CN107292798A - A kind of shared bicycle parks determination method and device a little - Google Patents
A kind of shared bicycle parks determination method and device a little Download PDFInfo
- Publication number
- CN107292798A CN107292798A CN201710517669.1A CN201710517669A CN107292798A CN 107292798 A CN107292798 A CN 107292798A CN 201710517669 A CN201710517669 A CN 201710517669A CN 107292798 A CN107292798 A CN 107292798A
- Authority
- CN
- China
- Prior art keywords
- subregion
- classification
- shared bicycle
- determined
- little
- 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
- 238000000034 method Methods 0.000 title claims abstract description 96
- 230000008569 process Effects 0.000 claims description 39
- 230000006870 function Effects 0.000 claims description 21
- 230000011218 segmentation Effects 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 14
- 239000012141 concentrate Substances 0.000 claims description 2
- 230000008901 benefit Effects 0.000 description 3
- 229910052799 carbon Inorganic materials 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000003379 elimination reaction Methods 0.000 description 2
- 230000009469 supplementation Effects 0.000 description 2
- OKTJSMMVPCPJKN-UHFFFAOYSA-N Carbon Chemical compound [C] OKTJSMMVPCPJKN-UHFFFAOYSA-N 0.000 description 1
- 238000003915 air pollution Methods 0.000 description 1
- 230000000903 blocking effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 230000008030 elimination Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 230000009467 reduction Effects 0.000 description 1
- 230000017105 transposition Effects 0.000 description 1
- 239000002699 waste material Substances 0.000 description 1
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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- 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
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Tourism & Hospitality (AREA)
- Human Resources & Organizations (AREA)
- Theoretical Computer Science (AREA)
- Physics & Mathematics (AREA)
- Marketing (AREA)
- Development Economics (AREA)
- General Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Entrepreneurship & Innovation (AREA)
- Operations Research (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Traffic Control Systems (AREA)
Abstract
Determination method and device a little is parked the invention provides a kind of shared bicycle, this method includes:According to the functional area information with demand of parking corresponding with current slot, the subregion with the function is determined from predeterminable area;The subregion classification determined using default sorting algorithm pair;The center for obtained each classification of classifying is defined as into shared bicycle to park a little.In the present invention during it is determined that shared bicycle is parked a little, time factor is associated with the subregion with the demand of parking, and the corresponding multiple subregions with demand of parking of current slot are classified, parked the center of each classification as shared bicycle a little, shared bicycle administrative staff so can be effectively instructed to be scheduled shared bicycle, so as to meet demand of user of the current slot in predeterminable area to shared bicycle, some region is reduced as far as possible and the shared bicycle situation that supply falls short of demand occurs, lifts user experience.
Description
Technical field
The present invention relates to technical field of computer information processing, parked a little really in particular to a kind of shared bicycle
Determine method and device.
Background technology
At present, domestic cityization and mechanization process are gradually accelerated, thus the problems such as caused urban traffic blocking, pollution
It is increasingly serious, and the trend of air pollution will be inevitable within the long duration.So developing public transport and being considered as
The only way which must be passed of urban transport problems is solved, bicycle is shared as public transport important component, especially, shares bicycle conduct
The vehicles have become new generation of city and ridden instead of walk emperorship, and shared bicycle is the optimal vehicles of short distance trip, are alleviating
There is very important effect in terms of urban congestion, reduction motor vehicle carbon emission problem, in the recent period, Beijing, Shanghai, Guangzhou etc. are big
The development of shared bicycle is all carried forward vigorously in city, have the advantages that with take with, there is car to ride whenever and wherever possible, Green Travel, give people
Bringing great convenience property of daily life, meanwhile, open healthy low-carbon new life, can provide the user easily to go out
Row service, so as to increasingly obtain the favor of user.
However, effective performance of shared bicycle will depend on rational allocation plan, the scale design of science, it is flexible to adjust
In terms of degree operation and suitable Cost-Sharing, one of key point serviced as shared bicycle system optimization parks choosing a little
Location planning is target to the maximum with service coverage, then to obtain optimal shared bicycle and park a number and position.Currently,
In shared bicycle scheduling process, mainly determine that shared bicycle is parked a little by standard empirical by dispatcher, will be shared
Bicycle is parked in flow of the people than larger region, such as bus station, subway station.
From above statement, at present in it is determined that shared bicycle parks point process, artificial experience and city are relied primarily on
The auxiliary facility of planning builds angle and goes to plan that shared car is parked a little, and there is the shared bicycle determined, to park a degree of accuracy low
Problem, causes a certain district-share bicycle often occur that supply falls short of demand or easy situation, causes shared bicycle resource
Waste, it is impossible to play its maximum value, reduce user experience.
The content of the invention
In view of this, the purpose of the embodiment of the present invention is that a kind of shared bicycle of offer parks determination method and dress a little
Put, park a problem of degree of accuracy is low to solve to exist the shared bicycle determined, cause a certain district-share list often occur
Supply falls short of demand or easy situation for car, causes the shared bicycle wasting of resources, it is impossible to play its maximum value, reduce
The problem of user experience.
In a first aspect, parking determination method a little the embodiments of the invention provide a kind of shared bicycle, this method includes:
According to the functional area information with demand of parking corresponding with current slot, determine have from predeterminable area
The subregion of the function;
The subregion classification determined using default sorting algorithm pair;
The center for obtained each classification of classifying is defined as into shared bicycle to park a little, each classification is included
At least one subregion.
With reference in a first aspect, the embodiments of the invention provide the possible embodiment of the first of first aspect, wherein, institute
Default sorting algorithm is stated for K-means algorithms;
Before being classified using default sorting algorithm to the subregion, in addition to:
According to the position relationship between each subregion, it is determined that the number for the classification that classification is obtained.
With reference to the first possible embodiment of first aspect, the embodiments of the invention provide second of first aspect
Possible embodiment, wherein, the position relationship according between each subregion, it is determined that for the classification that classification is obtained
Number, is specifically included:
For every sub-regions, according to the position relationship between the subregion and other subregions, the subregion institute is determined
The subregion is defined as isolated area by the subregion collection of category;
The number of the subregion collection of division is defined as classifying the number of obtained classification;
Wherein, the subregion collection meets following first preparatory condition:
For every sub-regions collection, any subregion that the subregion collection is included is concentrated in the subregion has another sub-district
The distance between domain and any subregion are within pre-determined distance threshold value;And son is not present in the subregion outside the subregion collection
The distance between region and any subregion are within pre-determined distance threshold value;
The isolated area meets following second preparatory condition:
For each subregion as isolated area, in the absence of the distance between any subregion and the subregion pre-
If within distance threshold.
