbon emission amount in motor-vehicle tail-gas is as the main of Urban climatic change
Factor, driver, traffic-police, motroist, cyclist and pedestrian are chronically in the environment of air pollution, and car tail gas carbon is arranged
Calculating high-volume is significant to natural environment and climate research, only motor vehicle carbon emission amount is accurately predicted,
Corresponding countermeasure can be found, air quality is lifted, however, in the prior art, how accurately to calculate the carbon emission amount of vehicle also
It is a technical barrier.
The content of the invention
It is a primary object of the present invention to provide a kind of carbon emission amount computational methods, device and storage medium, it is intended to solve
It is above-mentioned how it is accurate calculate vehicle carbon emission amount technical problem.
To achieve the above object, the present invention provides a kind of carbon emission amount computational methods, the carbon emission amount computational methods bag
Include following steps：
Target vehicle is obtained in history driving information at different moments, historical external environmental information and corresponding actual carbon row
High-volume, preset relation letter is established according to the history driving information, historical external environmental information and corresponding actual carbon emission amount
Number；
Obtain the current driving information and environment nowadays information of the target vehicle；
Using the current driving information and environment nowadays information as current signature parameter；
The current carbon emission of the target vehicle is calculated by the preset relation function according to the current signature parameter
Amount.
In one of the embodiments, the acquisition target vehicle is in history driving information, historical external at different moments
Environmental information and corresponding actual carbon emission amount, according to the history driving information, historical external environmental information and corresponding reality
Border carbon emission amount establishes preset relation function, specifically includes：
Target vehicle is obtained in history driving information at different moments, historical external environmental information；
Using the history driving information and historical external environmental information as sample characteristics parameter；
Obtain actual carbon emission amount corresponding to each sample characteristics parameter difference；
The preset relation function is established according to the sample characteristics parameter and corresponding actual carbon emission amount.
In one of the embodiments, it is described that institute is established according to the sample characteristics parameter and corresponding actual carbon emission amount
Preset relation function is stated, is specifically included：
Described preset is established by linear fit algorithm according to the sample characteristics parameter and corresponding actual carbon emission amount
Relation function.
In one of the embodiments, it is described that line is passed through according to the sample characteristics parameter and corresponding actual carbon emission amount
Property fitting algorithm establishes the preset relation function, specifically includes：
The sample characteristics parameter and corresponding actual carbon emission amount are indicated with coordinate system；
The variation tendency of the sample characteristics parameter according to the coordinate system and corresponding actual carbon emission amount enters line
Property fitting, obtain the preset relation function.
In one of the embodiments, it is described that institute is established according to the sample characteristics parameter and corresponding actual carbon emission amount
Preset relation function is stated, is specifically included：
Default disaggregated model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount, obtains institute
State preset relation function.
In one of the embodiments, the default disaggregated model includes：Neural network model；
Correspondingly, it is described that default disaggregated model is carried out based on the sample characteristics parameter and corresponding actual carbon emission amount
Training, obtains the preset relation function, specifically includes：
The neural network model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount, obtained
Obtain the preset relation function.
In one of the embodiments, the default disaggregated model includes：Supporting vector machine model；
Correspondingly, it is described that default disaggregated model is carried out based on the sample characteristics parameter and corresponding actual carbon emission amount
Training, obtains the preset relation function, specifically includes：
The supporting vector machine model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount,
Obtain the preset relation function.
In one of the embodiments, the external environmental information includes：At least one in Weather information and traffic information
Kind；
The driving information includes：The speed of traveling, acceleration, engine speed, mileage information, weight information, oil consumption
At least one of information and exhaust emissions parameter information.
In addition, to achieve the above object, the present invention also proposes a kind of carbon emission amount computing device, and described device includes：Deposit
Reservoir, processor and the carbon emission amount calculation procedure that can be run on the memory and on the processor is stored in, it is described
Carbon emission amount calculation procedure is arranged for carrying out the step of carbon emission amount computational methods as described above.
In addition, to achieve the above object, the present invention also proposes a kind of computer-readable recording medium, described computer-readable
Carbon emission amount calculation procedure is stored with storage medium, is realized when the carbon emission amount calculation procedure is executed by processor as above
The step of described carbon emission amount computational methods.
