CN108932595A - A kind of haulage vehicle evaluation method and equipment - Google Patents
A kind of haulage vehicle evaluation method and equipment Download PDFInfo
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Abstract
The embodiment of the present invention provides a kind of haulage vehicle evaluation method and equipment.The method includes：The haulage vehicle detection information and cargo transport demand information in preset time period are obtained, haulage vehicle detection information includes all kinds of website acquisition information and each enterprise's waybill；Calculate the numerical value of each vehicle indications and corresponding each factor；The evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model；Clustering is carried out to the haulage vehicle according to evaluation score and obtains cluster analysis result, target vehicle is obtained according to cluster analysis result.The equipment is for executing the method.The embodiment of the present invention passes through the numerical value according to haulage vehicle detection information and the corresponding factor of cargo transport demand information calculating vehicle transport information, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model, clustering is carried out to haulage vehicle according to evaluation score, target vehicle is obtained, the comprehensive and accuracy of selection target vehicle is improved.
Description
Technical field
The present embodiments relate to field of intelligent transportation technology more particularly to a kind of haulage vehicle evaluation methods and equipment.
Background technique
As information technology is in the deep development of traffic and transport field, using vehicle source information and information of freight source as the logistics of representative
Information resources are more and more abundant, in the application, need from magnanimity information of vehicles comprehensively, fast and accurately selection meet cargo
The high-quality vehicle of transportation demand.
In existing logistics platform technology, the owner of cargo can actively select car owner to haul goods according to vehicle source information, can also be with
Robbing the automatic competition for orders of single-unit and select the owner of cargo by platform.For the owner of cargo selects a kind of this mode of car owner, the owner of cargo is most
It is all to be selected by subjective judgement or platform is recommended according to time priority mechanism or override mechanism of bidding are the owner of cargo
Car owner, such as it is that the owner of cargo selects car owner that override mechanism of bidding, which is to price, competition for orders time, distance,.Since vehicle goods information resources have
Have that data volume is big, updates frequently, the flow velocity of data, flow, flows to the stream datas feature such as complicated and changeable, causing can not basis
The demand of the owner of cargo for its provide comprehensively and accurately high-quality car owner come the problem of service for it.
Summary of the invention
In view of the problems of the existing technology, the embodiment of the present invention provides a kind of haulage vehicle evaluation method and equipment.
In a first aspect, the embodiment of the present invention provides a kind of haulage vehicle evaluation method, including：
Obtain the haulage vehicle detection information and cargo transport demand information in preset time period, the haulage vehicle detection
Information includes all kinds of website acquisition information and each enterprise's waybill；It is transported according to the haulage vehicle detection information and the cargo
Defeated demand information calculates the numerical value of each vehicle indications and corresponding each factor；
According to the numerical value of the corresponding factor of each haulage vehicle, calculated using hierarchical structure hierarchical model each described
The evaluation score of haulage vehicle；
Clustering is carried out to the haulage vehicle according to the evaluation score, cluster analysis result is obtained, according to described
Cluster analysis result obtains target vehicle.
Second aspect, the embodiment of the present invention provide a kind of haulage vehicle valuator device, including：
Module is obtained, for obtaining haulage vehicle detection information and cargo transport demand information in preset time period, institute
Stating haulage vehicle detection information includes all kinds of website acquisition information and each enterprise's waybill；First computing module is used for basis
The haulage vehicle detection information and the cargo transport demand information calculate the number of each vehicle indications and corresponding each factor
Value；
Second computing module utilizes hierarchical structure for the numerical value according to the corresponding factor of each haulage vehicle
Hierarchical model calculates the evaluation score of each haulage vehicle；
Target vehicle obtains module, for carrying out clustering to the haulage vehicle according to the evaluation score, obtains
Cluster analysis result obtains target vehicle according to the cluster analysis result.
The third aspect, the embodiment of the present invention provide another haulage vehicle valuator device, including：Processor, memory and
Bus, wherein
The processor and the memory complete mutual communication by the bus；
The memory is stored with the program instruction that can be executed by the processor, and the processor calls described program to refer to
Order is able to carry out following method：
Obtain the haulage vehicle detection information and cargo transport demand information in preset time period, the haulage vehicle detection
Information includes all kinds of website acquisition information and each enterprise's waybill；It is transported according to the haulage vehicle detection information and the cargo
Defeated demand information calculates the numerical value of each vehicle indications and corresponding each factor；According to each haulage vehicle it is corresponding it is described because
The numerical value of element, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model；
Clustering is carried out to the haulage vehicle according to the evaluation score, cluster analysis result is obtained, according to described
Cluster analysis result obtains target vehicle.
Fourth aspect, the embodiment of the present invention provide a kind of non-transient computer readable storage medium, including：
The non-transient computer readable storage medium stores computer instruction, and the computer instruction makes the computer
Execute following method：
Obtain the haulage vehicle detection information and cargo transport demand information in preset time period, the haulage vehicle detection
Information includes all kinds of website acquisition information and each enterprise's waybill；It is transported according to the haulage vehicle detection information and the cargo
Defeated demand information calculates the numerical value of each vehicle indications and corresponding each factor；According to each haulage vehicle it is corresponding it is described because
The numerical value of element, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model；
Clustering is carried out to the haulage vehicle according to the evaluation score, cluster analysis result is obtained, according to described
Cluster analysis result obtains target vehicle.