With reference to second of possible embodiment of first aspect, the embodiments of the invention provide the third of first aspect
Possible embodiment, wherein, before the number for the obtained classification that is defined as the number of the subregion collection of division classifying, also
Including:
The every sub-regions obtained from division are concentrated, and determine that area is more than or equal to the subregion collection of preset area;
According to default segmentation rule, the subregion collection determined is divided into segmentation subregion collection;
The number of the subregion collection by division is defined as classifying the number of obtained classification, specifically includes:
The quantity sum of segmentation subregion collection by the quantity of not segmented subregion collection with being obtained through over-segmentation is determined
For the number for obtained classification of classifying.
With reference to second of the possible embodiment or the third possible embodiment, the embodiment of the present invention of first aspect
There is provided the 4th kind of possible embodiment of first aspect, wherein, the subregion point determined using K-means algorithms pair
Class, is specifically included:
For the subregion in the subregion in addition to isolated area, the center for randomly selecting K sub-regions is sat
The cluster centre initial value respectively as K classification is marked, wherein, the number for the classification that K obtains for classification;
Perform following sorting procedure:
For every sub-regions in remaining all subregion in all subregion in addition to this K cluster centre, it is determined that
The subregion center is respectively the distance between with this K cluster centre;
Cluster centre generic nearest with the subregion center position in this K cluster centre is defined as
The subregion generic;
For obtained each classification, it is determined that the average value of all subregion center position coordinates of the affiliated category, and will
The center position coordinates of the affiliated subregion of the corresponding coordinate position of the average value are defined as in the cluster that next cluster process is used
The heart;And
Judge whether the cluster centre that the cluster centre that the next cluster process is used is used with this cluster process meets
Preparatory condition, if it is not satisfied, the cluster centre for then using next cluster process is as this new K cluster centre, again
Perform the sorting procedure;If meeting, the classification results that this cluster process is obtained are defined as final classification result.
With reference in a first aspect, the embodiments of the invention provide the possible embodiment of the 5th of first aspect kind, wherein, institute
Default sorting algorithm is stated for K-means algorithms;
According to the functional area information with demand of parking corresponding with current slot, determine have from predeterminable area
The subregion of the function, is specifically included:
The predeterminable area is divided into by many sub-regions based on default unit area, it is institute to make the area of every sub-regions
State default unit area;
It is true from the multiple subregion according to the functional area information with demand of parking corresponding with current slot
Surely there is the subregion of the function;
Before the subregion classification determined using default sorting algorithm pair, in addition to:
Subregion number with the function in the multiple subregion is defined as classifying the number of obtained classification.
With reference to the 4th kind of possible embodiment of first aspect, the embodiments of the invention provide the 6th of first aspect kind
Possible embodiment, wherein, methods described also includes:
Parked a little for each shared bicycle, the GPS information that a shared bicycle set is provided is parked according to this, it is common to this
Bicycle is enjoyed to be monitored;
Determine that this parks shared bicycle user a little and the supply-demand relationship of shared bicycle according to monitored results;
According to the supply-demand relationship adjust this park a little set by share bicycle quantity.
Second aspect, the embodiment of the present invention additionally provides a kind of shared bicycle and parks determining device a little, and the device includes:
Subregion determining module, for the basis functional area information with demand of parking corresponding with current slot,
The subregion with the function is determined from predeterminable area;
Subregion sort module, for the subregion classification determined using default sorting algorithm pair;
Bicycle parks a determining module, stops for the center for obtained each classification of classifying to be defined as into shared bicycle
Put a little, each classification includes at least one subregion.
The third aspect, the embodiment of the present invention additionally provides a kind of computer equipment, including memory, processor and is stored in
On the memory and the computer program that can run on the processor, described in the computing device during computer program
The step of realizing the method any one of above-mentioned first aspect to the 6th kind of possible embodiment of first aspect.
Fourth aspect, the embodiment of the present invention additionally provides a kind of computer-readable recording medium, described computer-readable to deposit
Be stored with computer program on storage media, and the computer program performs above-mentioned first aspect to first party when being run by processor
The step of method any one of the 6th kind of possible embodiment in face.
In the determination method and device that shared bicycle provided in an embodiment of the present invention parks a little, this method includes:According to
The functional area information with demand of parking corresponding with current slot, determines the sub-district with the function from predeterminable area
Domain;The subregion classification determined using default sorting algorithm pair;The center for obtained each classification of classifying is defined as altogether
Bicycle is enjoyed to park a little.In the present invention during it is determined that shared bicycle is parked a little, by time factor and with the demand of parking
Subregion is associated, and the corresponding multiple subregions with demand of parking of current slot are classified, by each class
Other center is parked a little as shared bicycle, so can effectively instruct shared bicycle administrative staff to enter shared bicycle
Row scheduling, so as to meet demand of user of the current slot in predeterminable area to shared bicycle, reduces some area as far as possible
There is the shared bicycle situation that supply falls short of demand in domain, lifts user experience.
To enable the above objects, features and advantages of the present invention to become apparent, preferred embodiment cited below particularly, and coordinate
Appended accompanying drawing, is described in detail below.
Brief description of the drawings
In order to illustrate the technical solution of the embodiments of the present invention more clearly, below will be attached to what is used required in embodiment
Figure is briefly described, it will be appreciated that the following drawings illustrate only certain embodiments of the present invention, therefore is not construed as pair
The restriction of scope, for those of ordinary skill in the art, on the premise of not paying creative work, can also be according to this
A little accompanying drawings obtain other related accompanying drawings.