The present invention is used as current signature parameter by the current driving information and environment nowadays information of vehicle, according to
The current signature parameter calculates the current carbon emission amount of the vehicle by preset relation function, realizes the carbon emission of vehicle
The accurate calculating of amount.
Brief description of the drawings
Fig. 1 is the structural representation of carbon emission amount computing device embodiment of the present invention；
Fig. 2 is a kind of schematic flow sheet of carbon emission amount computational methods first embodiment of the present invention；
Fig. 3 is a kind of schematic flow sheet of carbon emission amount computational methods second embodiment of the present invention；
Fig. 4 is a kind of schematic flow sheet of carbon emission amount computational methods 3rd embodiment of the present invention；
Fig. 5 is a kind of schematic flow sheet of carbon emission amount computational methods fourth embodiment of the present invention；
Fig. 6 is a kind of flow signal of the one of embodiment of carbon emission amount computational methods of the present invention in specific implementation
Figure；
The realization, functional characteristics and advantage of the object of the invention will be described further referring to the drawings in conjunction with the embodiments.
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.
Reference picture 1, Fig. 1 are the carbon emission amount computing device structure for the hardware running environment that scheme of the embodiment of the present invention is related to
Schematic diagram.
As shown in figure 1, the device can include：Processor 1001, such as CPU, communication bus 1002, user interface
1003, network interface 1004, memory 1005, vehicle-mounted bus interface 1006.Wherein, communication bus 1002 is used to realize these groups
Connection communication between part.User interface 1003 can include display screen (Display), input block such as keyboard
(Keyboard), optional user interface 1003 can also include wireline interface, the wave point of standard.Network interface 1004 is optional
Wireline interface, the wave point (such as WI-FI interfaces) that can include standard.Memory 1005 can be high-speed RAM storage
Device or stable memory (non-volatile memory), such as magnetic disk storage.Memory 1005 is optional
It can also be the storage device independently of aforementioned processor 1001.Vehicle-mounted bus interface 1006, can be controller local area network
(Controller Area Network, CAN) EBI.
It will be understood by those skilled in the art that the restriction of the structure shown in Fig. 1 not structure twin installation, can include than
More or less parts are illustrated, either combine some parts or different parts arrangement.
In the device shown in Fig. 1, network interface 1004 is mainly used in connection server, and carrying out data with server leads to
Letter；User interface 1003 is mainly used in connecting user terminal, enters row data communication with user terminal；Vehicle-mounted bus interface 1006 is led
It is used for and the onboard diagnostic system of vehicle (On-Board Diagnostic, OBD) diagnosis seat connection, acquisition vehicle data；
As operating system and carbon emission amount calculation procedure, the dress can be included in a kind of memory 1005 of computer-readable storage medium
Put and the carbon emission amount calculation procedure stored in memory 1005 is called by processor 1001, and perform following operate：
Target vehicle is obtained in history driving information at different moments, historical external environmental information and corresponding actual carbon row
High-volume, preset relation letter is established according to the history driving information, historical external environmental information and corresponding actual carbon emission amount
Number；
Obtain the current driving information and environment nowadays information of the target vehicle；
Using the current driving information and environment nowadays information as current signature parameter；
The current carbon emission of the target vehicle is calculated by the preset relation function according to the current signature parameter
Amount.
In one of the embodiments, processor 1001 can call the carbon emission amount stored in memory 1005 to calculate journey
Sequence, also perform following operate：
Target vehicle is obtained in history driving information at different moments, historical external environmental information；
Using the history driving information and historical external environmental information as sample characteristics parameter；
Obtain actual carbon emission amount corresponding to each sample characteristics parameter difference；
The preset relation function is established according to the sample characteristics parameter and corresponding actual carbon emission amount.
In one of the embodiments, processor 1001 can call the carbon emission amount stored in memory 1005 to calculate journey
Sequence, also perform following operate：
Described preset is established by linear fit algorithm according to the sample characteristics parameter and corresponding actual carbon emission amount
Relation function.
