CN110059839A - A kind of method that need-based extracts unmet demand - Google Patents
A kind of method that need-based extracts unmet demand Download PDFInfo
- Publication number
- CN110059839A CN110059839A CN201910340031.4A CN201910340031A CN110059839A CN 110059839 A CN110059839 A CN 110059839A CN 201910340031 A CN201910340031 A CN 201910340031A CN 110059839 A CN110059839 A CN 110059839A
- Authority
- CN
- China
- Prior art keywords
- site
- hour
- car
- historical data
- demand
- 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.)
- Pending
Links
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
- G06Q10/00—Administration; Management
- G06Q10/02—Reservations, e.g. for tickets, services or events
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- 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
- G06Q30/0645—Rental transactions; Leasing transactions
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F17/00—Coin-freed apparatus for hiring articles; Coin-freed facilities or services
- G07F17/0042—Coin-freed apparatus for hiring articles; Coin-freed facilities or services for hiring of objects
- G07F17/0057—Coin-freed apparatus for hiring articles; Coin-freed facilities or services for hiring of objects for the hiring or rent of vehicles, e.g. cars, bicycles or wheelchairs
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04L67/125—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks involving control of end-device applications over a network
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/52—Network services specially adapted for the location of the user terminal
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Strategic Management (AREA)
- General Physics & Mathematics (AREA)
- Economics (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Accounting & Taxation (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Quality & Reliability (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Operations Research (AREA)
- Finance (AREA)
- Educational Administration (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention relates to a kind of methods that need-based extracts unmet demand, include: step (1): the App for obtaining each client application buries a historical data, and show that each hour history starts number of users in 1500 meters around each site according to it；Step (2): it obtains user and returns the car quantity using hour as each site history of dimension；Step (3): current each site vehicle number M to be rented is obtained；Step (4): each hour total demand S in each site is predicted；Step (5): it is returned the car quantity N according to obtained user by each site history of the dimension each site of quantitative forecast each hour of returning the car of hour；Step (6): current each site unmet demand number Y is calculated according to Y=M+N-S.The stock idle rate that the present invention reduces the shared automobile of site most saves the promotion site order volume of words under the premise of meeting the market demand, and promotes enterprise income.
Description
Technical field
The invention belongs to share automotive field, and in particular to a kind of method that need-based extracts unmet demand.
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 ".
With the development of computer, electron key and global position system, " Car sharing " of today not only possesses technology
It ensures, and increases many new intensions.
Car sharing refers to that many people share a vehicle, i.e. the driver only has the right to use to vehicle, without ownership,
It is somewhat similarly to hire a car in the short time in row of hiring a car.Its simple procedure is made a phone call or by online or cell phone application
Vehicle is ordered in reservation.Car sharing coordinates vehicle generally by some company, and the problems such as be responsible for the insurance of vehicle and park.This
Kind mode can not only save money, but also help to alleviate the abrasion of traffic jam and highway, reduce air pollution, reduction pair
The dependence of energy, development prospect are extremely wide.
But the operator of current shared automobile is mostly the tune that shared vehicle is carried out according to the total demand of site
Degree, but this operation has the following disadvantages:
1, it will cause stock idle；
2, due to the limitation of human resources, it will cause demand waste.
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
The method that need-based extracts unmet demand solves existing to be scheduled vehicle by total demand vehicle is caused to transport
It leaves unused for a long time in battalion problem, by obtaining current destination vehicle number to be rented, predicting that user returns the car the more accurate output of quantity
Vehicle needed for site promotes site and dispatches buses accuracy.
A kind of technical solution: method that need-based extracts unmet demand, comprising the following steps:
Step (1): the App for obtaining each client application buries a historical data, and buries a history number according to the App of acquisition
According to history starting number of users (automobile-used amount can be used) for obtaining around each site each hour in 1500 meters, enter after the completion
Step (2), in which:
It includes lower single historical data that App, which buries a historical data, and lower list historical data is counted by dimension of hour；
Step (2): user is obtained according to lower single historical data that step (1) obtains and is gone through by each site of dimension of hour
History is returned the car quantity, enters step (3) after the completion；
Step (3): current each site vehicle number M to be rented is obtained, enters step (4) after the completion；
Step (4): each hour history starts user in 1500 meters around each site obtained according to step (1)
Several, lower single historical data calculating predicts each hour total demand S in each site, enters step (5) after the completion；
Step (5): the user obtained according to step (2) is every as each site history of dimension quantitative forecast of returning the car using hour
A site each hour returns the car quantity N, enters step (6) after the completion
Step (6): current each site unmet demand number Y is calculated according to Y=M+N-S, in which:
N is quantity of returning the car each site each hour；
M is that current each site waits hiring a car；
S is each hour total demand in each site.
Further, it is using hour as dimension that the App of each client application obtained in step (1), which buries a historical data,
It is counted.