Fig. 1 shows that the shared bicycle that one embodiment of the invention is provided parks the schematic flow sheet of determination method a little;
Fig. 2 shows that the shared bicycle that another embodiment of the present invention is provided parks the signal of one of determination method a little flow
Figure;
Fig. 3 shows that the shared bicycle that another embodiment of the present invention is provided parks the two flows signal of determination method a little
Figure;
Fig. 4 shows that the shared bicycle that another embodiment of the present invention is provided parks the three flows signal of determination method a little
Figure;
Fig. 5 shows that the shared bicycle that another embodiment of the present invention is provided parks the four flows signal of determination method a little
Figure;
Fig. 6 shows that the shared bicycle that another embodiment of the present invention is provided parks realization principle schematic diagram a little;
Fig. 7 shows that the shared bicycle that another embodiment of the present invention is provided parks the five flows signal of determination method a little
Figure;
Fig. 8 shows that the shared bicycle that further embodiment of this invention is provided parks the flow signal of determination method a little
Figure;
Fig. 9 shows that a kind of shared bicycle that the embodiment of the present invention is provided parks the structural representation of determining device a little
Figure;
Figure 10 shows a kind of structural representation for computer equipment that the embodiment of the present invention is provided.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
Middle accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is only
It is a part of embodiment of the invention, rather than whole embodiments.The present invention being generally described and illustrated herein in the accompanying drawings is real
Applying the component of example can be arranged and be designed with a variety of configurations.Therefore, it is of the invention to what is provided in the accompanying drawings below
The detailed description of embodiment is not intended to limit the scope of claimed invention, but is merely representative of the selected reality of the present invention
Apply example.Based on embodiments of the invention, the institute that those skilled in the art are obtained on the premise of creative work is not made
There is other embodiment, belong to the scope of protection of the invention.
In view of in it is determined that shared bicycle parks point process, relying primarily on the supporting of artificial experience and urban planning at present
Facilities Construction angle goes to plan that shared car is parked a little, there is the shared bicycle determined and parks a problem of degree of accuracy is low, causes
A certain district-share bicycle often occur, supply falls short of demand or easy situation, causes the shared bicycle wasting of resources, it is impossible to
Its maximum value is played, user experience is reduced.Based on this, parked a little the embodiments of the invention provide a kind of shared bicycle
Determination method and device, be described below by embodiment.
One embodiment of the invention parks determination method a little there is provided a kind of shared bicycle, as shown in figure 1, this method includes
Following steps:
S101, basis the functional area information with demand of parking corresponding with current slot, from predeterminable area really
Surely there is the subregion of above-mentioned functions.
In this step, functional area can be the region with difference in functionality in urban planning, for example:Residential block, business
Circle etc..Predeterminable area can be that shared bicycle to be determined parks region a little, such as Chaoyang District, Haidian District, current slot
Period a little is parked for shared bicycle to be determined, is distributed, is determined from predeterminable area with working as based on such as table 1 below and functional area
The corresponding subregion with demand of parking of preceding period, for example, predeterminable area is Chaoyang District, current slot is working day 7:
00-10:00, now, that determines has the residential quarters and multiple Chaoyang that the subregion for demand of parking is multiple Chaoyang Districts
The subway in area.
S102, the subregion determined using default sorting algorithm pair are classified.
In this step, the subregion with demand of parking determined using default sorting algorithm to step S101 is carried out
Classification, can be classified as a class by the subregion that distance between subregion is less than predetermined threshold value or there will be the sub-district of specific demand
Domain is divided into a class.
S103, the center for each classification for obtaining classification are defined as shared bicycle and parked a little, and each classification is wrapped
Containing at least one subregion.
In this step, for step S102 divide multiple classifications, it is contemplated that most bicyclists away from the distance parked a little,
Shared bicycle is docked to the center position of each classification, is so easy to shared bicycle to concentrate and parks, and be easy to bicyclist fast
Speed correctly finds required shared bicycle.
Wherein, have in step S101, between current slot and functional area information with the demand of parking certain
Corresponding relation, as shown in table 1, the corresponding relation is specially:
Table 1
Current slot | Functional area information | |
1 | Working day 7:00-10:00 | Residential building, subway |
2 | Working day 11:30-12:30 | Office building, place of having dinner |
3 | Working day 17:00-20:00 | Office building, subway |
4 | Nonworkdays 9:00-12:00 | Residential building, subway |
5 | Nonworkdays 13:00-21:00 | Recreational places, subway |
… | … | … |
It should be noted that in the specific implementation, not to the current slot in table 1 and the function with the demand of parking
Corresponding relation is defined between area information, can be set according to the actual requirements, main to realize time factor and tool
The subregion for having the demand of parking is associated.
In the embodiment that provides of the present invention, during it is determined that shared bicycle is parked a little, by time factor and have
The subregion for parking demand is associated, and the corresponding multiple subregions with demand of parking of current slot are divided
Class, is parked the center of each classification as shared bicycle a little, so can effectively instruct shared bicycle administrative staff
Shared bicycle is scheduled, so as to meet demand of user of the current slot in predeterminable area to shared bicycle, to the greatest extent
Amount reduces some region and the shared bicycle situation that supply falls short of demand occurs, lifts user experience.
A kind of shared bicycle of another embodiment of the present invention offer parks determination method a little, and determination method a little is parked at this
In, above-mentioned default sorting algorithm is K-means algorithms, it is contemplated that the process classified using K-means algorithms to subregion
In, it is necessary to the number for the classification that classification needed for providing is obtained, as shown in Fig. 2 this method comprises the following steps:
S201, basis the functional area information with demand of parking corresponding with current slot, from predeterminable area really
Surely there is the subregion of above-mentioned functions.
S202, according to the position relationship between each above-mentioned subregion, it is determined that the number for the classification that classification is obtained.
S203, the subregion determined using K-means algorithms pair are classified.
S204, the center for each classification for obtaining classification are defined as shared bicycle and parked a little, and each classification is wrapped
Containing at least one subregion.
As shown in figure 3, above-mentioned steps S202 can be specifically embodied as S2021~step S2022:
S2021, for every sub-regions, according to the position relationship between the subregion and other subregions, determine the son
The subregion is defined as isolated area by subregion collection belonging to region.
In this step, based on the position relationship between subregion two-by-two, by each sub-zone dividing to a certain subregion collection
In, or it is defined as isolated area, it is all higher than pre-determined distance threshold value for the distance between any subregion and other subregions
Situation, isolated area is defined as by the subregion.
S2022, the obtained classification that by the number of the subregion collection of division is defined as classifying number.
In this step, the division result based on S2021 determines the number for the classification that classification is obtained.
Wherein, above-mentioned subregion collection meets following first preparatory condition:
For every sub-regions collection, any subregion that the subregion collection is included is concentrated in the subregion has another sub-district
The distance between domain and any subregion are within pre-determined distance threshold value;And son is not present in the subregion outside the subregion collection
The distance between region and any subregion are within pre-determined distance threshold value.
Above-mentioned isolated area meets following second preparatory condition:
For each subregion as isolated area, in the absence of the distance between any subregion and the subregion pre-
If within distance threshold.
In the specific implementation, above-mentioned steps S2021 can be specifically embodied as:To any of above-mentioned subregion subregion,
Perform following subregion collection division operation:
Step one:Judge to whether there is the first subregion in the subregion adjacent with the subregion, make first subregion
With the distance between the subregion within pre-determined distance threshold value.