In one of the embodiments, processor 1001 can call the carbon emission amount stored in memory 1005 to calculate journey
Sequence, also perform following operate：
The sample characteristics parameter and corresponding actual carbon emission amount are indicated with coordinate system；
The variation tendency of the sample characteristics parameter according to the coordinate system and corresponding actual carbon emission amount enters line
Property fitting, obtain the preset relation function.
In one of the embodiments, processor 1001 can call the carbon emission amount stored in memory 1005 to calculate journey
Sequence, also perform following operate：
Default disaggregated model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount, obtains institute
State preset relation function.
In one of the embodiments, processor 1001 can call the carbon emission amount stored in memory 1005 to calculate journey
Sequence, also perform following operate：
The neural network model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount, obtained
Obtain the preset relation function.
In one of the embodiments, processor 1001 can call the carbon emission amount stored in memory 1005 to calculate journey
Sequence, also perform following operate：
The supporting vector machine model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount,
Obtain the preset relation function.
The present embodiment such scheme, it is used as by the current driving information and environment nowadays information of target vehicle and is worked as
Preceding characteristic parameter, the current carbon emission amount of the vehicle is calculated by preset relation function according to the current signature parameter, it is real
The accurate calculating of the carbon emission amount of vehicle is showed.
Based on above-mentioned hardware configuration, a kind of carbon emission amount computational methods embodiment of the present invention is proposed.
Reference picture 2, propose a kind of carbon emission amount computational methods first embodiment of the present invention.
In the present embodiment, the carbon emission amount computational methods comprise the following steps：
Step S10, target vehicle is obtained in history driving information at different moments, historical external environmental information and corresponding
Actual carbon emission amount, established according to the history driving information, historical external environmental information and corresponding actual carbon emission amount pre-
If relation function；
Vehicle is in travel speed at different moments, the acceleration of vehicle, the load-carrying of vehicle, the time of traveling and mileage information
Will be different, these driving informations are related to the carbon emission amount of vehicle.How much fast with the traveling of vehicle the exhaust emissions amount of vehicle is
Degree, the acceleration of vehicle, the load-carrying of vehicle, the time of traveling and mileage are related, and when the load-carrying increase of vehicle, vehicle can also consume
More fuel, correspondingly exhaust emissions amount can also increase, the discharge capacity of the mileage number increase then tail gas of vehicle traveling is also corresponding
Increase.In order to more accurately calculate the carbon emission amount of Vehicular exhaust, it is necessary to history driving information and historical external to vehicle
Environmental information carries out data analysis, and in wherein one is applied example, the history driving information includes：The speed of history traveling, add
At least one of speed, engine speed, mileage information, weight information, fuel consumption information and exhaust emissions parameter information.Wherein,
The exhaust emissions parameter includes the temperature and discharge capacity data of tail gas.
It should be noted that the preset relation function is in history driving information at different moments, history according to vehicle
External environmental information and corresponding actual carbon emission amount carry out data analysis, and the traveling obtained using the Algorithm Analysis of correlation is believed
Breath and the relation function between external environmental information and corresponding actual carbon emission amount.The related algorithm includes：Linear Quasi
Hop algorithm, fitting of a polynomial algorithm, trigonometric function fitting algorithm, SVMs or neural network algorithm etc., the present embodiment pair
This is not any limitation as.
Step S20, obtain the current driving information and environment nowadays information of the target vehicle；
It should be understood that the exhaust emissions amount of vehicle how much the travel speed with vehicle, the acceleration of vehicle, the load of vehicle
Weight, the time of traveling and mileage are related, and when the load-carrying increase of vehicle, vehicle can also consume more fuel, and correspondingly tail gas is arranged
High-volume it can also increase, the discharge capacity of the mileage number increase then tail gas of vehicle traveling also accordingly increases.In order to more accurately calculate
The carbon emission amount of Vehicular exhaust is, it is necessary to obtain more comprehensive vehicle traveling information and external environmental information, in the present embodiment, institute
Stating current driving information includes：The current speed of vehicle, acceleration, engine speed, mileage information, weight information, oil consumption letter
At least one of breath and exhaust emissions parameter information.Wherein, the exhaust emissions parameter includes the temperature and discharge capacity number of tail gas
According to.