A kind of haulage vehicle evaluation method and equipment provided in an embodiment of the present invention, by obtaining the fortune in preset time period
Defeated vehicle detecting information and cargo transport demand information calculate each according to haulage vehicle detection information and cargo transport demand information
The numerical value of a vehicle indications and corresponding factor calculates evaluating for each haulage vehicle using hierarchical structure hierarchical model
Point, clustering is carried out to haulage vehicle according to evaluation score, target vehicle is obtained, improves the comprehensive of selection target vehicle
And accuracy.
Detailed description of the invention
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technical description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Bright some embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is a kind of haulage vehicle evaluation method flow diagram provided in an embodiment of the present invention；
Fig. 2 is hierarchical structure hierarchical model schematic diagram provided in an embodiment of the present invention；
Fig. 3 is a kind of haulage vehicle valuator device structural schematic diagram provided in an embodiment of the present invention；
Fig. 4 be another embodiment of the present invention provides a kind of haulage vehicle valuator device structural schematic diagram；
Fig. 5 is equipment entity structural schematic diagram provided in an embodiment of the present invention.
Specific embodiment
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
Every other embodiment obtained without creative efforts, shall fall within the protection scope of the present invention.
Fig. 1 is a kind of haulage vehicle evaluation method flow diagram provided in an embodiment of the present invention, as shown in Figure 1, described
Method, including：
Step 101：Obtain the haulage vehicle detection information and cargo transport demand information in preset time period, the transport
Vehicle detecting information includes all kinds of website acquisition information and each enterprise's waybill；
Specifically, haulage vehicle valuator device obtains all transports of all haulage vehicles within a preset period of time and corresponds to
Haulage vehicle detection information, wherein haulage vehicle detection information includes all kinds of websites acquisition information and each enterprise's waybill,
Website acquisition system includes non-at-scene enforcement system, high speed previewing system, overload remediation station system etc., and it includes vehicle that website, which acquires information,
The information such as board, car weight, speed, the number of axle；Waybill includes vehicle transport start-stop place, transport cargo type, carrier information
And other items shipping needs information be client submit the relevant information about cargo to be transported, such as：Where cargo type, cargo
Destination, cargo transport time that ground, cargo transport to etc..
Step 102：According to the haulage vehicle detection information and the cargo transport demand information, calculates each vehicle and refer to
The numerical value of mark and corresponding each factor；
Specifically, according to haulage vehicle detection information and cargo transport demand information, all vehicles pair got are calculated
The numerical value of the corresponding each factor of vehicle indications and vehicle indications for each vehicle answered.Wherein information of vehicles includes multiple
Vehicle indications, vehicle indications can be：Vehicle information-carrying, vehicle real time, vehicle operator information, rule-breaking vehicle information and
Vehicle always between customized information.It is understood that vehicle indications can also be other information of vehicles, the embodiment of the present invention
This is not especially limited.Preset time period can be the haulage vehicle information in one month, can also according to the actual situation into
Row adjustment, the present invention is not especially limit this.
In each vehicle indications include Multiple factors, wherein vehicle information-carrying include because being known as：Vehicle/spindle-type,
Maximum pay load, ownership place, traveling classification, transport cargo type, scope of activities, transport number, hauled weight/average load
Weight, transport mileage/average mileage, unloaded number/no-load ratio, goes out to save number average speed/go out hauled weight/average load-carrying and save
Utilization rate, kilometres utilization, punctuality rate when ratio, total vehicle.Vehicle real time include because being known as：Distance, whether off-duty train
, it is whether unloaded, the latest the departure time, the latest arrival time, etc. ETCD estimated time of commencing discharging/driver's time of having a rest.Vehicle operator packet
Include because being known as income, insured amount/number, the maintenance frequency/amount of money.Rule-breaking vehicle information include because being known as；Transfinite number/
Transfinite ratio, 50% number that transfinites/50% ratio that transfinites, hypervelocity number/hypervelocity ratio.Vehicle always between customized information packet
It includes because being known as, according to the corresponding punctuality rate in cargo location and destination, the transport number, transport in cargo transport demand information
Weight/average load-carrying, travelling speed, unloaded number/no-load ratio, rate of actual loading.It should be noted that in above-mentioned each vehicle indications
Including factor can also have other factors, the present invention is not especially limit this.
For example, cargo transport demand information is to transport from Beijing to Tianjin, then vehicle information-carrying, vehicle real time,
Vehicle operator information, rule-breaking vehicle information are comprehensive information of vehicles, the numerical value of corresponding each factor in the synthesis information of vehicles
It is constant, but vehicle always between in customized information the numerical value of corresponding each factor be to be changed according to cargo transport demand information
Become, therefore the numerical value of the corresponding each factor of each haulage vehicle can be calculated according to cargo transport demand information.Such as：
In the 1000 all haulage vehicles all times vehicle transport information in one month, a license plate number is the fortune in capital 12345
Defeated vehicle transported 50 cargos altogether in one month, wherein have 10 times be to transport Tianjin to from Beijing, transported to from Beijing for 15 times
Shijiazhuang.If cargo transport demand information is to transport from Beijing to Tianjin, the transport number in vehicle information-carrying this
The numerical value of the corresponding factor of one factor is 50, vehicle always between transport number this factor in customized information it is corresponding because
Prime number value is 10.But if cargo transport demand information is to transport Shijiazhuang to from Beijing, the transport in vehicle information-carrying
The numerical value of the corresponding factor of this factor of number remains as 50, vehicle always between transport number in customized information this because
The corresponding factor numerical value of element then becomes 15.