Step 2:If in the presence of the first subregion, judging to whether there is unique second subregion in first subregion, making
Second subregion has been included in any subregion collection.
Step 3:If in the presence of the second subregion, the subregion is included in into any subregion collection.
Step 4:If in the absence of the second subregion, judging in first subregion with the presence or absence of at least two the 3rd sons
Region, makes at least two the 3rd subregion be included in different subregion collection respectively.
Step 5:If in the presence of the 3rd subregion, the different subregion collection is merged, and the subregion is included in into the conjunction
And after subregion collection.
Step 6:If in the absence of the 3rd subregion, making the subregion and first subregion constitute subregion collection.
Step 7:If in the absence of the first subregion, the subregion is defined as into isolated area.
Step 8:Judgement is currently not yet included in corresponding subregion collection with the presence or absence of subregion or is defined as isolated region
Domain;If in the presence of to the above-mentioned subregion collection division operation of subregion execution.
Further, it is contemplated that step S2021 divides obtained many sub-regions collection and there may be the excessive situation of area,
It may so cause the number of classification determined less than normal, and then cause the problem of subsequent classification degree of accuracy is low, therefore, in step
S2022 the number of the subregion collection of division is defined as classifying obtained classification number before, as shown in figure 4, above-mentioned determination
Method also comprises the following steps:
S2023, the every sub-regions obtained from division are concentrated, and determine that area is more than or equal to the subregion of preset area
Collection.
S2024, according to it is default segmentation rule, by the subregion collection determined be divided into segmentation subregion collection.
In this step, the subregion collection that the area determined to step S2023 is more than or equal to preset area is carried out carefully
Change segmentation, and the segmentation subregion that segmentation is obtained is also required to meet above-mentioned first preparatory condition.
Corresponding, above-mentioned steps S2022 can be specifically embodied as S20221:
The quantity sum of segmentation subregion collection by the quantity of not segmented subregion collection with being obtained through over-segmentation is determined
For the number for obtained classification of classifying.
The number of the classification obtained based on the classification determined in above-mentioned Fig. 3 or Fig. 4, as shown in figure 5, above-mentioned steps S203
It can be specifically embodied as step S2031~step S2037:
S2031, for the subregion in above-mentioned subregion in addition to isolated area, randomly select the center of K sub-regions
Position coordinates respectively as K classification cluster centre initial value, wherein, the number of classification that K obtains for classification.
In this step, the number K for obtained classification of being classified based on step S202, randomly selects K cluster centre initial
Value.Specifically, assuming that the center position coordinates collection of subregion is combined into Ω={ (x1,y1),(x2,y2),...,(xi,yi),...,
(xn,yn), cluster centre initial value of the center respectively as K classification of K sub-regions is randomly selected from Ω, by K
The set expression of individual classification is into C=(ck, k=1,2 ..., K), each classification ckCorresponding cluster centre μkRepresent, wherein,
(xi,yi) can be longitude and latitude coordinate, plane coordinate system can also be set up to predeterminable area to be converted to longitude and latitude
Coordinate after plane coordinates.
Perform following sorting procedure:
S2032, for each sub-district in remaining all subregion in all subregion in addition to this K cluster centre
Domain, determines the subregion center respectively the distance between with this K cluster centre.
In this step, according to formulaDetermine in all subregion except this K cluster
Every sub-regions center (x in remaining all subregion outside centeri,yi) respectively with (x in this K cluster centrek,
yk) the distance between d.
S2033, by cluster centre generic nearest with the subregion center position in this K cluster centre
It is defined as the subregion generic.
S2034, each classification for obtaining, it is determined that all subregion center position coordinates of the affiliated category are averaged
Value, and the center position coordinates of the affiliated subregion of the corresponding coordinate position of the average value are defined as what next cluster process was used
Cluster centre.
When it is implemented, can determine to belong to the x coordinate average value of all subregion of the categoryAnd y-coordinate average valueBy what is obtainedThe center of affiliated subregion is defined as the cluster centre that next cluster process is used.
In this step, center of the center away from the nearest subregion of the average value can also be defined as next time
The cluster centre that cluster process is used.
S2035, judge that the cluster centre that cluster centre and this cluster process that the next cluster process uses are used is
It is no to meet preparatory condition, wherein, the preparatory condition can be both distances in preset threshold range, i.e., next cluster process makes
Difference between cluster centre is identical with the cluster centre that this cluster process is used or both is less than the threshold value specified.
S2036, if it is not satisfied, the cluster centre for then using next cluster process is as this new K cluster centre,
Above-mentioned sorting procedure is performed again, that is to say, that it is determined that the cluster centre and this cluster process that next cluster process is used
When the cluster centre used is unsatisfactory for preparatory condition, step S2032 to S2035 is continued executing with, untill meeting preparatory condition.
If S2037, satisfaction, the classification results that this cluster process is obtained are defined as final classification result.
In this step, expire in next the cluster process cluster centre used and the cluster centre that this cluster process is used
Sufficient preparatory condition (cluster centre that i.e. next cluster process is used and the cluster centre that this cluster process is used meet both away from
From in preset threshold range) when, now illustrate that the cluster centre that two cluster process are used is overlapped or close, whole cluster
Process terminates.
As shown in fig. 6, the realization principle schematic diagram that shared bicycle parks determination method a little is given, and in figure 6, ☆ tables
Show the subregion with demand of parking, represents predeterminable area, specifically included:
(1) determine that subregion is distributed:According to it is corresponding with current slot have park the functional area information of demand, from
The subregion with above-mentioned functions is determined in predeterminable area.
(2) to sub- region clustering process:Clustering is carried out to many sub-regions in (1) using K-means algorithms, drawn
It is divided into 3 classifications, wherein, before to sub- region clustering, the number for the classification that classification is obtained first is determined, then based on the category
Many sub-regions are clustered into 3 classifications by number.
(3) abnormity point elimination process:By the subregion of discrete distribution in each classification in (2) as abnormity point, and should
Abnormity point elimination.
(4) determination process is parked:The center for obtained each classification of classifying is defined as into shared bicycle to park a little.
Further, can also be using step S205~to step S207 adjustment as shown in fig. 7, after step s 204
Park the quantity of a little set shared bicycle:
S205, park a little for each shared bicycle, the global location that the shared bicycle set is provided is parked according to this
System (GPS, Global Positioning System) information, is monitored to the shared bicycle.