Further, step (4) the following steps are included:
(41) the lower single historical data obtained according to step (1), extracts the accumulation amount of placing an order that each site is gone over 30 days,
Subsequently into step (2)；
(42) it is extracted around the site in the accumulation amount of placing an order that each site that step (41) obtains goes over 30 days
The accumulation amount of placing an order to place an order in 1500 meters is obtained as each hour need in each site after rounding then by it divided by 30
Seek total amount S.
Further, step (5) the following steps are included:
(51) user obtained according to step (2) obtains each net by each site history of dimension quantity of returning the car of hour
Point accumulation in the past 30 days is returned the car number；
(52) accumulation that each site that step (51) obtains is gone over 30 days is returned the car into number divided by 30, is conduct after rounding
Each site each hour returns the car quantity N.
The utility model has the advantages that the method that a kind of need-based disclosed by the invention extracts unmet demand has below beneficial to effect
Fruit:
The stock idle rate for reducing the shared automobile of site most saves the promotion of words under the premise of meeting the market demand
Site order volume, and promote enterprise income.
Detailed description of the invention
Fig. 1 is the flow chart for the method that a kind of need-based disclosed by the invention extracts unmet demand.
Specific embodiment:
Detailed description of specific embodiments of the present invention below.
As shown in Figure 1, a kind of method that need-based extracts unmet demand, comprising the following steps:
Step (1): the App for obtaining each client application buries a historical data, and buries a history number according to the App of acquisition
According to history starting number of users (automobile-used amount can be used) for obtaining around each site each hour in 1500 meters, enter after the completion
Step (2), in which:
It includes lower single historical data that App, which buries a historical data, and lower list historical data is counted by dimension of hour；
Step (2): user is obtained according to lower single historical data that step (1) obtains and is gone through by each site of dimension of hour
History is returned the car quantity, enters step (3) after the completion；
Step (3): current each site vehicle number M to be rented is obtained, enters step (4) after the completion；
Step (4): each hour history starts user in 1500 meters around each site obtained according to step (1)
Several, lower single historical data calculating predicts each hour total demand S in each site, enters step (5) after the completion；
Step (5): the user obtained according to step (2) is every as each site history of dimension quantitative forecast of returning the car using hour
A site each hour returns the car quantity N, enters step (6) after the completion
Step (6): current each site unmet demand number Y is calculated according to Y=M+N-S, in which:
N is quantity of returning the car each site each hour；
M is that current each site waits hiring a car；
S is each hour total demand in each site.
Further, it is using hour as dimension that the App of each client application obtained in step (1), which buries a historical data,
It is counted.
Further, step (4) the following steps are included:
(41) the lower single historical data obtained according to step (1), extracts the accumulation amount of placing an order that each site is gone over 30 days,
Subsequently into step (2)；
(42) it is extracted around the site in the accumulation amount of placing an order that each site that step (41) obtains goes over 30 days
The accumulation amount of placing an order to place an order in 1500 meters is obtained as each hour need in each site after rounding then by it divided by 30
Seek total amount S.
Further, step (5) the following steps are included:
(51) user obtained according to step (2) obtains each net by each site history of dimension quantity of returning the car of hour
Point accumulation in the past 30 days is returned the car number；
(52) accumulation that each site that step (51) obtains is gone over 30 days is returned the car into number divided by 30, is conduct after rounding
Each site each hour returns the car quantity N.
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 (4)
1. a kind of method that need-based extracts unmet demand, which comprises the following steps:
Step (1): the App for obtaining each client application buries a historical data, and buries a historical data according to the App of acquisition and obtain
Each hour history starts number of users in 1500 meters around each site out, enters step (2) after the completion, in which:
It includes lower single historical data that App, which buries a historical data, and lower list historical data is counted by dimension of hour；
Step (2): according to lower single historical data that step (1) obtains obtain user using hour as each site history of dimension also
Vehicle quantity enters step (3) after the completion；
Step (3): current each site vehicle number M to be rented is obtained, enters step (4) after the completion；
Step (4): around each site obtained according to step (1) in 1500 meters each hour history starting number of users, under
Single historical data calculating predicts each hour total demand S in each site, enters step (5) after the completion；
Step (5): the user obtained according to step (2) returns the car each net of quantitative forecast using hour as each site history of dimension
Point each hour returns the car quantity N, enters step (6) after the completion
Step (6): current each site unmet demand number Y is calculated according to Y=M+N-S, in which:
N is quantity of returning the car each site each hour；
M is that current each site waits hiring a car；
S is each hour total demand in each site.
2. the method that a kind of need-based as described in claim 1 extracts unmet demand, which is characterized in that step (1)
The App of each client application of middle acquisition, which buries a historical data, to be counted by dimension of hour.
