CN110838023A - Data processing method and device for vehicle purchasing decision - Google Patents
Data processing method and device for vehicle purchasing decision Download PDFInfo
- Publication number
- CN110838023A CN110838023A CN201910982594.3A CN201910982594A CN110838023A CN 110838023 A CN110838023 A CN 110838023A CN 201910982594 A CN201910982594 A CN 201910982594A CN 110838023 A CN110838023 A CN 110838023A
- Authority
- CN
- China
- Prior art keywords
- information
- vehicle
- purchasing decision
- user side
- type
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/02—Marketing; Price estimation or determination; Fundraising
- G06Q30/0201—Market modelling; Market analysis; Collecting market data
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
Landscapes
- Business, Economics & Management (AREA)
- Accounting & Taxation (AREA)
- Finance (AREA)
- Strategic Management (AREA)
- Engineering & Computer Science (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Economics (AREA)
- Marketing (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Data Mining & Analysis (AREA)
- Navigation (AREA)
Abstract
The application discloses a data processing method and device for vehicle purchasing decision making. The method comprises the following steps: receiving a vehicle purchasing decision request of a user side, wherein the vehicle purchasing decision request comprises vehicle type information or route information; calling energy price information corresponding to the vehicle purchasing decision request in a preset database according to the vehicle purchasing decision request of the user side, wherein the energy price information comprises oil price information or electricity price information; determining running cost information corresponding to the vehicle type information according to the vehicle purchasing decision request of the user side and the energy price information; and displaying the running cost information at the user side according to a preset rule. The method and the device solve the technical problem that the efficiency of the user car purchasing decision is low due to the fact that the accurate estimation of the automobile driving cost cannot be carried out in the related technology. Through the method and the device, the purpose of accurately estimating the automobile running cost is achieved, and therefore the technical effect of improving the automobile purchasing decision efficiency of users is achieved.
Description
Technical Field
The application relates to the technical field of automobile big data analysis, in particular to a data processing method and device for automobile purchasing decision.
Background
The decision of purchasing a car is a long process for the consumer, and various factors influence the final choice made by the consumer, and the driving cost is one of the important factors.
In the field of vehicle purchasing decision making, no convenient driving cost calculation system exists at present. For example, when a user buys a vehicle, some service parties can tell the user how much fuel consumption per kilometer of a certain vehicle is increased and how much electricity consumption per kilometer is consumed, but for the user, the driving cost of the user is calculated for the user who specifically buys the type of vehicle and the type of vehicle in real life, and especially when the comparison between a new energy vehicle and a fuel vehicle is involved, the requirement for the user to obtain the driving cost is higher.
Aiming at the problem that the efficiency of the user car purchasing decision is low due to the fact that the accurate estimation of the car driving cost cannot be carried out in the related technology, an effective solution is not provided at present.
Disclosure of Invention
The present application mainly aims to provide a data processing method and device for vehicle purchasing decision, so as to solve the problem of low efficiency of vehicle purchasing decision of a user due to the fact that accurate estimation of vehicle driving cost cannot be performed in the related art.
To achieve the above object, according to one aspect of the present application, there is provided a data processing method for vehicle purchase decision.
The data processing method for vehicle purchasing decision making according to the application comprises the following steps: receiving a vehicle purchasing decision request of a user side, wherein the vehicle purchasing decision request comprises vehicle type information or route information; calling energy price information corresponding to the vehicle purchasing decision request in a preset database according to the vehicle purchasing decision request of the user side, wherein the energy price information comprises oil price information or electricity price information; determining running cost information corresponding to the vehicle type information according to the vehicle purchasing decision request of the user side and the energy price information; and displaying the running cost information at the user side according to a preset rule.
Further, the route information includes city information, the vehicle purchasing decision request from the receiving user side includes, before the vehicle type information or the route information: collecting the vehicle type information and energy consumption information corresponding to the vehicle type information; pulling the energy price information corresponding to the city information based on the city information; and storing the acquisition result and the pulling result in the preset database.