Step 103：According to the numerical value of the corresponding factor of each haulage vehicle, hierarchical structure hierarchical model meter is utilized
Calculate the evaluation score of each haulage vehicle；
Specifically, the Multiple factors for the haulage vehicle being calculated and the corresponding numerical value of factor are input to hierarchical structure layer
In secondary model, so that the hierarchical structure hierarchical model can export the corresponding evaluation score of each vehicle.It should be noted that goods
The numerical value of the corresponding factor of factor for the haulage vehicle that object shipping needs information difference is got is also different, so as to obtain,
Different cargo transport demand information can make the evaluation score of haulage vehicle different.
Step 104：Clustering is carried out to the haulage vehicle according to the evaluation score, obtains cluster analysis result,
Target vehicle is obtained according to the cluster analysis result.
Specifically, clustering is carried out to these haulage vehicles according to the evaluation score of more haulage vehicles, is divided into two
Or multiple classifications, for example, according to evaluation score more haulage vehicles can be divided into it is excellent, good, in, poor four class, it is possible to understand that
It is to be further divided into other more careful classifications, the present invention is not especially limit this, from the classification divided
Middle selection target vehicle.
A kind of haulage vehicle evaluation method and equipment provided in an embodiment of the present invention, by obtaining the fortune in preset time period
Defeated vehicle detecting information and cargo transport demand information calculate each vehicle according to detection information and cargo transport demand information and refer to
The numerical value of mark and corresponding factor, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model, according to commenting
Valence score carries out clustering to haulage vehicle, obtains target vehicle, improves the comprehensive and accuracy of selection target vehicle.
On the basis of the above embodiments, the method also includes：
The hierarchical structure hierarchical model is constructed according to the multiple index and the multiple factor, wherein described pass rank knot
Structure hierarchical model includes destination layer, rule layer and sub- rule layer；
The rule layer includes the multiple vehicle indications, constructs the 1st of the rule layer the according to the vehicle indications
Matrix is caused, the corresponding feature vector of first Consistent Matrix is calculated, the vehicle indications pair are obtained according to described eigenvector
The first weight answered；
The sub- rule layer includes the multiple factor, constructs the 2nd 1 of the sub- rule layer the according to the multiple factor
Cause matrix, calculate the corresponding described eigenvector of second Consistent Matrix, according to described eigenvector obtain it is the multiple because
Corresponding second weight of element.
Specifically, Fig. 2 is hierarchical structure hierarchical model schematic diagram provided in an embodiment of the present invention, as shown in Fig. 2, according to fortune
The multiple vehicle indications and Multiple factors of defeated vehicle construct hierarchical structure hierarchical model, and hierarchical structure hierarchical model includes target
Layer, rule layer and sub- rule layer.
Rule layer includes multiple vehicle indications, such as：Vehicle information-carrying, vehicle real time, vehicle operator information, vehicle
Violation information and vehicle always between customized information, establish the first Consistent Matrix of rule layer, wherein the first Consistent Matrix is such as
Shown in formula (1)：
Wherein, aijFor vehicle indications i and vehicle indications j important ratio compared with as a result, m is index number.Index it is important
Property compares to be obtained by experts' evaluation.
Calculate the corresponding feature vector V=(v of the first Consistent Matrix1...vj...vm)T, vjIndicate the first of vehicle indications j
Weight.
Sub- rule layer includes Multiple factors, constructs a second consistent square according to the corresponding Multiple factors of each vehicle indications
Battle array, wherein shown in the second Consistent Matrix such as formula (2)：
Wherein, bijFor factor i and factor j important ratio compared with as a result, n is the number of factor.
Calculate the corresponding characteristic vector W of the second Consistent Matrix=(w1...wi...wn)T, wiThe second weight of expression factor i.
It should be noted that the first Consistent Matrix is to be compared the importance of each vehicle indications in building,
To obtain each of the first Consistent Matrix element, for the vehicle information-carrying in vehicle indications, vehicle operator information
Belong to conventional vehicles index with rule-breaking vehicle information, vehicle real time and vehicle always between customized information belong to personalization
Vehicle indications, therefore personalized vehicle indications are more important for conventional vehicles index.
The embodiment of the present invention is by constructing hierarchical structure hierarchical model according to the vehicle indications and factor of vehicle, by passing rank
Layer of structure model evaluates vehicle from multiple dimensions, improves the accuracy to vehicle evaluation.
On the basis of the above embodiments, the numerical value according to the corresponding factor of each haulage vehicle, utilizes
Hierarchical structure hierarchical model calculates the evaluation score of each haulage vehicle, including：
The numerical value of the factor is normalized, the numerical value of factor after being handled；
The vehicle indications score is obtained according to the numerical value of the factor and second weight；
The haulage vehicle is obtained according to corresponding first weight of the vehicle indications score and the vehicle indications
Evaluation score.
Specifically, in order to by each factor correspond to numerical value from have dimension become dimensionless number according to and by the numerical value of each factor
It is placed on the same order of magnitude, the numerical value of factor is normalized, the numerical value of factor after acquisition processing.According to each vehicle
The numerical value and the second weight of factor, obtain each vehicle indications score after the processing of corresponding Multiple factors of index.Wherein, may be used
To utilize the standardized method of min-max, i.e., according to formulaThe numerical value of factor is normalized,
So that the value range of the numerical value of factor is between 0-1, wherein d*For the numerical value of factor after the processing after normalized, d is
The numerical value of the corresponding factor of factor, max are the numerical value of corresponding the biggest factor of the factor in the more haulage vehicles, and min is
The numerical value of the corresponding minimum factor of the factor in the more haulage vehicles.