3. the method that a kind of need-based as described in claim 1 extracts unmet demand, which is characterized in that step (4)
The following steps are included:
(41) the lower single historical data obtained according to step (1), extracts the accumulation amount of placing an order that each site is gone over 30 days, then
Enter step (2)；
(42) it is extracted 1500 around the site in the accumulation amount of placing an order that each site that step (41) obtains goes over 30 days
The accumulation amount of placing an order to place an order in rice obtains total as each hour demand in each site then by it divided by 30, after rounding
Measure S.
4. the method that a kind of need-based as described in claim 1 extracts unmet demand, which is characterized in that step (5)
The following steps are included:
(51) user obtained according to step (2) obtains each site mistake by each site history of dimension quantity of returning the car of hour
The accumulation gone 30 days is returned the car number；
(52) accumulation that each site that step (51) obtains is gone over 30 days is returned the car into number divided by 30, i.e. as each after rounding
Site each hour returns the car quantity N.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910340031.4A CN110059839A (en) | 2019-04-25 | 2019-04-25 | A kind of method that need-based extracts unmet demand |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910340031.4A CN110059839A (en) | 2019-04-25 | 2019-04-25 | A kind of method that need-based extracts unmet demand |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110059839A true CN110059839A (en) | 2019-07-26 |
Family
ID=67320953
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910340031.4A Pending CN110059839A (en) | 2019-04-25 | 2019-04-25 | A kind of method that need-based extracts unmet demand |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110059839A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112613752A (en) * | 2020-12-25 | 2021-04-06 | 环球车享汽车租赁有限公司 | Method, electronic device, and storage medium for vehicle scheduling |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105719019A (en) * | 2016-01-21 | 2016-06-29 | 华南理工大学 | Public bicycle peak time demand prediction method considering user reservation data |
| CN106503869A (en) * | 2016-11-14 | 2017-03-15 | 东南大学 | A kind of public bicycles dynamic dispatching method that is predicted based on website short-term needs |
| CN108346010A (en) * | 2018-04-23 | 2018-07-31 | 徐漫洋 | Shared Truck dispartching method based on user requirements analysis |
-
2019
- 2019-04-25 CN CN201910340031.4A patent/CN110059839A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105719019A (en) * | 2016-01-21 | 2016-06-29 | 华南理工大学 | Public bicycle peak time demand prediction method considering user reservation data |
| CN106503869A (en) * | 2016-11-14 | 2017-03-15 | 东南大学 | A kind of public bicycles dynamic dispatching method that is predicted based on website short-term needs |
| CN108346010A (en) * | 2018-04-23 | 2018-07-31 | 徐漫洋 | Shared Truck dispartching method based on user requirements analysis |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112613752A (en) * | 2020-12-25 | 2021-04-06 | 环球车享汽车租赁有限公司 | Method, electronic device, and storage medium for vehicle scheduling |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Guo et al. | Parking spaces repurchase strategy design via simulation optimization | |
| WO2019237522A1 (en) | Vehicle leasing method and apparatus, and computer device and storage medium | |
| CN106503869A (en) | A kind of public bicycles dynamic dispatching method that is predicted based on website short-term needs | |
| US20150339595A1 (en) | Method and system for balancing rental fleet of movable asset | |
| CN103729353A (en) | Method for searching for ticket business information and servers | |
| CN103632532A (en) | Taxi taxi-taking inducing method | |
| CN105117790A (en) | Fare estimating method and apparatus | |
| CN105512741A (en) | Bus passenger traffic combined prediction method | |
| CN113256022B (en) | Method and system for predicting electric load of transformer area | |
| CN102333274A (en) | Cell phone signal data based-method for processing commuting information and apparatus thereof | |
| CN110956296A (en) | User loss probability prediction method and device | |
| CN110070718A (en) | Expressway Service service quality dynamic assessment method, system and equipment | |
| CN109934634A (en) | Map grid arrangement method, device, system, computer equipment and storage medium | |
| Gehrke et al. | Patterns and predictors of dockless bikeshare trip generation and duration in Boston’s suburbs | |
| Hall et al. | Pricing in designed markets: The case of ride-sharing | |
| CN110147919A (en) | A kind of public bicycles automatic scheduling method based on price competition mechanism | |
| CN111291321A (en) | Urban traffic model construction method based on big data | |
| CN113935505A (en) | Shared electric vehicle operation optimization method based on column generation and ant colony algorithm fusion | |
| CN117217380A (en) | Parking lot vacant parking space prediction method and device, electronic equipment and storage medium | |
| CN110059839A (en) | A kind of method that need-based extracts unmet demand | |
| CN112652164B (en) | Traffic time interval dividing method, device and equipment | |
| Kho et al. | A development of punctuality index for bus operation | |
| Tengilimoglu et al. | Evaluating the mileage and time efficiency of ridesourcing services: Austin, Texas case | |
| CN110175718A (en) | A kind of berth allocation method and terminal device | |
| CN108596381B (en) | Urban parking demand prediction method based on OD data |
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 | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20190726 |
|
| RJ01 | Rejection of invention patent application after publication |