Further, the distance information includes city information or mileage information, the vehicle purchasing decision request from the receiving user side includes, after the vehicle type information or distance information is included in the vehicle purchasing decision request: acquiring the city information and the mileage information set by the user side; calling the energy price information corresponding to the city information according to the city information; and determining the driving cost information according to the city information, the mileage information and the energy price information.
Further, the receiving a vehicle purchasing decision request from a user side, where the vehicle purchasing decision request includes vehicle type information or route information, and then includes: judging the energy consumption type corresponding to the vehicle type information; if the energy consumption type is the oil consumption type, calling oil price information corresponding to the energy consumption type from the preset database; and if the energy consumption type is the electricity consumption type, calling electricity price information corresponding to the energy consumption type from the preset database.
Further, the displaying the driving cost information at the user side according to a preset rule includes: acquiring original price information corresponding to the vehicle type information; processing the driving cost corresponding to the vehicle type information and then sorting the driving cost from low to high; and displaying the original price information corresponding to the vehicle type information and the sequenced driving cost at the user side.
In order to achieve the above object, according to another aspect of the present application, there is provided a data processing apparatus for vehicle purchase decision.
The data processing device for vehicle purchasing decision according to the application comprises: the system comprises a receiving module, a judging module and a judging module, wherein the receiving module is used for receiving a vehicle purchasing decision request of a user side, and the vehicle purchasing decision request comprises vehicle type information or route information; the system comprises a first calling module, a second calling module and a third calling module, wherein the first calling module is used for calling energy price information corresponding to a vehicle purchasing decision request in a preset database according to the vehicle purchasing decision request of a user side, and the energy price information comprises oil price information or electricity price information; the first determining module is used for determining driving cost information corresponding to the vehicle type information according to a vehicle purchasing decision request of the user side and the energy price information; and the display module is used for displaying the driving cost information at the user side according to a preset rule.
Further, the distance information includes city information, and the apparatus further includes: the acquisition module is used for acquiring the vehicle type information and the energy consumption information corresponding to the vehicle type information; a pull module for pulling the energy price information corresponding to the city information based on the city information; and the storage module is used for storing the acquisition result and the pull result into the preset database.
Further, the distance information includes city information or mileage information, and the apparatus further includes: the acquisition module is used for acquiring the city information and the mileage information set by the user side; the second calling module is used for calling the energy price information corresponding to the city information according to the city information; and the second determining module is used for determining the driving cost information according to the city information, the mileage information and the energy price information.
Further, the apparatus further comprises: the judging module is used for judging the energy consumption type corresponding to the vehicle type information; the third calling module is used for calling oil price information corresponding to the energy consumption type from the preset database if the energy consumption type is the oil consumption type; and the fourth calling module is used for calling the electricity price information corresponding to the energy consumption type from the preset database if the energy consumption type is the electricity consumption type.
Further, the display module comprises: an acquisition unit configured to acquire original price information corresponding to the vehicle type information; the processing unit is used for processing the driving cost corresponding to the vehicle type information and then sorting the driving cost from low to high; and the display unit is used for displaying the original price information corresponding to the vehicle type information and the sequenced driving cost at the user side.
In the embodiment of the application, a vehicle purchasing decision request of a receiving user side is adopted, wherein the vehicle purchasing decision request comprises vehicle type information or route information; calling energy price information corresponding to the vehicle purchasing decision request from a preset database according to the vehicle purchasing decision request of the user side; the method for determining the driving cost information corresponding to the vehicle type information according to the vehicle purchasing decision request of the user side and the energy price information achieves the purpose of accurately estimating the vehicle driving cost by displaying the driving cost information at the user side according to the preset rule, thereby achieving the technical effect of improving the vehicle purchasing decision efficiency of a user, and further solving the technical problem of low vehicle purchasing decision efficiency caused by the fact that the accurate estimation of the vehicle driving cost cannot be carried out in the related technology.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, serve to provide a further understanding of the application and to enable other features, objects, and advantages of the application to be more apparent. The drawings and their description illustrate the embodiments of the invention and do not limit it. In the drawings:
fig. 1 is a schematic flow chart of a data processing method for vehicle purchase decision making according to a first embodiment of the present application;
FIG. 2 is a schematic flow chart diagram of a data processing method for vehicle purchasing decision making according to a second embodiment of the present application;
FIG. 3 is a schematic flow chart diagram of a data processing method for vehicle purchasing decision making according to a third embodiment of the present application;
FIG. 4 is a schematic flow chart diagram of a data processing method for vehicle purchasing decision making according to a fourth embodiment of the present application;
FIG. 5 is a schematic flow chart diagram of a data processing method for vehicle purchasing decision making according to a fifth embodiment of the present application;
FIG. 6 is a schematic diagram of a data processing device for vehicle purchasing decision making according to a first embodiment of the present application; and
fig. 7 is a schematic structural diagram of a data processing device for vehicle purchasing decision according to a second embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It should be understood that the data so used may be interchanged under appropriate circumstances such that embodiments of the application described herein may be used. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict. The present application will be described in detail below with reference to the embodiments with reference to the attached drawings.