In this step, each GPS information for parking the shared bicycle currently parked a little determined by obtaining, can
To determine respectively to park the shared bicycle quantity a little currently parked.
S206, according to monitored results determine that this parks shared bicycle user a little and the supply-demand relationship of shared bicycle.
In this step, a little corresponding user's quantity is parked based on each, is a little currently stopped according to respectively parking of determining
The shared bicycle quantity put, it may be determined that each supply-demand relationship parked a little, the supply-demand relationship can be sharing of requiring supplementation with
The quantity of bicycle quantity or unnecessary shared bicycle.
S207, according to above-mentioned supply-demand relationship adjust this park a little set by share bicycle quantity.
In this step, each supply-demand relationship parked a little based on above-mentioned determination, and then each park can be determined
The quantity for the shared bicycle that point is required supplementation with needs the quantity of shared bicycle withdrawn.
In a specific embodiment, as shown in table 2, determination is corresponding with current slot from predeterminable area has
The subregion of demand is parked, is specially:
Table 2
In table 2, there be the subregion with demand of parking corresponding with current slot respectively in predeterminable area:A1、A2、
A3、A4、A5、A6、A7、A8、A9、A10。
As shown in table 3,10 sub-regions in table 2 are classified using K-means algorithms, is specially:
Table 3
In table 3,10 sub-regions are divided into two classifications, wherein, first category includes:A1, A2, A3, A7, Equations of The Second Kind
Do not include:A5、A6、A8、A10.
As shown in table 4, the center of each classification in table 3 is defined as into shared bicycle to park a little, is specially:
Table 4
In table 4, the coordinate each parked a little is (abscissa, ordinate).
Further embodiment of this invention parks determination method a little there is provided a kind of shared bicycle, and determination side a little is parked at this
In method, it is K-means algorithms to preset sorting algorithm, as shown in figure 8, this method comprises the following steps:
S801, above-mentioned predeterminable area is divided into by many sub-regions based on default unit area, makes the face of every sub-regions
Product is above-mentioned default unit area.
S802, basis the functional area information with demand of parking corresponding with current slot, from above-mentioned multiple sub-districts
The subregion with above-mentioned functions is determined in domain.
S803, be defined as classifying by the subregion number with above-mentioned functions in above-mentioned many sub-regions obtained classification
Number.
S804, the subregion determined using K-means algorithms pair are classified.
S805, the center for each classification for obtaining classification are defined as shared bicycle and parked a little, and each classification is wrapped
Containing at least one subregion.
Wherein, step S804 can be specifically embodied as S2031~step S2037, repeat no more here.
Based on same inventive concept, the embodiment of the present invention additionally provides a kind of shared bicycle and parks determination transposition a little, by
The principle for solving problem in the device is similar to foregoing determination method, therefore the implementation of the device may refer to preceding method
Implement, repeat part and repeat no more.
A kind of shared bicycle of offer of the embodiment of the present invention parks determining device a little, as shown in figure 9, the device includes:
Subregion determining module 901, for being believed according to the functional area with demand of parking corresponding with current slot
Breath, determines the subregion with above-mentioned functions from predeterminable area;
Subregion sort module 902, for the subregion classification determined using default sorting algorithm pair;
Bicycle parks a determining module 903, shared single for the center for obtained each classification of classifying to be defined as
Car is parked a little, and each above-mentioned classification includes at least one subregion.
Further, for presetting the situation that sorting algorithm is K-means algorithms, above-mentioned determining device also includes:
Classification number determining module 904, for before being classified using default sorting algorithm to the subregion, according to each
Position relationship between above-mentioned subregion, it is determined that the number for the classification that classification is obtained.
Wherein, above-mentioned classification number determining module 904, specifically for:
For every sub-regions, according to the position relationship between the subregion and other subregions, the subregion institute is determined
The subregion is defined as isolated area by the subregion collection of category;
The number of the subregion collection of division is defined as classifying the number of obtained classification;
Wherein, above-mentioned subregion collection meets following first preparatory condition:
For every sub-regions collection, any subregion that the subregion collection is included is concentrated in the subregion has another sub-district
The distance between domain and any subregion are within pre-determined distance threshold value;And son is not present in the subregion outside the subregion collection
The distance between region and any subregion are within pre-determined distance threshold value;
Above-mentioned isolated area meets following second preparatory condition:
For each subregion as isolated area, in the absence of the distance between any subregion and the subregion pre-
If within distance threshold.
Further, above-mentioned determining device also includes:
Subregion collection splits module 905, in the obtained classification of being defined as classifying by the number of the subregion collection of division
Number before, concentrated from obtained every sub-regions are divided, determine subregion collection of the area more than or equal to preset area;Press
According to default segmentation rule, the subregion collection determined is divided into segmentation subregion collection;
It is corresponding, above-mentioned classification number determining module 904, specifically for:
The quantity sum of segmentation subregion collection by the quantity of not segmented subregion collection with being obtained through over-segmentation is determined
For the number for obtained classification of classifying.
Wherein, for presetting the situation that sorting algorithm is K-means algorithms, above-mentioned subregion sort module 902 is specific to use
In:
For the subregion in above-mentioned subregion in addition to isolated area, the center for randomly selecting K sub-regions is sat
The cluster centre initial value respectively as K classification is marked, wherein, the number for the classification that K obtains for classification;
Perform following sorting procedure:
For every sub-regions in remaining all subregion in all subregion in addition to this K cluster centre, it is determined that
The subregion center is respectively the distance between with this K cluster centre;
Cluster centre generic nearest with the subregion center position in this K cluster centre is defined as
The subregion generic;
For obtained each classification, it is determined that the average value of all subregion center position coordinates of the affiliated category, and will
The center position coordinates of the affiliated subregion of the corresponding coordinate position of the average value are defined as in the cluster that next cluster process is used
The heart;And
Judge whether the cluster centre that the cluster centre that the next cluster process is used is used with this cluster process meets
Preparatory condition, if it is not satisfied, the cluster centre for then using next cluster process is as this new K cluster centre, again
Perform above-mentioned sorting procedure;If meeting, the classification results that this cluster process is obtained are defined as final classification result.
Further, for presetting the situation that sorting algorithm is K-means algorithms, above-mentioned subregion determining module 901, tool
Body is used for:
Above-mentioned predeterminable area is divided into by many sub-regions based on default unit area, the area for making every sub-regions is upper
State default unit area;
It is true from above-mentioned many sub-regions according to the functional area information with demand of parking corresponding with current slot
Surely there is the subregion of above-mentioned functions;
It is corresponding, above-mentioned classification number determining module 904, also particularly useful for:
It is upper by having in above-mentioned many sub-regions before the subregion classification determined using default sorting algorithm pair
The subregion number for stating function is defined as classifying the number of obtained classification.