The numerical value of the corresponding factor of factor can also be normalized using Z-score standardized method, i.e.,
According to formulaThe numerical value of the corresponding factor of factor is normalized.Wherein d*It is carried out for the numerical value of factor
The numerical value of factor after processing after normalized, d are the numerical value of the corresponding factor of the factor, and μ is the corresponding factor of the factor
Mean value, σ are that the corresponding factor criterion of the factor is poor.
The evaluation score that haulage vehicle is obtained according to each vehicle indications score and corresponding first weight, wherein can be
The evaluation score of haulage vehicle is calculated with the calculation method of weighted sum.
The numerical value of factor after acquisition processing is normalized by the numerical value to factor for the embodiment of the present invention, according to place
The numerical value of factor, the first weight and the second weight obtain the evaluation score of haulage vehicle after reason, to improve calculating transport vehicle
Accuracy.
On the basis of the above embodiments, the vehicle indications include：Vehicle information-carrying, vehicle real time, vehicle
Operation information, rule-breaking vehicle information, vehicle always between customized information.
Specifically, the vehicle indications of each haulage vehicle all include vehicle information-carrying, vehicle real time, vehicle operator
Information, rule-breaking vehicle information, vehicle always between customized information, it should be noted that vehicle indications and may include other
Information, the present invention is not especially limit this.
On the basis of the above embodiments, described that the vehicle is obtained according to the numerical value of the factor and second weight
Index score, including：
According toIt calculates and obtains the vehicle indications score, wherein X is the vehicle indications score, wiFor
Corresponding second weight of the factor i,For the numerical value of factor after the corresponding processing of the factor i, n be it is described because
Plain sum, 1≤i≤n；Correspondingly,
It is described that the transport is obtained according to corresponding first weight of the vehicle indications score and the vehicle indications
The evaluation score of vehicle, including：
According toThe evaluation score for obtaining the haulage vehicle is calculated, wherein Y is described evaluates
Point, vjFor corresponding first weight of vehicle indications j, XjFor the corresponding vehicle indications score of the vehicle indications j, m is
The number of the vehicle indications, 1≤j≤m.
Specifically, it is calculated according to weighted sum algorithm and obtains vehicle indications score, formula isWherein, X
For the vehicle indications score, wiFor corresponding second weight of factor i that the vehicle indications include,For the vehicle indications
Including the corresponding processing of factor i after factor numerical value, n is factor sum, 1≤i≤n.It is understood that such as
Fruit has multiple vehicle indications, then should calculate the corresponding vehicle indications score of each vehicle indications.
The same algorithm for using weighted sum, is transported according to corresponding first weight of vehicle indications score and vehicle indications
The evaluation score of vehicle, specific formula are：Wherein Y is the evaluation score of haulage vehicle, vjFor the transport
Corresponding first weight of the vehicle indications j that vehicle includes, XjThe corresponding vehicle indications of vehicle indications j for including for the haulage vehicle
Score, m are the number of vehicle indications, 1≤j≤m.
A kind of haulage vehicle evaluation method and equipment provided in an embodiment of the present invention, by obtaining the fortune in preset time period
Defeated vehicle detecting information and cargo transport demand information calculate each vehicle according to detection information and cargo transport demand information and refer to
The numerical value of mark and corresponding factor, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model, according to commenting
Valence score carries out clustering to haulage vehicle, obtains target vehicle, improves the comprehensive and accuracy of selection target vehicle.
It is described that cluster point is carried out to the haulage vehicle according to the evaluation score on the basis of the various embodiments described above
Analysis obtains cluster analysis result, obtains target vehicle according to the cluster analysis result, including：
If the evaluation score of the haulage vehicle is greater than preset threshold, high-quality vehicle is set by the haulage vehicle
, using the high-quality vehicle as the target vehicle.
Specifically, according to the evaluation score for more haulage vehicles being calculated and preset threshold to more haulage vehicles
Clustering is carried out, specific analytical method can be, and high-quality vehicle be set by the haulage vehicle for evaluating score >=90, by 90
The haulage vehicle of > evaluation score >=80 is set as good grade vehicle, sets middle rank for the haulage vehicle of 80 > evaluation score >=70
Vehicle sets poor grade vehicle for the haulage vehicle of 70 > evaluation score, recommends the owner of cargo using high-quality vehicle as target vehicle.
It should be noted that above-mentioned preset threshold can be adjusted according to the actual situation, the embodiment of the present invention does not limit this specifically
It is fixed.