According to an embodiment of the present invention, there is provided a data processing method for vehicle purchasing decision, as shown in fig. 1, the method includes the following steps S101 to S104:
step S101, a vehicle purchasing decision request of a user side is received, wherein the vehicle purchasing decision request comprises vehicle type information or route information.
In specific implementation, a vehicle purchasing decision request sent by a user side needs to be acquired first, and the vehicle purchasing decision request may include vehicle type information and planned travel distance information intended to be purchased by the user.
Step S102, calling energy price information corresponding to the vehicle purchasing decision request in a preset database according to the vehicle purchasing decision request of the user side, wherein the energy price information comprises oil price information or electricity price information.
In specific implementation, a database can be pre-constructed to store information of various vehicle types, energy consumption types corresponding to each vehicle type, energy price information of each city and the like, such as average electricity prices (prices per degree of electricity) of different cities in the past 1 year and average prices (prices per liter of oil) of different cities in the past 1 year for different fuel types. After a vehicle purchasing decision request of a user is received, specific vehicle type information and route information in the request are identified, namely, a vehicle which the user intends to purchase, a main driving place of the vehicle and the like are judged firstly, and the information is further searched and matched in the preset database, so that the energy type and the corresponding price information which are matched with the vehicle type and the driving place requested by the user are called. For example, the vehicle purchase decision request sent by the user includes: and the vehicle type Audi A4L and the place Shanghai correspondingly acquire the fuel type corresponding to the vehicle type Audi A4L and the price information of the fuel type in Shanghai.
And step S103, determining driving cost information corresponding to the vehicle type information according to the vehicle purchasing decision request of the user side and the energy price information.
In specific implementation, the preset database also stores the hundred kilometers of oil consumption or electricity consumption information corresponding to each type of vehicle, and the driving cost corresponding to the type of vehicle information can be determined by combining the obtained energy price information and the distance information input by the user, such as the driving mileage or the driving starting and stopping point information.
And step S104, displaying the driving cost information at the user side according to a preset rule.
In specific implementation, after the driving cost corresponding to each vehicle type input by the user is determined through the information, the driving cost is displayed according to a certain rule, for example, the driving costs are directly sorted from low to high, or the vehicle type with the minimum driving cost is taken as a reference, the difference value between the driving cost of other vehicle types and the driving cost of the other vehicle types is calculated, and the difference value is displayed according to the sequence from low to high, so that the comparison of the users is facilitated, a reference is made for the vehicle purchasing decision of the users, and the decision efficiency of the users is improved.
As a preferred implementation manner of the embodiment of the present application, as shown in fig. 2, the route information includes city information, and the vehicle purchasing decision request from the receiving user side includes, before the vehicle type information or the route information, the following steps S201 to S203:
step S201, collecting the vehicle type information and energy consumption information corresponding to the vehicle type information.
In specific implementation, before receiving a vehicle purchasing decision request of a user, firstly, information of various vehicle types needs to be collected, and then, energy consumption information matched with the vehicle type is collected, wherein the energy consumption information comprises fuel oil, power consumption information and the like, such as oil consumption of hundreds of kilometers or power consumption of hundreds of kilometers. In addition, it is necessary to determine whether each vehicle type is a fuel vehicle type or an electricity-consuming vehicle type, and if it is a fuel vehicle type, it is necessary to further determine the fuel type.