It should be noted that the acquisition of the driving information can be obtained by number of ways, such as：The OBD of vehicle (is English
Literary On-Board Diagnostic abbreviation, translator of Chinese are ＂ onboard diagnostic system ＂) operation of engine can be monitored at any time
The working condition of situation and exhaust gas aftertreatment system, the then speed of vehicle, acceleration, engine speed, mileage information and oil consumption
Information can all be obtained by the OBD of vehicle.System for monitoring pressure in tyre (Tire Pressure Monitoring System,
TPMS), it is that one kind uses Radio Transmission Technology, is existed using the high-sensitivity miniature wireless sensing device being fixed in automobile tire
The data such as automotive tire pressure, temperature are gathered in the state of driving a vehicle or being static, and are transferred data in the main frame in driver's cabin,
The related data such as real-time display automotive tire pressure and temperature in the form of digitized, and it is (pre- explosion-proof when tire occurs abnormal
Tire) prompting driver carries out the automobile active safety system of early warning in the form of buzzing or voice etc., then and the weight information of vehicle can
To be obtained by system for monitoring pressure in tyre.The temperature and discharge capacity of vehicle exhaust can be obtained by way of remote sensing detection.Institute
Stating the acquisition of driving information can also be obtained by other means, and the present embodiment is not any limitation as to this.
In one of the embodiments, external environmental information includes：At least one of Weather information and traffic information.No
Same weather can also cause to influence accordingly on the exhaust emissions of vehicle, for example rainy weather, road surface slippery situation, vehicle can slow down slowly
OK, power fuel consumption increases, and exhaust emissions amount increases.Road conditions also can cause to influence accordingly on the exhaust emissions amount of vehicle,
For example travelled in die Dorfstrasse, vehicle can consume more fuel to prevent from skidding so that exhaust emissions amount increases；Road
Traffic congestion getting worse, vehicle runs at a low speed to will also result in power fuel and consume for a long time in congested link to be increased,
Exhaust emissions amount increases.
In the specific implementation, in order to accurately calculate the carbon emission amount of vehicle, by by the current line of the target vehicle
Sail information and environment nowadays information is merged, so as to calculate more comprehensively and accurately actual carbon emission amount.
Step S30, using the current driving information and environment nowadays information as current signature parameter；
It should be understood that the current driving information and environmental information of currently going out all have shadow to the carbon emission amount of vehicle
Ring, in order to more accurately calculate the carbon emission amount of Vehicular exhaust, by the vehicle traveling information of acquisition and external environmental information all
As current signature parameter.
Step S40, the current carbon of the target vehicle is calculated by preset relation function according to the current signature parameter
Discharge capacity, the corresponding relation between the preset relation function reflection characteristic parameter and carbon emission amount.
It should be noted that using the current driving information and environment nowadays information of acquisition as current signature
Parameter, you can calculated according to the current signature parameter by preset relation function, obtain the current carbon row of target vehicle
High-volume.The preset relation function is in history driving information at different moments, historical external environment according to the target vehicle
Information and corresponding actual carbon emission amount are trained, learnt, the driving information that is obtained using the Algorithm Analysis of correlation and outer
Relation function between portion's environmental information and corresponding actual carbon emission amount.The related algorithm includes：Linear fit algorithm,
SVMs or neural network algorithm etc., the present embodiment is not any limitation as to this.Then, according to the preset relation function pair of acquisition
The current signature parameter is calculated, you can obtains the current carbon emission amount of the target vehicle.
The present embodiment such scheme, it is used as by the current driving information and environment nowadays information of target vehicle and is worked as
Preceding characteristic parameter, the current carbon emission amount of the vehicle is calculated by preset relation function according to the current signature parameter, it is real
The accurate calculating of the carbon emission amount of vehicle is showed.
In one of the embodiments, as shown in figure 3, proposing that a kind of carbon emission amount of the present invention calculates based on first embodiment
Method second embodiment.