Further, above-mentioned determining device also includes:
Shared bicycle monitoring module 906, for being parked a little for each shared bicycle, the shared of a setting is parked according to this
The GPS information that bicycle is provided, is monitored to the shared bicycle;
Supply-demand relationship determining module 907, for determining that this parks shared bicycle user a little together according to monitored results
Enjoy the supply-demand relationship of bicycle;
Bicycle quantity adjusting module 908, for according to above-mentioned supply-demand relationship adjust this park a little set by share bicycle
Quantity.
In shared bicycle provided in an embodiment of the present invention parks determining device a little, it is determined that shared bicycle is parked a little
During, time factor is associated with the subregion with the demand of parking, and multiple has to current slot is corresponding
The subregion for parking demand is classified, and is parked the center of each classification as shared bicycle a little, so can be effective
Ground instructs shared bicycle administrative staff to be scheduled shared bicycle, so as to meet use of the current slot in predeterminable area
Is reduced at family by some region as far as possible and the shared bicycle situation that supply falls short of demand occurs, user experience is lifted for the demand of shared bicycle.
The respective handling step that the function of above-mentioned each unit may correspond in flow shown in Fig. 1 to Fig. 8, no longer goes to live in the household of one's in-laws on getting married herein
State.
Determination method a little is parked corresponding to the shared bicycle in Fig. 1, the embodiment of the present invention additionally provides a kind of computer
Equipment, as shown in Figure 10, the equipment include memory 1000, processor 2000 and are stored on the memory 1000 and can be at this
The computer program run on processor 2000, wherein, above-mentioned processor 2000 is realized above-mentioned when performing above computer program
The step of shared bicycle parks determination method a little.
Specifically, above-mentioned memory 1000 and processor 2000 can be general memory and processor, not do here
It is specific to limit, when the computer program that the run memory 1000 of processor 2000 is stored, it is able to carry out above-mentioned shared bicycle and stops
Determination method a little is put, so as to solve to park a problem of degree of accuracy is low in the presence of the shared bicycle determined, causes often appearance
Supply falls short of demand or easy situation for a certain district-share bicycle, causes the shared bicycle wasting of resources, it is impossible to play it most
Big value, the problem of reducing user experience, and then shared bicycle administrative staff can be effectively instructed to sharing bicycle
It is scheduled, meets demand of user of the current slot in predeterminable area to shared bicycle, some region is reduced as far as possible
There is the shared bicycle situation that supply falls short of demand, lift user experience.
Determination method a little is parked corresponding to the shared bicycle in Fig. 1, the embodiment of the present invention additionally provides a kind of computer
Be stored with computer program on readable storage medium storing program for executing, the computer-readable recording medium, and the computer program is run by processor
The step of above-mentioned shared bicycles of Shi Zhihang park determination method a little.
Specifically, the storage medium can be general storage medium, such as mobile disk, hard disk, on the storage medium
Computer program when being run, be able to carry out above-mentioned shared bicycle and park determination method a little, determined so as to solve to exist
Shared bicycle park a problem of degree of accuracy is low, cause often to occur a certain district-share bicycle supply falls short of demand or for excessively
Situation about asking, causes the shared bicycle wasting of resources, it is impossible to play its maximum value, the problem of reducing user experience is entered
And can effectively instruct shared bicycle administrative staff to be scheduled shared bicycle, current slot is met positioned at predeterminable area
Interior user reduces some region and the shared bicycle situation that supply falls short of demand occurs, lift user as far as possible to the demand of shared bicycle
Experience Degree.
Claims (10)
1. a kind of shared bicycle parks determination method a little, it is characterised in that methods described includes:
According to the functional area information with demand of parking corresponding with current slot, determined from predeterminable area with described
The subregion of function;
The subregion classification determined using default sorting algorithm pair;
The center for obtained each classification of classifying is defined as into shared bicycle to park a little, each classification is comprising at least
One sub-regions.
2. according to the method described in claim 1, it is characterised in that the default sorting algorithm is K-means algorithms;
Before being classified using default sorting algorithm to the subregion, in addition to:
According to the position relationship between each subregion, it is determined that the number for the classification that classification is obtained.
3. method according to claim 2, it is characterised in that the position relationship according between each subregion,
It is determined that the number for the classification that classification is obtained, is specifically included:
For every sub-regions, according to the position relationship between the subregion and other subregions, determine belonging to the subregion
The subregion is defined as isolated area by subregion collection;
The number of the subregion collection of division is defined as classifying the number of obtained classification;
Wherein, the subregion collection meets following first preparatory condition:
For every sub-regions collection, any subregion that the subregion collection is included the subregion concentrate exist another subregion with
The distance between any subregion is within pre-determined distance threshold value;And subregion is not present in the subregion outside the subregion collection
With the distance between any subregion within pre-determined distance threshold value;
The isolated area meets following second preparatory condition:
For each subregion as isolated area, in the absence of the distance between any subregion and the subregion it is default away from
Within threshold value.
4. method according to claim 3, it is characterised in that be defined as classifying by the number of the subregion collection of division
Before the number of the classification arrived, in addition to:
The every sub-regions obtained from division are concentrated, and determine that area is more than or equal to the subregion collection of preset area;
According to default segmentation rule, the subregion collection determined is divided into segmentation subregion collection;
The number of the subregion collection by division is defined as classifying the number of obtained classification, specifically includes:
The quantity of not segmented subregion collection and the quantity sum of segmentation subregion collection obtained through over-segmentation are defined as point
The number for the classification that class is obtained.
5. the method according to claim 3 or 4, it is characterised in that the subregion determined using K-means algorithms pair
Classification, is specifically included:
For the subregion in the subregion in addition to isolated area, the center position coordinates point of K sub-regions are randomly selected
Not as the cluster centre initial value of K classification, wherein, the number for the classification that K obtains for classification;
Perform following sorting procedure:
For every sub-regions in remaining all subregion in all subregion in addition to this K cluster centre, the son is determined
Regional center position is respectively the distance between with this K cluster centre;
Cluster centre generic nearest with the subregion center position in this K cluster centre is defined as the son
Region generic;
For obtained each classification, it is determined that the average value of all subregion center position coordinates of the affiliated category, and this is put down
The center position coordinates of the affiliated subregion of the corresponding coordinate position of average are defined as the cluster centre that next cluster process is used;With
And
Judge whether the next cluster process cluster centre used and the cluster centre that this cluster process is used meet default
Condition, if it is not satisfied, the cluster centre for then using next cluster process is performed again as this new K cluster centre
The sorting procedure;If meeting, the classification results that this cluster process is obtained are defined as final classification result.