Step S202, based on the city information, pulling the energy price information corresponding to the city information.
In a specific implementation, the distance information input by the user end may specifically include city information, for example, when the user sends a vehicle purchasing decision request, the user needs to preliminarily determine a main use location of the vehicle purchased by the user, and the use location may be one or multiple. For example, the city information input by the user includes Shanghai and Beijing. Therefore, the average oil price or electricity price information of each city or region in the past period of time needs to be respectively pulled.
And step S203, storing the acquisition result and the pulling result in the preset database.
In specific implementation, the obtained vehicle type information, the energy consumption information corresponding to the vehicle type information and the energy price information corresponding to the city information are all stored in the preset database to serve as a basis for subsequently calling the information according to a user request.
As a preferred implementation manner of the embodiment of the present application, as shown in fig. 3, the route information includes city information or mileage information, and the vehicle purchasing decision request from the receiving user end includes the following steps S301 to S303 after the vehicle purchasing decision request includes vehicle type information or route information:
step S301, the city information and the mileage information set by the user side are obtained.
In specific implementation, after a vehicle purchasing decision request of a user terminal is received, route information input by the user terminal needs to be determined, and the route information specifically includes city information and route information. For example, when a user sends a vehicle purchasing decision request, the user needs to preliminarily determine the main use location of the vehicle purchased by the user, and there may be one or more use locations. For example, the city information input by the user includes Shanghai and Beijing. In addition, in order to enable the prediction of the driving cost to be more accurate, the user can input the driving mileage of the vehicle type, and if the user can not accurately predict the mileage, the user can select a starting point and a terminal point which come and go frequently, and the distance from the starting point to the terminal point is automatically calculated. In addition, different coefficients can be set for different driving paths input by the user to serve as the final mileage. For example, when the user applies the vehicle type to a scene of going to work and going to work, the one-way mileage value can be obtained after the user inputs the place and the home of the work, if the coefficient is 2, the one-way mileage value represents the one-day one-way trip distance, if the coefficient is 40, the one-month one-way trip distance represents the one-month one-way trip distance, and so on. Besides the application scenes of going to work and going to work, other application scenes can be set and input, such as the distance between the old and the current city, the number of times of returning home, multiplied by the coefficient of 2, can be used as the mileage going to and from the old in 1 year, and the scenes of going to and going to school, driving tour and the like of a child can be added. And finally accumulating the mileage of the plurality of application scenes as a total mileage.
Step S302, the energy price information corresponding to the city information is called according to the city information.
In specific implementation, after the city information and the mileage information input by the user are determined, the chargeable price information matched with the city information input by the user is called from the preset database. For example, city information entered by a user includes: and correspondingly acquiring the energy consumption type corresponding to the vehicle type Audi A4L and the price information of the energy consumption type in Shanghai and Beijing respectively from the database at the site-Shanghai/Beijing.
Step S303, determining the driving cost information according to the city information, the mileage information and the energy price information.
And in specific implementation, according to the information of the vehicle type to be purchased by the user, the obtained city information, the mileage information and the energy price information are combined to determine the final driving cost information of the vehicle. For example, if the vehicle model is audi A4L, the fuel consumption per kilometer is 7L/100km, the fuel price of gasoline No. 92 in the past month in shanghai is 6.7 yuan/L, the driving location is shanghai, and the driving mileage is 100 km/month, then the driving cost of audi A4L in one month is 7L/100km, 6.7 yuan/L, or 46.9 yuan.
As a preferred implementation manner of the embodiment of the present application, as shown in fig. 4, after receiving a vehicle purchasing decision request from a user side, the vehicle purchasing decision request further includes the following steps S401 to S403 after including vehicle type information or route information:
and step S401, judging the energy consumption type corresponding to the vehicle type information.
In specific implementation, the existing vehicle types are classified into fuel vehicle types or new energy vehicle types according to energy consumption types, so that after a vehicle purchasing decision request of a user side is received, whether the vehicle type to be purchased by the user is the fuel consumption type or the power consumption type needs to be judged.
Step S402, if the energy consumption type is the oil consumption type, oil price information corresponding to the energy consumption type is called from the preset database.