In the present embodiment, the step S10, is specifically included：
Step S101, target vehicle is obtained in history driving information at different moments and historical external environmental information；
Target vehicle is in travel speed at different moments, the acceleration of vehicle, the load-carrying of vehicle, the time of traveling and mileage
Information all can be different, and these driving informations are related to the carbon emission amount of vehicle.The exhaust emissions amount of vehicle how much the row with vehicle
Speed is sailed, the acceleration of vehicle, the load-carrying of vehicle, the time of traveling and mileage are related, and when the load-carrying increase of vehicle, vehicle also can
More fuel are consumed, correspondingly exhaust emissions amount can also increase, the discharge capacity of the mileage number increase then tail gas of vehicle traveling
Corresponding increase.In order to more accurately calculate the carbon emission amount of Vehicular exhaust, it is necessary to history driving information and history to vehicle
External environmental information carries out data analysis, and in one of the embodiments, the history driving information includes：The car of history traveling
At least one of speed, acceleration, engine speed, mileage information, weight information, fuel consumption information and exhaust emissions parameter information.
Wherein, the exhaust emissions parameter includes the temperature and discharge capacity data of tail gas.
It should be noted that the history driving information can be obtained by number of ways, such as：The speed of vehicle, accelerate
Degree, engine speed, mileage information and fuel consumption information can all be obtained by the OBD of vehicle, and the weight information of vehicle can pass through
System for monitoring pressure in tyre is obtained, and the temperature and discharge capacity of vehicle exhaust can be obtained by way of remote sensing detection, can also be passed through
Other modes obtain the historic state parameter information, and the present embodiment is not any limitation as to this.
It should be understood that the historical external environmental information includes at least one of Weather information and traffic information.No
Same weather can also cause to influence accordingly on the exhaust emissions of vehicle, for example foggy weather, low visibility, vehicle can slow down slowly
OK, power fuel consumption increases, and exhaust emissions amount increases.Road conditions also can cause to influence accordingly on the exhaust emissions amount of vehicle,
For example travelled in hill path, vehicle can consume more fuel to climb so that exhaust emissions amount increases；Road traffic congestion
Situation getting worse, vehicle runs at a low speed to will also result in power fuel and consume for a long time in congested link to be increased, exhaust emissions
Amount increases.
Step S102, using the history driving information and historical external environmental information as sample characteristics parameter；
It will be appreciated that in order to obtain the driving information of the target vehicle and external environmental information and corresponding reality
Relation between carbon emission amount, can be to the target vehicle of acquisition in history driving information and historical external at different moments
Environmental information carries out data analysis, study and training, with described in acquisition as sample characteristics parameter to the sample characteristics parameter
Relation between sample characteristics parameter and corresponding actual carbon emission.
Step S103, obtain actual carbon emission amount corresponding to each sample characteristics parameter difference；
It should be understood that actual carbon emission amount at different moments can be obtained by number of ways, such as pass through remote sensing detection
Mode obtain the temperature and discharge capacity of vehicle exhaust.Each sample characteristics parameter of acquisition is entered with corresponding actual carbon emission amount
Line number according to statistics, can form mapping table, for subsequently establishing preset relation function provides data.
Step S104, the preset relation letter is established according to the sample characteristics parameter and corresponding actual carbon emission amount
Number.
It should be noted that obtain substantial amounts of sample characteristics parameter and corresponding actual carbon emission amount, then can be by pre-
Imputation method, data analysis is carried out to the sample characteristics parameter and corresponding actual carbon emission amount, to obtain the sample characteristics
Relation function between parameter and corresponding actual carbon emission amount, that is, establish the preset relation function.The preset algorithm bag
Include：Linear fit algorithm, SVMs or neural network algorithm etc., the present embodiment is not any limitation as to this.
The present embodiment such scheme, by by the target vehicle of acquisition in history driving information at different moments and
Historical external environmental information obtains actual carbon emission amount corresponding to each sample characteristics parameter as sample characteristics parameter, then root
The preset relation function is established according to the sample characteristics parameter and corresponding actual carbon emission amount, make use of substantial amounts of history row
Information, historical external environmental information and corresponding actual carbon emission amount are sailed, can really react each sample parameter and corresponding reality
Relation between the carbon emission of border, so as to the preset relation function established, available for the carbon emission for accurately calculating vehicle
Amount.