Additionally it should explanation, the owner of cargo may not merely consider cargo location and this factor of destination, it may be also
It can go for the closer vehicle location in from origin to destination between two places, vehicle credit height, be selected by more owners of cargo
It selects, vehicle is pair of origin more familiar with destination road, vehicle is sent to more on time or the lower corresponding haulage vehicle of vehicle freight rate
Evaluation score.Such as：This demand closer for vehicle location, i.e. distance of the haulage vehicle apart from cargo location is as one
A important consideration factor can be weighed on the basis of each factor calculated corresponding second weight to second at this time
It is finely adjusted again, the second weight of distance can be increased by 20%, and other factors with distance in the same vehicle indications
It is comprehensive to reduce 20%, the importance of distance can be embodied by improving the second weight of distance in this way, so as to haulage vehicle
Evaluation score be more applicable for the cargo transport demand of the owner of cargo.Cargo that is high for vehicle credit, being selected by more owners of cargo
Transportation demand：Corresponding second weight of transport number of the adjustable haulage vehicle within the certain predetermined period.For vehicle
Pair of origin be more familiar with this cargo transport demand with destination road, it is adjustable always between haulage vehicle transport time
Corresponding second weight of number.Be sent to this cargo transport demand more on time for vehicle, it is adjustable always between transport vehicle
Corresponding second weight of punctuality rate.It is understood that being also possible that other are needed in the cargo transport demand information of the owner of cargo
It asks, the embodiment of the present invention will not enumerate.
A kind of haulage vehicle evaluation method and equipment provided in an embodiment of the present invention, by obtaining the fortune in preset time period
Defeated vehicle detecting information and cargo transport demand information calculate each vehicle according to detection information and cargo transport demand information and refer to
The numerical value of mark and corresponding factor, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model, according to commenting
Valence score carries out clustering to haulage vehicle, obtains target vehicle, improves the comprehensive and accuracy of selection target vehicle.
Fig. 3 is a kind of haulage vehicle valuator device structural schematic diagram provided in an embodiment of the present invention, as shown in figure 3, described
Equipment, including：It obtains module 301, the first computing module 302, the second computing module 303 and target vehicle and obtains module 304,
In：
Module 301 is obtained to be used to obtain the haulage vehicle detection information and cargo transport demand information in preset time period,
The haulage vehicle detection information includes all kinds of website acquisition information and each enterprise's waybill；First computing module 302 is used for
According to the haulage vehicle detection information and the cargo transport demand information, calculates each vehicle indications and correspond to each factor
Numerical value；Second computing module 303 is used to utilize hierarchical structure layer according to the numerical value of the corresponding factor of each haulage vehicle
Secondary model calculates the evaluation score of each haulage vehicle；Target vehicle obtains module 304 and is used for according to the evaluation score pair
The haulage vehicle carries out clustering, obtains cluster analysis result, obtains target vehicle according to the cluster analysis result.
Specifically, it obtains module 301 and obtains the corresponding fortune of all transports of all haulage vehicles within a preset period of time
Defeated vehicle detecting information and cargo transport demand information, wherein haulage vehicle detection information includes all kinds of website acquisition information
With each the first computing module of enterprise's waybill 302 according to haulage vehicle detection information and cargo transport demand information, calculating is obtained
The vehicle indications of the corresponding each vehicle of all vehicles got and the numerical value of the corresponding each factor of vehicle indications.For example,
Cargo transport demand information is to transport from Beijing to Tianjin, then vehicle information-carrying, vehicle real time, vehicle operator information,
Rule-breaking vehicle information is comprehensive information of vehicles, and the numerical value of corresponding each factor is constant in the synthesis information of vehicles, but vehicle
Always the numerical value of corresponding each factor is changed according to cargo transport demand information in customized information between, therefore basis
Cargo transport demand information can calculate the numerical value of the corresponding each factor of each haulage vehicle.Second computing module 303 will
The corresponding numerical value of Multiple factors and factor for the haulage vehicle being calculated is input in hierarchical structure hierarchical model, so that this is passed
Stage structure hierarchical model can export the corresponding evaluation score of each vehicle.It should be noted that cargo transport demand information is not
It is also different with the numerical value of the corresponding factor of factor of the haulage vehicle got, so as to obtain, different cargo transport demands
Information can make the evaluation score of haulage vehicle different.Target vehicle obtains the evaluating according to more haulage vehicles of module 304
Divide and clustering is carried out to these haulage vehicles, be divided into two or more classifications, for example, can be transported more according to evaluation score
Defeated vehicle be divided into it is excellent, good, in, poor four class, it is to be understood that be further divided into other more careful classifications, the present invention is real
It applies example and this is not especially limited, the selection target vehicle from the classification divided.
The embodiment of equipment provided by the invention specifically can be used for executing the process flow of above-mentioned each method embodiment,
Details are not described herein for function, is referred to the detailed description of above method embodiment.
A kind of haulage vehicle evaluation method and equipment provided in an embodiment of the present invention, by obtaining the fortune in preset time period
Defeated vehicle detecting information and cargo transport demand information calculate each vehicle according to detection information and cargo transport demand information and refer to
The numerical value of mark and corresponding factor, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model, according to commenting
Valence score carries out clustering to haulage vehicle, obtains target vehicle, improves the comprehensive and accuracy of selection target vehicle.
On the basis of the above embodiments, Fig. 4 be another embodiment of the present invention provides a kind of haulage vehicle valuator device
Structural schematic diagram, as shown in figure 4, the equipment, including：Obtain module 301, the first computing module 302, the second computing module
303, target vehicle obtains module 304 and model construction module 305 wherein：Model construction module 305 is used for according to the multiple
Index and the multiple factor construct the hierarchical structure hierarchical model, wherein the hierarchical structure hierarchical model includes target
Layer, rule layer and sub- rule layer；The rule layer includes the multiple vehicle indications, constructs the standard according to the vehicle indications
Then the first Consistent Matrix of layer, calculates the corresponding feature vector of first Consistent Matrix, obtains institute according to described eigenvector
State corresponding first weight of vehicle indications；The sub- rule layer includes the multiple factor, constructs institute according to the multiple factor
The second Consistent Matrix of sub- rule layer is stated, the corresponding described eigenvector of second Consistent Matrix is calculated, according to the feature
Vector obtains corresponding second weight of the multiple factor.
