CN110069482A - A kind of data cleaning method predicted for sharing automobile demand - Google Patents
A kind of data cleaning method predicted for sharing automobile demand Download PDFInfo
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- CN110069482A CN110069482A CN201910340014.0A CN201910340014A CN110069482A CN 110069482 A CN110069482 A CN 110069482A CN 201910340014 A CN201910340014 A CN 201910340014A CN 110069482 A CN110069482 A CN 110069482A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
- G06F16/215—Improving data quality; Data cleansing, e.g. de-duplication, removing invalid entries or correcting typographical errors
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- 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
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- G06Q30/0201—Market modelling; Market analysis; Collecting market data
- G06Q30/0202—Market predictions or forecasting for commercial activities
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- 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
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- G06Q30/0645—Rental transactions; Leasing transactions
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Abstract
The present invention relates to a kind of for sharing the data cleaning method of automobile demand prediction, extracts the data opened with all client applications of once interaction including (1)；(2) all sites in interaction 5 kilometer range of spot are obtained and whether there is or not the data wait hire a car for corresponding site when this time interaction occurs；(3) whether there is or not the data for carrying out lower single operation after acquisition this time interaction；(4) the process id of this opening client application is belonged to and is interacted spot apart from nearest site；(5) it obtains and carries out the longest pick-up walking distance that the success of this time user of interaction places an order；(6) all site information in user's longest pick-up walking distance are obtained；(7) determine whether wait hire a car；(8) this data result interacted is belonged to and interacts spot apart from nearest site, cleaned data and finish.The validity of present invention guarantee data；Dirty data will not be adulterated, improves forecasting accuracy, while reducing the model calculation time.
Description
Technical field
The invention belongs to share automotive field, and in particular to a kind of for sharing the data cleansing side of automobile demand prediction
Method.
Background technique
" Car sharing " comes across the last century 40's earliest, is invented by Swiss.They have organized " self-driving in the whole nation
Vehicle cooperative society ", this mountainous region country as Switzerland is very useful, after a people is finished vehicle, just gives car key next
People is easier than establishing network in level land country.
The states such as later Japan, Britain fall over each other to imitate, but all not formed scale.Japan is primarily due to automaker and does not prop up
Hold this plan, Japanese likes possessing oneself a private car.And Britain is although obtain governmental support, automobile leasing expense
It is cheap, to hinder the development of " Car sharing ".
Currently, in the shared automobile for having had already appeared multiple companies in the street of China, but at present for sharing automobile
Requirement forecasting be still within research and development and exploratory stage, the requirement forecasting of shared automobile is conducive to maximumlly bring row of hiring a car together
For.But the data of requirement forecasting are simply cleaned mostly or are applied without cleaning, and then lead to current share
The requirement forecasting of automobile has the following disadvantages:
1. not can guarantee the validity of data；
2. dirty data can be adulterated, forecasting accuracy is influenced.
Summary of the invention
Goal of the invention: the present invention has made improvements in view of the above-mentioned problems of the prior art, i.e., the invention discloses one kind
For sharing the data cleaning method of automobile demand prediction, one is made accurately for original data required for requirement forecasting
Data cleansing.
Technical solution: a kind of for sharing the data cleaning method of automobile demand prediction, comprising the following steps:
(1), it from the data extracted in the data obtained and opened with all client applications of once interaction are buried, completes
After enter step (2)；
(2), step (1) extract data in, obtain interaction 5 kilometer range of spot in all sites and this time
Corresponding site enters step (3) whether there is or not the data wait hire a car after the completion when interaction occurs；
(3), by open client application process id (sessionid) come obtain this time interaction after whether there is or not place an order
The data of operation enter step (4) after the completion；
(4), the process id of this opening client application is belonged to and is interacted spot apart from nearest site, it is complete
(5) are entered step after；
(5), it obtains and carries out the longest pick-up walking distance that the success of this time user of interaction places an order, enter step after the completion
(6), in which:
Walking distance when longest pick-up walking distance refers to placing an order successfully between user position and pick-up site；
(6), all site information in user's longest pick-up walking distance are obtained, enter step (7) after the completion；
(7) if, step (6) have not less than one in all sites for obtaining wait hire a car, be considered as and need to be hired a car,
It is on the contrary then be considered as without wait hire a car, (8) are entered step after the completion；
(8), this data result interacted is belonged to and interacts spot apart from nearest site, it is complete to clean data
Finish, in which:
This time data result of interaction include this interaction either with or without place an order, either with or without wait hire a car.
Further, the data that client application is opened include neighbouring site and information of vehicles, facility information, Yong Huxin
Whether breath order placement information and clicks each icon information.
Further, step (5) if in the user be new registration user, longest pick-up walking distance is set as 100 meters.
The utility model has the advantages that a kind of data cleaning method for sharing automobile demand prediction disclosed by the invention has with following
Beneficial effect:
1, guarantee the validity of data；
2, dirty data will not be adulterated, forecasting accuracy is improved；
3, the model calculation time is reduced after cleaning data.
Detailed description of the invention
Fig. 1 is disclosed by the invention a kind of for sharing the flow chart of the data cleaning method of automobile demand prediction.
Specific embodiment:
Detailed description of specific embodiments of the present invention below.