In one of the embodiments, as shown in figure 4, proposing that a kind of carbon emission amount of the present invention calculates based on second embodiment
Method 3rd embodiment.
In the present embodiment, the step S104, specifically include：
Step S105, established according to the sample characteristics parameter and corresponding actual carbon emission amount by linear fit algorithm
The preset relation function.
Some discrete function values of certain known function, by adjusting some undetermined coefficients in the function so that the function with
The difference of known point set is minimum.If unJeiermined function is linear, just linear fit is.In the present embodiment, the sample characteristics ginseng
Several and corresponding actual carbon emission amount is some discrete function values of function, it is known that actual carbon corresponding to each sample characteristics parameter
Discharge capacity, then can be by the way that the sample characteristics parameter and corresponding actual carbon emission amount be indicated with coordinate system, and analysis is each
Linear relationship between sample characteristics parameter and corresponding actual carbon emission amount, analyze the ginseng of sample characteristics described in the coordinate system
The variation tendency of several and corresponding actual carbon emission amount, to sample characteristics parameter described in the coordinate system and corresponding actual carbon
Discharge capacity carries out linear fit, and the fitting function of acquisition is as the preset relation function.It is so accurately default in order to obtain
Relation function, it is described that linear fit is passed through according to the sample characteristics parameter and corresponding actual carbon emission amount in the present embodiment
Algorithm establishes the preset relation function, specifically includes：The sample characteristics parameter and corresponding actual carbon emission amount are sat
Mark system is indicated；The variation tendency of the sample characteristics parameter according to the coordinate system and corresponding actual carbon emission amount is entered
Row linear fit, obtain the preset relation function.
It should be understood that in this one of embodiment, the linear fit algorithm can use fitting of a polynomial or triangle
Function Fitting scheduling algorithm replaces, that is to say, that the preset relation function is except according to the sample characteristics parameter and corresponding
Actual carbon emission amount is established by the linear fit algorithm, can also be arranged according to the sample characteristics parameter and corresponding actual carbon
High-volume scheduling algorithm is fitted by fitting of a polynomial or trigonometric function to establish, this is not any limitation as.
The present embodiment such scheme, by using linear fit algorithm, to the sample characteristics parameter and corresponding reality
Carbon emission amount carries out data analysis, so as to obtain the preset relation function, so as to pass through institute according to the current signature parameter
The current carbon emission amount of target vehicle can accurately be calculated by stating preset relation function.
In one of the embodiments, as shown in figure 5, proposing that a kind of carbon emission amount of the present invention calculates based on second embodiment
Method fourth embodiment.
In the present embodiment, the step S104, specifically include：
Step S106, default disaggregated model is instructed based on the sample characteristics parameter and corresponding actual carbon emission amount
Practice, obtain the preset relation function.
It should be understood that machine learning algorithm, which is a kind of automatically analyzed from data, obtains rule, and assimilated equations are not to
The algorithm that primary data is predicted.The sample characteristics parameter and corresponding actual carbon emission amount are entered using machine learning algorithm
Row data analysis, rule is obtained, the default disaggregated model can be the model established using machine learning algorithm, based on described
Sample characteristics parameter and corresponding actual carbon emission amount are trained to default disaggregated model so that the default disaggregated model energy
Enough relations accurately reflected between characteristic parameter and carbon emission amount, so as to obtain the preset relation function.
It should be noted that neutral net is widely interconnected by substantial amounts of, simple processing unit and formed
Complex networks system, it is a highly complex non-linear dynamic learning system.Neutral net has large-scale parallel, distribution
Storage and processing, self-organizing, adaptive and self-learning ability, be particularly suitable for processing needs and meanwhile consider many factors and condition,
Inaccurate and fuzzy information-processing problem.It is described default in the present embodiment in order to obtain the accurate preset relation function
Disaggregated model includes：Neural network model；Correspondingly, it is described to be based on the sample characteristics parameter and corresponding actual carbon emission amount
Default disaggregated model is trained, the preset relation function is obtained, specifically includes：Based on the sample characteristics parameter and right
The actual carbon emission amount answered is trained to the neural network model, obtains the preset relation function.