In specific implementation, if the vehicle type to be purchased by the user is the fuel consumption type, the specific fuel type, such as No. 92 gasoline or No. 95 gasoline, is further determined, and then the fuel prices corresponding to different fuel types are called from the preset database.
Step S403, if the energy consumption type is a power consumption type, retrieving average electricity price information in a period of time corresponding to the energy consumption type from the preset database.
In specific implementation, if the vehicle type to be purchased by the user is the power consumption type, the average oil price information in a corresponding period of time is called from the preset database.
As a preferred implementation manner of the embodiment of the present application, as shown in fig. 5, the displaying, at the user side according to the preset rule, the driving cost information includes the following steps S501 to S503:
step S501, original price information corresponding to the vehicle type information is obtained.
In specific implementation, the preset database also stores average selling price information corresponding to each vehicle type, and after the vehicle type information to be purchased by a user is determined, original price information corresponding to the vehicle type information is called from the database.
Step S502, the driving costs corresponding to the vehicle type information are processed and then sorted from low to high.
Specifically, the driving costs corresponding to the vehicle type information are processed and then sorted in the order from low to high, specifically, the driving costs may be directly sorted in the order from low to high, or the vehicle type with the smallest driving cost may be used as a reference, a difference between the driving costs of other vehicle types and the driving costs of the other vehicle types is calculated, and the differences are sorted in the order from low to high.
Step S503, displaying the original price information corresponding to the vehicle type information and the sorted driving cost at the user side.
In specific implementation, the sorted vehicle type information, the corresponding running cost and the original price information are sent to a user to make reference for a vehicle purchasing decision of the user.
From the above description, it can be seen that the present invention achieves the following technical effects: receiving a vehicle purchasing decision request of a user side, wherein the vehicle purchasing decision request comprises vehicle type information or route information; calling energy price information corresponding to the vehicle purchasing decision request from a preset database according to the vehicle purchasing decision request of the user side; and the driving cost information corresponding to the vehicle type information is determined according to the vehicle purchasing decision request of the user side and the energy price information, and the driving cost information is displayed on the user side according to a preset rule, so that the aim of accurately estimating the driving cost of the vehicle is fulfilled, and the technical effect of improving the vehicle purchasing decision efficiency of the user is realized.
It should be noted that the steps illustrated in the flowcharts of the figures may be performed in a computer system such as a set of computer-executable instructions and that, although a logical order is illustrated in the flowcharts, in some cases, the steps illustrated or described may be performed in an order different than presented herein.
According to an embodiment of the present invention, there is also provided an apparatus for implementing the data processing method for vehicle purchasing decision, as shown in fig. 6, the apparatus includes: the system comprises a receiving module 1, a judging module and a display module, wherein the receiving module 1 is used for receiving a vehicle purchasing decision request of a user side, and the vehicle purchasing decision request comprises vehicle type information or distance information; the first calling module 2 is used for calling energy price information corresponding to the vehicle purchasing decision request from a preset database according to the vehicle purchasing decision request of the user side, wherein the energy price information comprises oil price information or electricity price information 3; the first determining module 4 is used for determining driving cost information corresponding to the vehicle type information according to the vehicle purchasing decision request of the user side and the energy price information; and the display module 4 is used for displaying the driving cost information at the user side according to a preset rule.
In specific implementation, a vehicle purchasing decision request sent by a user side is firstly acquired through a receiving module, and the vehicle purchasing decision request can include vehicle type information and planned travel information which are intended to be purchased by the user. Preferably, the database may be pre-constructed to store various vehicle type information, energy consumption types corresponding to each vehicle type, energy price information of each city, and the like, such as average electricity prices (prices per degree of electricity) of the last 1 year of different cities, average prices (prices per liter of oil) of the last 1 year of different fuel types of different cities. After a vehicle purchasing decision request of a user is received, specific vehicle type information and route information in the request are identified, namely, a vehicle which the user intends to purchase, a main driving place of the vehicle and the like are judged firstly, the information is further searched and matched in the preset database, and the energy type and the corresponding price information which are matched with the vehicle type and the driving place requested by the user are called through the first calling module. For example, the vehicle purchase decision request sent by the user includes: and the vehicle type Audi A4L and the place Shanghai correspondingly acquire the fuel type corresponding to the vehicle type Audi A4L and the price information of the fuel type in Shanghai.