6. according to the method described in claim 1, it is characterised in that the default sorting algorithm is K-means algorithms;
According to the functional area information with demand of parking corresponding with current slot, determined from predeterminable area with described
The subregion of function, is specifically included:
The predeterminable area is divided into by many sub-regions based on default unit area, the area for making every sub-regions is described pre-
If unit area;
According to the functional area information with demand of parking corresponding with current slot, tool is determined from the multiple subregion
There is the subregion of the function;
Before the subregion classification determined using default sorting algorithm pair, in addition to:
Subregion number with the function in the multiple subregion is defined as classifying the number of obtained classification.
7. method according to claim 5, it is characterised in that also include:
Parked a little for each shared bicycle, the global position system GPS letter that a shared bicycle set is provided is parked according to this
Breath, is monitored to the shared bicycle;
Determine that this parks shared bicycle user a little and the supply-demand relationship of shared bicycle according to monitored results;
According to the supply-demand relationship adjust this park a little set by share bicycle quantity.
8. a kind of shared bicycle parks determining device a little, it is characterised in that described device includes:
Subregion determining module, for according to it is corresponding with current slot have park the functional area information of demand, from pre-
If determining the subregion with the function in region;
Subregion sort module, for the subregion classification determined using default sorting algorithm pair;
Bicycle parks a determining module, is parked for the center for obtained each classification of classifying to be defined as into shared bicycle
Point, each classification includes at least one subregion.
9. a kind of computer equipment, including memory, processor and it is stored on the memory and can be on the processor
The computer program of operation, it is characterised in that realized described in the computing device during computer program the claims 1 to
The step of method described in 7 any one.
10. be stored with computer program, its feature on a kind of computer-readable recording medium, the computer-readable recording medium
It is, the step of method described in any one of the claims 1 to 7 is performed when the computer program is run by processor.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710517669.1A CN107292798A (en) | 2017-06-29 | 2017-06-29 | A kind of shared bicycle parks determination method and device a little |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710517669.1A CN107292798A (en) | 2017-06-29 | 2017-06-29 | A kind of shared bicycle parks determination method and device a little |
Publications (1)
Publication Number | Publication Date |
---|---|
CN107292798A true CN107292798A (en) | 2017-10-24 |
Family
ID=60098514
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710517669.1A Pending CN107292798A (en) | 2017-06-29 | 2017-06-29 | A kind of shared bicycle parks determination method and device a little |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN107292798A (en) |
Cited By (15)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108205884A (en) * | 2018-01-02 | 2018-06-26 | 童超 | A kind of standardized and orderly shared bicycle parking method and system |
CN108364213A (en) * | 2018-02-06 | 2018-08-03 | 浙江齐享科技有限公司 | A kind of parking method and system of shared Moped Scooter |
CN108765927A (en) * | 2018-06-08 | 2018-11-06 | 上海新炬网络技术有限公司 | Management method is parked in a kind of shared bicycle intelligence |
CN108898294A (en) * | 2018-06-15 | 2018-11-27 | 杭州后博科技有限公司 | Bicycle active schedule distribution method and system are shared in a kind of region |
CN109145989A (en) * | 2018-08-22 | 2019-01-04 | 深圳市东部公共交通有限公司 | Bus station distribution method, device and terminal |
CN109726964A (en) * | 2019-01-04 | 2019-05-07 | 杭州卓凯科技有限公司 | The method that the resident point of driver excavates is carried out according to driver's historical track |
CN109740684A (en) * | 2019-01-08 | 2019-05-10 | 北京工业大学 | Shared bicycle lairage detection method and device |
CN111210135A (en) * | 2019-12-31 | 2020-05-29 | 上海钧正网络科技有限公司 | Order dispatching method and device, order dispatching platform server and order dispatching system |
CN111649759A (en) * | 2020-06-18 | 2020-09-11 | 北京骑胜科技有限公司 | Navigation method, device, equipment and storage medium of vehicle |
CN111881939A (en) * | 2020-06-24 | 2020-11-03 | 东南大学 | Shared single-vehicle parking area layout method based on clustering algorithm |
CN112185014A (en) * | 2020-04-07 | 2021-01-05 | 江苏智途科技股份有限公司 | Method for judging rationality of parking points of shared bicycle |
CN112884498A (en) * | 2019-11-29 | 2021-06-01 | 浙江大搜车软件技术有限公司 | Charging equipment address selection method and device |
CN115018389A (en) * | 2022-08-05 | 2022-09-06 | 深圳壹家智能锁有限公司 | Management scheduling method, device, equipment and storage medium of self-service wheelchair |
CN115409536A (en) * | 2022-07-21 | 2022-11-29 | 浙江本源质品信息科技股份有限公司 | Campus personnel flow adaptive site scheduling method and system |
CN118072502A (en) * | 2024-04-17 | 2024-05-24 | 北京工业大学 | Planning method and device for electronic fence, electronic equipment and storage medium |
Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104166895A (en) * | 2014-07-28 | 2014-11-26 | 浙江工业大学 | Public bike scheduling area dividing method |
CN104376327A (en) * | 2014-11-05 | 2015-02-25 | 南京师范大学 | Public bike leasing point clustering method |
CN104850900A (en) * | 2015-04-27 | 2015-08-19 | 北京工业大学 | Public bicycle system branch layout optimization complete set method |
CN105868860A (en) * | 2016-04-07 | 2016-08-17 | 浙江万马新能源有限公司 | Clustering-based area trip will intensity analysis method, apparatus and addressing method |
-
2017
- 2017-06-29 CN CN201710517669.1A patent/CN107292798A/en active Pending
Patent Citations (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN104166895A (en) * | 2014-07-28 | 2014-11-26 | 浙江工业大学 | Public bike scheduling area dividing method |
CN104376327A (en) * | 2014-11-05 | 2015-02-25 | 南京师范大学 | Public bike leasing point clustering method |
CN104850900A (en) * | 2015-04-27 | 2015-08-19 | 北京工业大学 | Public bicycle system branch layout optimization complete set method |