In the specific implementation, the default disaggregated model can also be other classification moulds except the neural network model
Type, in machine learning, SVMs is the relevant supervised learning model of learning algorithm with correlation, can with analyze data,
Recognition mode, Statistical Learning Theory and Structural risk minization are built upon for classification and regression analysis, support vector machine method
On basis, in the complexity (the study precision i.e. to specific training sample) of model and learned according to limited sample information
Seek optimal compromise between habit ability (ability for identifying arbitrary sample without error), to obtain best Generalization Ability.
In order to obtain the accurate preset relation function, in the present embodiment, the default disaggregated model includes：SVMs mould
Type；It is correspondingly, described that default disaggregated model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount,
The preset relation function is obtained, is specifically included：Based on the sample characteristics parameter and corresponding actual carbon emission amount to described
Supporting vector machine model is trained, and obtains the preset relation function.
It will be appreciated that the default disaggregated model, including neural network model or supporting vector machine model, it can also be
Other disaggregated models, the present embodiment are not any limitation as to this.
The present embodiment such scheme, by the sample characteristics parameter and corresponding actual carbon emission amount to default classification mould
Type is trained, and obtains the preset relation function, and the default disaggregated model includes neural network model or SVMs
Model etc., so that the preset relation function can more accurately reflect characteristic parameter and corresponding actual carbon emission
Relation between amount, so as to can accurately calculate target vehicle by the preset relation function according to the current signature parameter
Current carbon emission amount.
With reference to 3rd embodiment and fourth embodiment, each step is integrated, as shown in fig. 6, to embody the present invention one
Flow chart of the kind carbon emission amount computational methods in specific implementation.
In specific implementation, being calculated by number of ways for the preset relation function obtains, the preset relation function
It can be established according to the sample characteristics parameter and corresponding actual carbon emission amount by the linear fit algorithm, can also be according to institute
State sample characteristics parameter and corresponding actual carbon emission amount and scheduling algorithm foundation is fitted by fitting of a polynomial or trigonometric function.May be used also
By being trained based on the sample characteristics parameter and corresponding actual carbon emission amount to default disaggregated model, obtain described pre-
If relation function.The default disaggregated model can also be supporting vector machine model except the neural network model.
As shown in fig. 6, the mode that the preset relation function is obtained is embodied in mono- step of step S107.
Step S107, linear fit algorithm or is passed through according to the sample characteristics parameter and corresponding actual carbon emission amount more
The fitting of item formula or trigonometric function fitting algorithm establish the preset relation function；Or, based on the sample characteristics parameter and correspondingly
Actual carbon emission amount neural network model or supporting vector machine model are trained, obtain the preset relation function.
In addition, the embodiment of the present invention also proposes a kind of computer-readable recording medium, the computer-readable recording medium
On be stored with carbon emission amount calculation procedure, the carbon emission amount calculation procedure realizes above-mentioned carbon emission gauge when being executed by processor
The step of calculation method.
It should be noted that herein, term " comprising ", "comprising" or its any other variant are intended to non-row
His property includes, so that process, method, article or system including a series of elements not only include those key elements, and
And also include the other element being not expressly set out, or also include for this process, method, article or system institute inherently
Key element.In the absence of more restrictions, the key element limited by sentence "including a ...", it is not excluded that including this
Other identical element also be present in the process of key element, method, article or system.
The embodiments of the present invention are for illustration only, do not represent the quality of embodiment.
Herein, the use of word first, second, and third does not indicate that any order.Can be by these word solutions
It is interpreted as title.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can add the mode of required general hardware platform to realize by software, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on such understanding, technical scheme is substantially done to prior art in other words
Going out the part of contribution can be embodied in the form of software product, and the computer software product is stored in one as described above
In storage medium (such as ROM/RAM, magnetic disc, CD), including some instructions to cause a station terminal equipment (can be mobile phone,
Computer, server, air conditioner, or network equipment etc.) perform method described in each embodiment of the present invention.