In specific implementation, the preset database also stores the hundred kilometer oil consumption or electricity consumption information corresponding to each type of vehicle, and the first determining module combines the obtained energy price information and the distance information input by the user, such as the driving mileage or the driving starting and stopping point information, so as to determine the driving cost corresponding to the type of vehicle information. After the driving cost corresponding to each vehicle type input by the user is determined through the information, the driving cost is displayed through the display module according to a certain rule, for example, the driving costs are directly sorted from low to high, or the vehicle type with the minimum driving cost is taken as a reference, the difference value between the driving cost of other vehicle types and the driving cost is calculated, and the difference value is displayed from low to high, so that the comparison of the users is facilitated, a reference is made for the vehicle purchasing decision of the users, and the decision efficiency of the users is improved.
As a preferred implementation manner of the embodiment of the present application, as shown in fig. 7, the route information includes city information, and the apparatus further includes: the acquisition module 5 is used for acquiring the vehicle type information and the energy consumption information corresponding to the vehicle type information; a pulling module 6, configured to pull the energy price information corresponding to the city information based on the city information; and the storage module 7 is used for storing the acquisition result and the pull result into the preset database.
As a preferred implementation manner of the embodiment of the present application, the distance information includes city information or mileage information, and the apparatus further includes: the acquisition module is used for acquiring the city information and the mileage information set by the user side; the second calling module is used for calling the energy price information corresponding to the city information according to the city information; and the second determining module is used for determining the driving cost information according to the city information, the mileage information and the energy price information.
As a preferred implementation of the embodiment of the present application, the apparatus further includes: the judging module is used for judging the energy consumption type corresponding to the vehicle type information; the third calling module is used for calling oil price information corresponding to the energy consumption type from the preset database if the energy consumption type is the oil consumption type; and the fourth calling module is used for calling the electricity price information corresponding to the energy consumption type from the preset database if the energy consumption type is the electricity consumption type.
As a preferred implementation of the embodiment of the present application, the display module includes: an acquisition unit configured to acquire original price information corresponding to the vehicle type information; the processing unit is used for processing the driving cost corresponding to the vehicle type information and then sorting the driving cost from low to high; and the display unit is used for displaying the original price information corresponding to the vehicle type information and the sequenced driving cost at the user side.
The detailed relationship between the modules or units in the above device and the functions and functions thereof are described with reference to the detailed description of the method, and are not repeated herein.
It will be apparent to those skilled in the art that the modules or steps of the present invention described above may be implemented by a general purpose computing device, they may be centralized on a single computing device or distributed across a network of multiple computing devices, and they may alternatively be implemented by program code executable by a computing device, such that they may be stored in a storage device and executed by a computing device, or fabricated separately as individual integrated circuit modules, or fabricated as a single integrated circuit module from multiple modules or steps. Thus, the present invention is not limited to any specific combination of hardware and software.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
Claims (10)
1. A data processing method for vehicle purchasing decision is characterized by comprising the following steps:
receiving a vehicle purchasing decision request of a user side, wherein the vehicle purchasing decision request comprises vehicle type information or route information;
calling energy price information corresponding to the vehicle purchasing decision request in a preset database according to the vehicle purchasing decision request of the user side, wherein the energy price information comprises oil price information or electricity price information;
determining running cost information corresponding to the vehicle type information according to the vehicle purchasing decision request of the user side and the energy price information;
and displaying the running cost information at the user side according to a preset rule.
2. The data processing method for vehicle purchasing decision making according to claim 1, wherein the distance information includes city information, the receiving client receives a vehicle purchasing decision request from a client, and the vehicle purchasing decision request includes vehicle type information or distance information, and the step of:
collecting the vehicle type information and energy consumption information corresponding to the vehicle type information;
pulling the energy price information corresponding to the city information based on the city information;
and storing the acquisition result and the pulling result in the preset database.