Specifically, module 301, the first computing module 302, the second computing module 303 and target vehicle are obtained and obtains module
304 is consistent with above-described embodiment, and details are not described herein again.Model construction module 305 according to multiple vehicle indications of haulage vehicle and
Multiple factors construct hierarchical structure hierarchical model, and hierarchical structure hierarchical model includes destination layer, rule layer and sub- rule layer.Criterion
Layer includes multiple vehicle indications, such as：Vehicle information-carrying, vehicle real time, vehicle operator information, rule-breaking vehicle information and vehicle
Always customized information between establishes the first Consistent Matrix of rule layer, calculates the corresponding feature vector of the first Consistent Matrix,
Each of feature vector being calculated element all indicates the first weight of vehicle indications.Sub- rule layer include it is multiple because
Element constructs second Consistent Matrix according to the corresponding Multiple factors of each vehicle indications, it is corresponding to calculate the second Consistent Matrix
Feature vector calculates the second weight of the element representation factor in the feature vector of the second Consistent Matrix.
More haulage vehicles are gathered according to the evaluation score for more haulage vehicles being calculated and preset threshold
Alanysis, specific analytical method can be, and set high-quality vehicle for the haulage vehicle for evaluating score >=90,90 > are evaluated
The haulage vehicle of score >=80 is set as good grade vehicle, sets intermediate vehicle for the haulage vehicle of 80 > evaluation score >=70,
Poor grade vehicle is set by the haulage vehicle of 70 > evaluation score, recommends the owner of cargo using high-quality vehicle as target vehicle.It should
What is illustrated is that above-mentioned preset threshold can be adjusted according to the actual situation, and the present invention is not especially limit this.
A kind of haulage vehicle evaluation method and equipment provided in an embodiment of the present invention, by obtaining the fortune in preset time period
Defeated vehicle detecting information and cargo transport demand information calculate each vehicle according to detection information and cargo transport demand information and refer to
The numerical value of mark and corresponding factor, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model, according to commenting
Valence score carries out clustering to haulage vehicle, obtains target vehicle, improves the comprehensive and accuracy of selection target vehicle.
Fig. 5 is equipment entity structural schematic diagram provided in an embodiment of the present invention, as shown in figure 5, the equipment, including：Place
Manage device (processor) 501, memory (memory) 502 and bus 503；Wherein,
The processor 501 and memory 502 complete mutual communication by the bus 503；
The processor 501 is used to call the program instruction in the memory 502, to execute above-mentioned each method embodiment
Provided method, for example including：Obtain the haulage vehicle detection information and cargo transport demand information in preset time period, institute
Stating haulage vehicle detection information includes all kinds of website acquisition information and each enterprise's waybill；It is detected and is believed according to the haulage vehicle
Breath and the cargo transport demand information calculate the numerical value of each vehicle indications and corresponding each factor；According to each transport vehicle
The numerical value of the corresponding factor, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model；According to
The evaluation score carries out clustering to the haulage vehicle, cluster analysis result is obtained, according to the cluster analysis result
Obtain target vehicle.
The present embodiment discloses a kind of computer program product, and the computer program product includes being stored in non-transient calculating
Computer program on machine readable storage medium storing program for executing, the computer program include program instruction, when described program instruction is calculated
When machine executes, computer is able to carry out method provided by above-mentioned each method embodiment, for example including：It obtains in preset time period
Haulage vehicle detection information and cargo transport demand information, the haulage vehicle detection information includes all kinds of websites acquisition information
With each enterprise's waybill；According to the haulage vehicle detection information and the cargo transport demand information, each vehicle is calculated
The numerical value of index and corresponding each factor；According to the numerical value of the corresponding factor of each haulage vehicle, hierarchical structure layer is utilized
Secondary model calculates the evaluation score of each haulage vehicle；Cluster point is carried out to the haulage vehicle according to the evaluation score
Analysis obtains cluster analysis result, obtains target vehicle according to the cluster analysis result.
The present embodiment provides a kind of non-transient computer readable storage medium, the non-transient computer readable storage medium
Computer instruction is stored, the computer instruction makes the computer execute method provided by above-mentioned each method embodiment, example
Such as include：Obtain the haulage vehicle detection information and cargo transport demand information in preset time period, the haulage vehicle detection
Information includes all kinds of website acquisition information and each enterprise's waybill；It is transported according to the haulage vehicle detection information and the cargo
Defeated demand information calculates the numerical value of each vehicle indications and corresponding each factor；According to each haulage vehicle it is corresponding it is described because
The numerical value of element, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model；According to the evaluation score pair
The haulage vehicle carries out clustering, obtains cluster analysis result, obtains target vehicle according to the cluster analysis result.This
Field those of ordinary skill is understood that：Realize that all or part of the steps of above method embodiment can pass through program instruction phase
The hardware of pass is completed, and program above-mentioned can be stored in a computer readable storage medium, which when being executed, holds
Row step including the steps of the foregoing method embodiments；And storage medium above-mentioned includes：ROM, RAM, magnetic or disk etc. are various can
To store the medium of program code.