The preferred embodiments of the present invention are these are only, are not intended to limit the scope of the invention, it is every to utilize this hair
The equivalent structure or equivalent flow conversion that bright specification and accompanying drawing information is made, or directly or indirectly it is used in other related skills
Art field, is included within the scope of the present invention.
Claims (10)
1. a kind of carbon emission amount computational methods, it is characterised in that the described method comprises the following steps：
Target vehicle is obtained in history driving information at different moments, historical external environmental information and corresponding actual carbon emission
Amount, preset relation function is established according to the history driving information, historical external environmental information and corresponding actual carbon emission amount；
Obtain the current driving information and environment nowadays information of the target vehicle；
Using the current driving information and environment nowadays information as current signature parameter；
The current carbon emission amount of the target vehicle is calculated by the preset relation function according to the current signature parameter.
2. carbon emission amount computational methods as claimed in claim 1, it is characterised in that the acquisition target vehicle is at different moments
History driving information, historical external environmental information and corresponding actual carbon emission amount, according to the history driving information, history
The step of external environmental information and corresponding actual carbon emission amount establish preset relation function, specifically includes：
Target vehicle is obtained in history driving information at different moments, historical external environmental information；
Using the history driving information and historical external environmental information as sample characteristics parameter；
Obtain actual carbon emission amount corresponding to each sample characteristics parameter difference；
The preset relation function is established according to the sample characteristics parameter and corresponding actual carbon emission amount.
3. carbon emission amount computational methods as claimed in claim 2, it is characterised in that it is described according to the sample characteristics parameter and
The step of corresponding actual carbon emission amount establishes the preset relation function, specifically includes：
The preset relation is established by linear fit algorithm according to the sample characteristics parameter and corresponding actual carbon emission amount
Function.
4. carbon emission amount computational methods as claimed in claim 3, it is characterised in that it is described according to the sample characteristics parameter and
The step of corresponding actual carbon emission amount establishes the preset relation function by linear fit algorithm, specifically includes：
The sample characteristics parameter and corresponding actual carbon emission amount are indicated with coordinate system；
The variation tendency of the sample characteristics parameter according to the coordinate system and corresponding actual carbon emission amount carries out Linear Quasi
Close, obtain the preset relation function.
5. carbon emission amount computational methods as claimed in claim 2, it is characterised in that it is described according to the sample characteristics parameter and
The step of corresponding actual carbon emission amount establishes the preset relation function, specifically includes：
Default disaggregated model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount, obtained described pre-
If relation function.
6. carbon emission amount computational methods as claimed in claim 5, it is characterised in that the default disaggregated model includes：Nerve
Network model；
Correspondingly, it is described that default disaggregated model is instructed based on the sample characteristics parameter and corresponding actual carbon emission amount
Practice, obtain the preset relation function, specifically include：
The neural network model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount, obtains institute
State preset relation function.
7. carbon emission amount computational methods as claimed in claim 5, it is characterised in that the default disaggregated model includes：Support
Vector machine model；
Correspondingly, it is described that default disaggregated model is instructed based on the sample characteristics parameter and corresponding actual carbon emission amount
Practice, obtain the preset relation function, specifically include：
The supporting vector machine model is trained based on the sample characteristics parameter and corresponding actual carbon emission amount, obtained
The preset relation function.
8. the carbon emission amount computational methods as described in any one of claim 1 to 7, it is characterised in that the external environment condition letter
Breath includes：At least one of Weather information and traffic information；
The driving information includes：Speed, acceleration, engine speed, mileage information, weight information, the fuel consumption information of traveling
And at least one of exhaust emissions parameter information.
9. a kind of carbon emission amount computing device, it is characterised in that described device includes：Memory, processor and it is stored in described
On memory and the carbon emission amount calculation procedure that can run on the processor, the carbon emission amount calculation procedure is described
The step of carbon emission amount computational methods as any one of claim 1 to 8 are realized during computing device.
10. a kind of computer-readable recording medium, it is characterised in that be stored with carbon emission on the computer-readable recording medium
Calculation procedure is measured, is realized when the carbon emission amount calculation procedure is executed by processor as any one of claim 1 to 8
The step of carbon emission amount computational methods.
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