As shown in Figure 1, a kind of for sharing the data cleaning method of automobile demand prediction, comprising the following steps:
(1), it from the data extracted in the data obtained and opened with all client applications of once interaction are buried, completes
After enter step (2)；
(2), step (1) extract data in, obtain interaction 5 kilometer range of spot in all sites and this time
Corresponding site enters step (3) whether there is or not the data wait hire a car after the completion when interaction occurs；
(3), by open client application process id (sessionid) come obtain this time interaction after whether there is or not place an order
The data of operation enter step (4) after the completion；
(4), the process id of this opening client application is belonged to and is interacted spot apart from nearest site, it is complete
(5) are entered step after；
(5), it obtains and carries out the longest pick-up walking distance that the success of this time user of interaction places an order, enter step after the completion
(6), in which:
Walking distance when longest pick-up walking distance refers to placing an order successfully between user position and pick-up site；
(6), all site information in user's longest pick-up walking distance are obtained, enter step (7) after the completion；
(7), determine whether wait hire a car, (8) are entered step after the completion
If had in all sites that step (6) obtains not less than one wait hire a car, it is considered as and needs to be hired a car, it is on the contrary
Then it is considered as without wait hire a car；
(8), this data result interacted is belonged to and interacts spot apart from nearest site, it is complete to clean data
Finish, in which:
This time data result of interaction include this interaction either with or without place an order, either with or without wait hire a car.
Further, the data that client application is opened include neighbouring site and information of vehicles, facility information, Yong Huxin
Whether breath order placement information and clicks each icon information.
Further, step (5) if in the user be new registration user, longest pick-up walking distance is set as 100 meters.
Embodiments of the present invention are elaborated above.But present invention is not limited to the embodiments described above,
Technical field those of ordinary skill within the scope of knowledge, can also do without departing from the purpose of the present invention
Various change out.
Claims (3)
1. a kind of for sharing the data cleaning method of automobile demand prediction, which comprises the following steps:
(1), it from the data extracted in the data obtained and opened with all client applications of once interaction are buried, completes laggard
Enter step (2)；
(2), in the data that step (1) is extracted, all sites in interaction 5 kilometer range of spot and this time interaction are obtained
Corresponding site enters step (3) whether there is or not the data wait hire a car after the completion when generation；
(3), it is obtained after this time interaction whether there is or not the data for carrying out lower single operation, is completed by opening the process id of client application
After enter step (4)；
(4), the process id of this opening client application is belonged to and is interacted spot apart from nearest site, after the completion
Enter step (5)；
(5), it obtains and carries out the longest pick-up walking distance that the success of this time user of interaction places an order, enter step (6) after the completion,
Wherein:
Walking distance when longest pick-up walking distance refers to placing an order successfully between user position and pick-up site；
(6), all site information in user's longest pick-up walking distance are obtained, enter step (7) after the completion；
(7) if, step (6) have not less than one in all sites for obtaining wait hire a car, be considered as and need to be hired a car, it is on the contrary
Then it is considered as without wait hire a car, enters step (8) after the completion；
(8), this data result interacted is belonged to and interacts spot apart from nearest site, cleaned data and finish,
In:
This time data result of interaction include this interaction either with or without place an order, either with or without wait hire a car.
2. as described in claim 1 a kind of for sharing the data cleaning method of automobile demand prediction, which is characterized in that client
The data that end application is opened include neighbouring site and information of vehicles, facility information, user information, whether order placement information and click
Each icon information.
3. as described in claim 1 a kind of for sharing the data cleaning method of automobile demand prediction, which is characterized in that step
(5) if in the user be new registration user, longest pick-up walking distance is set as 100 meters.
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| CN201910340014.0A CN110069482A (en) | 2019-04-25 | 2019-04-25 | A kind of data cleaning method predicted for sharing automobile demand |
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| CN201910340014.0A CN110069482A (en) | 2019-04-25 | 2019-04-25 | A kind of data cleaning method predicted for sharing automobile demand |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160078367A1 (en) * | 2014-10-15 | 2016-03-17 | Brighterion, Inc. | Data clean-up method for improving predictive model training |
| CN107196788A (en) * | 2017-05-02 | 2017-09-22 | 阿里巴巴集团控股有限公司 | A kind of processing method for burying point data, device, server and client |
| CN107871366A (en) * | 2017-11-10 | 2018-04-03 | 广州市睿仕信息科技有限公司 | One kind takes return the car easily automobile timesharing leasing system and its rent method |
| CN109582664A (en) * | 2018-11-23 | 2019-04-05 | 温州职业技术学院 | A kind of shared bicycle trip characteristics analysis method |
-
2019
- 2019-04-25 CN CN201910340014.0A patent/CN110069482A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20160078367A1 (en) * | 2014-10-15 | 2016-03-17 | Brighterion, Inc. | Data clean-up method for improving predictive model training |
| CN107196788A (en) * | 2017-05-02 | 2017-09-22 | 阿里巴巴集团控股有限公司 | A kind of processing method for burying point data, device, server and client |
| CN107871366A (en) * | 2017-11-10 | 2018-04-03 | 广州市睿仕信息科技有限公司 | One kind takes return the car easily automobile timesharing leasing system and its rent method |
| CN109582664A (en) * | 2018-11-23 | 2019-04-05 | 温州职业技术学院 | A kind of shared bicycle trip characteristics analysis method |
Non-Patent Citations (1)
| Title |
|---|
| 北京首汽智行科技有限公司: "GOFUN出行", 《GOFUN出行》 * |
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