The embodiments such as equipment described above are only schematical, wherein the unit as illustrated by the separation member
It may or may not be physically separated, component shown as a unit may or may not be physics list
Member, it can it is in one place, or may be distributed over multiple network units.It can be selected according to the actual needs
In some or all of the modules achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying creativeness
Labour in the case where, it can understand and implement.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
It realizes by means of software and necessary general hardware platform, naturally it is also possible to pass through hardware.Based on this understanding, on
Stating technical solution, substantially the part that contributes to existing technology can be embodied in the form of software products in other words, should
Computer software product may be stored in a computer readable storage medium, such as ROM/RAM, magnetic disk, CD, including several fingers
It enables and using so that a computer equipment (can be personal computer, server or the network equipment etc.) executes each implementation
Method described in certain parts of example or embodiment.
Finally it should be noted that：The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that：It still may be used
To modify the technical solutions described in the foregoing embodiments or equivalent replacement of some of the technical features；
And these are modified or replaceed, technical solution of various embodiments of the present invention that it does not separate the essence of the corresponding technical solution spirit and
Range.
Claims (10)
1. a kind of haulage vehicle evaluation method, which is characterized in that including：
Obtain the haulage vehicle detection information and cargo transport demand information in preset time period, the haulage vehicle detection information
Information and each enterprise's waybill are acquired including all kinds of websites；
According to the haulage vehicle detection information and the cargo transport demand information, calculate each vehicle indications and it is corresponding it is each because
The numerical value of element；
According to the numerical value of the corresponding factor of each haulage vehicle, hierarchical structure hierarchical model is utilized to calculate each transport
The evaluation score of vehicle；
Clustering is carried out to the haulage vehicle according to the evaluation score, cluster analysis result is obtained, according to the cluster
It analyzes result and obtains target vehicle.
2. the method according to claim 1, wherein the method also includes：
The hierarchical structure hierarchical model is constructed according to the multiple index and the multiple factor, wherein the hierarchical structure layer
Secondary model includes destination layer, rule layer and sub- rule layer；
The rule layer includes the multiple vehicle indications, and the first consistent square of the rule layer is constructed according to the vehicle indications
Battle array calculates the corresponding feature vector of first Consistent Matrix, and it is corresponding to obtain the vehicle indications according to described eigenvector
First weight；
The sub- rule layer includes the multiple factor, and the second consistent square of the sub- rule layer is constructed according to the multiple factor
Battle array, calculates the corresponding described eigenvector of second Consistent Matrix, obtains the multiple factor pair according to described eigenvector
The second weight answered.
3. the method according to claim 1, wherein described according to the corresponding factor of each haulage vehicle
Numerical value, the evaluation score of each haulage vehicle is calculated using hierarchical structure hierarchical model, including：
The numerical value of the factor is normalized, the numerical value of factor after being handled；
The vehicle indications score is obtained according to the numerical value of factor after the processing and second weight；
Commenting for the haulage vehicle is obtained according to corresponding first weight of the vehicle indications score and the vehicle indications
Valence score.
4. the method according to claim 1, wherein the vehicle indications include：Vehicle information-carrying, vehicle are real
When information, vehicle operator information, rule-breaking vehicle information, vehicle always between customized information.
5. according to the method described in claim 3, it is characterized in that, described according to the numerical value of factor after the processing and described
Two weights obtain the vehicle indications score, including：
According toIt calculates and obtains the vehicle indications score, wherein X is the vehicle indications score, wiIt is described
Corresponding second weight of factor i,For the numerical value of factor after the corresponding processing of the factor i, n is that the factor is total
Number, 1≤i≤n；Correspondingly,
It is described that the haulage vehicle is obtained according to corresponding first weight of the vehicle indications score and the vehicle indications
Evaluation score, including：
According toThe evaluation score for obtaining the haulage vehicle is calculated, wherein Y is the evaluation score, vj
For corresponding first weight of vehicle indications j, XjFor the corresponding vehicle indications score of the vehicle indications j, m is described
The number of vehicle indications, 1≤j≤m.
6. method according to claim 1-5, which is characterized in that it is described according to the evaluation score to the fortune
Defeated vehicle carries out clustering, obtains cluster analysis result, obtains target vehicle according to the cluster analysis result, including：
If the evaluation score of the haulage vehicle is greater than preset threshold, high-quality vehicle is set by the haulage vehicle,
Using the high-quality vehicle as the target vehicle.
7. a kind of haulage vehicle valuator device, which is characterized in that including：
Module is obtained, for obtaining haulage vehicle detection information and cargo transport demand information in preset time period, the fortune
Defeated vehicle detecting information includes all kinds of website acquisition information and each enterprise's waybill；
First computing module, for calculating each according to the haulage vehicle detection information and the cargo transport demand information
The numerical value of vehicle indications and corresponding each factor；
Second computing module utilizes hierarchical structure level for the numerical value according to the corresponding factor of each haulage vehicle
Model calculates the evaluation score of each haulage vehicle；
Target vehicle obtains module, for carrying out clustering to the haulage vehicle according to the evaluation score, is clustered
Analysis is as a result, obtain target vehicle according to the cluster analysis result.
8. equipment according to claim 7, which is characterized in that the equipment further includes：
Model construction module, for constructing the hierarchical structure hierarchical model according to the multiple index and the multiple factor,
Wherein the hierarchical structure hierarchical model includes destination layer, rule layer and sub- rule layer；
The rule layer includes the multiple vehicle indications, and the first consistent square of the rule layer is constructed according to the vehicle indications
Battle array calculates the corresponding feature vector of first Consistent Matrix, and it is corresponding to obtain the vehicle indications according to described eigenvector
First weight；
The sub- rule layer includes the multiple factor, and the second consistent square of the sub- rule layer is constructed according to the multiple factor
Battle array, calculates the corresponding described eigenvector of second Consistent Matrix, obtains the multiple factor pair according to described eigenvector
The second weight answered.