3. The data processing method for vehicle purchasing decision making according to claim 1, wherein the distance information includes city information or mileage information, the receiving a vehicle purchasing decision request from a user side, the vehicle purchasing decision request including vehicle type information or distance information includes:
acquiring the city information and the mileage information set by the user side;
calling the energy price information corresponding to the city information according to the city information;
and determining the driving cost information according to the city information, the mileage information and the energy price information.
4. The data processing method for vehicle purchasing decision making according to claim 1, wherein the receiving a vehicle purchasing decision request from a user side, the vehicle purchasing decision request including vehicle type information or route information further includes:
judging the energy consumption type corresponding to the vehicle type information;
if the energy consumption type is the oil consumption type, calling oil price information corresponding to the energy consumption type from the preset database;
and if the energy consumption type is the electricity consumption type, calling electricity price information corresponding to the energy consumption type from the preset database.
5. The data processing method for vehicle purchasing decision making according to claim 1, wherein the displaying of the driving cost information at the user side according to a preset rule comprises:
acquiring original price information corresponding to the vehicle type information;
processing the driving cost corresponding to the vehicle type information and then sorting the driving cost from low to high;
and displaying the original price information corresponding to the vehicle type information and the sequenced driving cost at the user side.
6. A data processing apparatus for vehicle purchase decision making, comprising:
the system comprises a receiving module, a judging module and a judging module, wherein the receiving module is used for receiving a vehicle purchasing decision request of a user side, and the vehicle purchasing decision request comprises vehicle type information or route information;
the system comprises a first calling module, a second calling module and a third calling module, wherein the first calling module is used for calling energy price information corresponding to a vehicle purchasing decision request in a preset database according to the vehicle purchasing decision request of a user side, and the energy price information comprises oil price information or electricity price information;
the first determining module is used for determining driving cost information corresponding to the vehicle type information according to a vehicle purchasing decision request of the user side and the energy price information;
and the display module is used for displaying the driving cost information at the user side according to a preset rule.
7. The data processing apparatus for vehicle purchase decision making of claim 6 wherein said distance information comprises city information, said apparatus further comprising:
the acquisition module is used for acquiring the vehicle type information and the energy consumption information corresponding to the vehicle type information;
a pull module for pulling the energy price information corresponding to the city information based on the city information;
and the storage module is used for storing the acquisition result and the pull result into the preset database.
8. The data processing apparatus for vehicle purchase decision making according to claim 6, wherein said journey information comprises city information or mileage information, said apparatus further comprising:
the acquisition module is used for acquiring the city information and the mileage information set by the user side;
the second calling module is used for calling the energy price information corresponding to the city information according to the city information;
and the second determining module is used for determining the driving cost information according to the city information, the mileage information and the energy price information.
9. The data processing apparatus for vehicle purchase decision making of claim 6, further comprising:
the judging module is used for judging the energy consumption type corresponding to the vehicle type information;
the third calling module is used for calling oil price information corresponding to the energy consumption type from the preset database if the energy consumption type is the oil consumption type;
and the fourth calling module is used for calling the electricity price information corresponding to the energy consumption type from the preset database if the energy consumption type is the electricity consumption type.