CN105868860A (en) * | 2016-04-07 | 2016-08-17 | 浙江万马新能源有限公司 | Clustering-based area trip will intensity analysis method, apparatus and addressing method |
Non-Patent Citations (1)
Title |
---|
张莉: "城市公共自行车租赁点规划", 《中国优秀硕士学位论文全文数据库 工程科技Ⅱ辑》 * |
Cited By (21)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108205884A (en) * | 2018-01-02 | 2018-06-26 | 童超 | A kind of standardized and orderly shared bicycle parking method and system |
CN108364213A (en) * | 2018-02-06 | 2018-08-03 | 浙江齐享科技有限公司 | A kind of parking method and system of shared Moped Scooter |
CN108765927A (en) * | 2018-06-08 | 2018-11-06 | 上海新炬网络技术有限公司 | Management method is parked in a kind of shared bicycle intelligence |
CN108898294B (en) * | 2018-06-15 | 2020-06-30 | 杭州后博科技有限公司 | Active dispatching distribution method and system for shared bicycle in area |
CN108898294A (en) * | 2018-06-15 | 2018-11-27 | 杭州后博科技有限公司 | Bicycle active schedule distribution method and system are shared in a kind of region |
CN109145989A (en) * | 2018-08-22 | 2019-01-04 | 深圳市东部公共交通有限公司 | Bus station distribution method, device and terminal |
CN109145989B (en) * | 2018-08-22 | 2021-07-06 | 深圳市东部公共交通有限公司 | Bus stop layout method and device and computer terminal |
CN109726964A (en) * | 2019-01-04 | 2019-05-07 | 杭州卓凯科技有限公司 | The method that the resident point of driver excavates is carried out according to driver's historical track |
CN109740684A (en) * | 2019-01-08 | 2019-05-10 | 北京工业大学 | Shared bicycle lairage detection method and device |
CN112884498A (en) * | 2019-11-29 | 2021-06-01 | 浙江大搜车软件技术有限公司 | Charging equipment address selection method and device |
CN111210135A (en) * | 2019-12-31 | 2020-05-29 | 上海钧正网络科技有限公司 | Order dispatching method and device, order dispatching platform server and order dispatching system |
CN112185014A (en) * | 2020-04-07 | 2021-01-05 | 江苏智途科技股份有限公司 | Method for judging rationality of parking points of shared bicycle |
CN111649759A (en) * | 2020-06-18 | 2020-09-11 | 北京骑胜科技有限公司 | Navigation method, device, equipment and storage medium of vehicle |
CN111881939A (en) * | 2020-06-24 | 2020-11-03 | 东南大学 | Shared single-vehicle parking area layout method based on clustering algorithm |
CN111881939B (en) * | 2020-06-24 | 2021-03-09 | 东南大学 | Shared single-vehicle parking area layout method based on clustering algorithm |
CN115409536A (en) * | 2022-07-21 | 2022-11-29 | 浙江本源质品信息科技股份有限公司 | Campus personnel flow adaptive site scheduling method and system |
CN115409536B (en) * | 2022-07-21 | 2023-09-15 | 浙江本源质品信息科技股份有限公司 | Campus personnel flow adaptive site scheduling method and system |
CN115018389A (en) * | 2022-08-05 | 2022-09-06 | 深圳壹家智能锁有限公司 | Management scheduling method, device, equipment and storage medium of self-service wheelchair |
CN115018389B (en) * | 2022-08-05 | 2022-10-25 | 深圳壹家智能锁有限公司 | Management scheduling method, device, equipment and storage medium of self-service wheelchair |
CN118072502A (en) * | 2024-04-17 | 2024-05-24 | 北京工业大学 | Planning method and device for electronic fence, electronic equipment and storage medium |
CN118072502B (en) * | 2024-04-17 | 2024-06-21 | 北京工业大学 | Planning method and device for electronic fence, electronic equipment and storage medium |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN107292798A (en) | A kind of shared bicycle parks determination method and device a little | |
CN107491895A (en) | A kind of shared bicycle parks determination method and device a little | |
CN105206046B (en) | The addressing of tax services station and feasibility assessment method based on big data | |
CN106297273B (en) | The processing method and processing device of regular bus route | |
CN108537391B (en) | Taxi stop station setting optimization method based on taxi track data | |
CN105185116B (en) | The intensive minibus trip requirements thermodynamic chart construction method of network | |
US20180300655A1 (en) | Method and device for obtaining demand-transport capacity unmatched region in car-calling services, an apparatus and non-volatile computer storage medium | |
CN108009653B (en) | Order management method, device, server and computer readable storage medium | |
Wei et al. | Zest: a hybrid model on predicting passenger demand for chauffeured car service | |
CN110909759A (en) | Urban area hierarchical management system and method based on population big data | |
CN104809344A (en) | IC (Integrated Circuit) card data-based estimation method for passenger flow in bus station interval | |
CN108388970B (en) | Bus station site selection method based on GIS | |
CN108510730A (en) | Vehicle dispatching method and system between shared automobile site | |
KR102288490B1 (en) | Vehicle rental method, system and program based on limit waiting time | |
CN113240265B (en) | Urban space division method based on multi-mode traffic data | |
CN106022577A (en) | On-line balanced scheduling for passenger vehicle | |
CN111861078A (en) | Work order distribution method and device, electronic equipment and storage medium | |
CN106875734A (en) | A kind of method and device for pushing parking route | |
Ge et al. | Urban taxi ridership analysis in the emerging metropolis: Case study in Shanghai | |
Caggiani et al. | A dynamic clustering method for relocation process in free-floating vehicle sharing systems | |
CN109785612A (en) | A kind of taxi intelligent dispatching method and device based on easy carrying coefficient | |
CN106130110B (en) | The electric taxi charging station constant volume method on trip ground is selected based on stratified probability | |
Kwakye et al. | An Android-based mobile paratransit application for vulnerable road users | |
CN105069055A (en) | Recommendation method, system and client for taking taxi | |
CN116882609A (en) | Customized bus route multi-objective optimization method based on improved track clustering algorithm |
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 | ||
CB02 | Change of applicant information |
Address after: 100070, No. 101-8, building 1, 31, zone 188, South Fourth Ring Road, Beijing, Fengtai District Applicant after: Guoxin Youyi Data Co., Ltd Address before: 100070, No. 188, building 31, headquarters square, South Fourth Ring Road West, Fengtai District, Beijing Applicant before: SIC YOUE DATA Co.,Ltd. |
|
CB02 | Change of applicant information | ||
RJ01 | Rejection of invention patent application after publication |
Application publication date: 20171024 |
|
RJ01 | Rejection of invention patent application after publication |