9. a kind of haulage vehicle valuator device, which is characterized in that including：Processor, memory and bus, wherein
The processor and the memory complete mutual communication by the bus；
The memory is stored with the program instruction that can be executed by the processor, and the processor calls described program to instruct energy
Enough methods executed as described in claim 1 to 6 is any.
10. a kind of non-transient computer readable storage medium, which is characterized in that the non-transient computer readable storage medium is deposited
Computer instruction is stored up, the computer instruction makes the computer execute the method as described in claim 1 to 6 is any.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111461615A (en) * | 2020-04-07 | 2020-07-28 | 中国民航信息网络股份有限公司 | Method, device and system for calculating luggage processing efficiency |
| CN112581028A (en) * | 2020-12-29 | 2021-03-30 | 安徽运通达物流科技有限公司 | Freight note assignment method in transportation platform |
| CN112926929A (en) * | 2021-04-13 | 2021-06-08 | 车主邦（北京）科技有限公司 | Carrier recommendation method, device, equipment and storage medium |
| CN115330273A (en) * | 2022-10-13 | 2022-11-11 | 永立数智(北京)科技有限公司 | Credit evaluation management method and device for network freight system and electronic equipment |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100913837B1 (en) * | 2006-01-10 | 2009-08-26 | 주식회사 엘지화학 | Method for Optimal Multi-Vehicle Dispatch and System for the Same |
| CN102592449A (en) * | 2012-01-21 | 2012-07-18 | 北京万集科技股份有限公司 | Off-site enforcement system for overloaded vehicle |
| CN202584421U (en) * | 2012-01-21 | 2012-12-05 | 北京万集科技股份有限公司 | A non on-site law enforcing system for vehicle overload |
| CN103413438A (en) * | 2013-08-26 | 2013-11-27 | 常熟市公安局交通巡逻警察大队 | Vehicle-mounted mobile police service law enforcement platform |
| CN104463548A (en) * | 2014-12-25 | 2015-03-25 | 南京大学 | Carriage quantitative selection method influenced by multiple factors |
| CN104867039A (en) * | 2015-06-09 | 2015-08-26 | 南京大学 | Vehicle member derivative credit evaluation method under influence of many factors |
| CN205594881U (en) * | 2016-05-16 | 2016-09-21 | 杭州智诚惠通科技有限公司 | Super non -at -scene law enforcement system is controlled to highway |
| CN106203867A (en) * | 2016-07-19 | 2016-12-07 | 国家电网公司 | Grid division methods based on power distribution network assessment indicator system and cluster analysis |
| CN106228499A (en) * | 2016-07-06 | 2016-12-14 | 东南大学 | A kind of cargo security evaluation model based on people's bus or train route goods multi-risk System source |
-
2017
- 2017-05-24 CN CN201710374676.0A patent/CN108932595A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100913837B1 (en) * | 2006-01-10 | 2009-08-26 | 주식회사 엘지화학 | Method for Optimal Multi-Vehicle Dispatch and System for the Same |
| CN102592449A (en) * | 2012-01-21 | 2012-07-18 | 北京万集科技股份有限公司 | Off-site enforcement system for overloaded vehicle |
| CN202584421U (en) * | 2012-01-21 | 2012-12-05 | 北京万集科技股份有限公司 | A non on-site law enforcing system for vehicle overload |
| CN103413438A (en) * | 2013-08-26 | 2013-11-27 | 常熟市公安局交通巡逻警察大队 | Vehicle-mounted mobile police service law enforcement platform |
| CN104463548A (en) * | 2014-12-25 | 2015-03-25 | 南京大学 | Carriage quantitative selection method influenced by multiple factors |
| CN104867039A (en) * | 2015-06-09 | 2015-08-26 | 南京大学 | Vehicle member derivative credit evaluation method under influence of many factors |
| CN205594881U (en) * | 2016-05-16 | 2016-09-21 | 杭州智诚惠通科技有限公司 | Super non -at -scene law enforcement system is controlled to highway |
| CN106228499A (en) * | 2016-07-06 | 2016-12-14 | 东南大学 | A kind of cargo security evaluation model based on people's bus or train route goods multi-risk System source |
| CN106203867A (en) * | 2016-07-19 | 2016-12-07 | 国家电网公司 | Grid division methods based on power distribution network assessment indicator system and cluster analysis |
Non-Patent Citations (1)
| Title |
|---|
| 姚国龙: ""基于精益物流的车货匹配综合评价与优化"", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111461615A (en) * | 2020-04-07 | 2020-07-28 | 中国民航信息网络股份有限公司 | Method, device and system for calculating luggage processing efficiency |
| CN112581028A (en) * | 2020-12-29 | 2021-03-30 | 安徽运通达物流科技有限公司 | Freight note assignment method in transportation platform |
| CN112926929A (en) * | 2021-04-13 | 2021-06-08 | 车主邦（北京）科技有限公司 | Carrier recommendation method, device, equipment and storage medium |
| CN115330273A (en) * | 2022-10-13 | 2022-11-11 | 永立数智(北京)科技有限公司 | Credit evaluation management method and device for network freight system and electronic equipment |
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