10. The data processing apparatus for vehicle purchase decision making of claim 6, wherein the display module comprises:
an acquisition unit configured to acquire original price information corresponding to the vehicle type information;
the processing unit is used for processing the driving cost corresponding to the vehicle type information and then sorting the driving cost from low to high;
and the display unit is used for displaying the original price information corresponding to the vehicle type information and the sequenced driving cost at the user side.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910982594.3A CN110838023A (en) | 2019-10-16 | 2019-10-16 | Data processing method and device for vehicle purchasing decision |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910982594.3A CN110838023A (en) | 2019-10-16 | 2019-10-16 | Data processing method and device for vehicle purchasing decision |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110838023A true CN110838023A (en) | 2020-02-25 |
Family
ID=69575335
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910982594.3A Withdrawn CN110838023A (en) | 2019-10-16 | 2019-10-16 | Data processing method and device for vehicle purchasing decision |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110838023A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113032730A (en) * | 2021-03-11 | 2021-06-25 | 武汉理工大学 | Data-driven vehicle TCO intelligent calculation method |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030135427A1 (en) * | 2000-06-26 | 2003-07-17 | Makoto Murakami | Vehicle sales method, server device, and area information displaying and charging system for a car |
| US20140249959A1 (en) * | 2010-08-06 | 2014-09-04 | Hitoshi Ishida | Vehicle evaluation device and vehicle evaluation method |
| US20150106204A1 (en) * | 2013-10-11 | 2015-04-16 | General Motors Llc | Methods for providing a vehicle with fuel purchasing options |
| CN106156871A (en) * | 2015-03-23 | 2016-11-23 | 同济大学 | A kind of electric automobile vehicle system of selection having cost based on Life cycle |
-
2019
- 2019-10-16 CN CN201910982594.3A patent/CN110838023A/en not_active Withdrawn
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20030135427A1 (en) * | 2000-06-26 | 2003-07-17 | Makoto Murakami | Vehicle sales method, server device, and area information displaying and charging system for a car |
| US20140249959A1 (en) * | 2010-08-06 | 2014-09-04 | Hitoshi Ishida | Vehicle evaluation device and vehicle evaluation method |
| US20150106204A1 (en) * | 2013-10-11 | 2015-04-16 | General Motors Llc | Methods for providing a vehicle with fuel purchasing options |
| CN106156871A (en) * | 2015-03-23 | 2016-11-23 | 同济大学 | A kind of electric automobile vehicle system of selection having cost based on Life cycle |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113032730A (en) * | 2021-03-11 | 2021-06-25 | 武汉理工大学 | Data-driven vehicle TCO intelligent calculation method |
| CN113032730B (en) * | 2021-03-11 | 2023-12-05 | 武汉理工大学 | Data-driven vehicle TCO intelligent calculation method |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Gnann et al. | Fast charging infrastructure for electric vehicles: Today’s situation and future needs | |
| Coffman et al. | Electric vehicles revisited: a review of factors that affect adoption | |
| Moon et al. | Forecasting electricity demand of electric vehicles by analyzing consumers’ charging patterns | |
| Faridimehr et al. | A stochastic programming approach for electric vehicle charging network design | |
| Funke et al. | Invest in fast-charging infrastructure or in longer battery ranges? A cost-efficiency comparison for Germany | |
| US20130261953A1 (en) | Route search system and method for electric automobile | |
| CN111612122A (en) | Method and device for predicting real-time demand and electronic equipment | |
| CN105225472A (en) | A kind of share-car method and apparatus | |
| WO2015177644A1 (en) | Method and system for balancing rental fleet of movable assets | |
| Wolbertus et al. | Charging station hogging: A data-driven analysis | |
| US20130335005A1 (en) | Charger information distribution device | |
| CN105279955A (en) | Carpooling method and device | |
| Viswanathan et al. | Development of an assessment model for predicting public electric vehicle charging stations | |
| LUO et al. | Evaluating the impact of autonomous vehicles on accessibility using agent-based simulation—A case study of Gunma Prefecture | |
| Mandev et al. | Empirical charging behavior of plug-in hybrid electric vehicles | |
| Sathaye | The optimal design and cost implications of electric vehicle taxi systems | |
| Sodenkamp et al. | Who can drive electric? Segmentation of car drivers based on longitudinal GPS travel data | |
| Xie et al. | Integrated US nationwide corridor charging infrastructure planning for mass electrification of inter-city trips | |
| CN111815096A (en) | Shared automobile delivery method, electronic device and storage medium | |
| CN111899061A (en) | Order recommendation method, device, equipment and storage medium | |
| CN111815344A (en) | Automobile refueling recommendation method, electronic equipment and storage medium | |
| Zinnari et al. | Electrification potential of fuel-based vehicles and optimal placing of charging infrastructure: a large-scale vehicle-telematics approach | |
| JP2016099704A (en) | Shared-vehicle management apparatus and shared-vehicle management method | |
| Berkelmans et al. | Predicting electric vehicle charging demand using mixed generalized extreme value models with panel effects | |
| CN111861080A (en) | Information processing method and device, electronic equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20200225 |
|
| WW01 | Invention patent application withdrawn after publication |