CN108681791A - A kind of density of stream of people prediction technique, device and storage medium - Google Patents
A kind of density of stream of people prediction technique, device and storage medium Download PDFInfo
- Publication number
- CN108681791A CN108681791A CN201810469742.7A CN201810469742A CN108681791A CN 108681791 A CN108681791 A CN 108681791A CN 201810469742 A CN201810469742 A CN 201810469742A CN 108681791 A CN108681791 A CN 108681791A
- Authority
- CN
- China
- Prior art keywords
- people
- stream
- density
- road
- predicted
- 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.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 31
- 230000001052 transient effect Effects 0.000 claims abstract description 5
- 230000002452 interceptive effect Effects 0.000 claims abstract description 4
- 230000006870 function Effects 0.000 claims description 25
- 238000007619 statistical method Methods 0.000 claims description 3
- 238000004891 communication Methods 0.000 claims description 2
- 238000010586 diagram Methods 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 4
- 238000001514 detection method Methods 0.000 description 3
- 238000009499 grossing Methods 0.000 description 3
- 241000208340 Araliaceae Species 0.000 description 2
- 235000005035 Panax pseudoginseng ssp. pseudoginseng Nutrition 0.000 description 2
- 235000003140 Panax quinquefolius Nutrition 0.000 description 2
- 235000008434 ginseng Nutrition 0.000 description 2
- 230000002902 bimodal effect Effects 0.000 description 1
- 238000010276 construction Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 239000004744 fabric Substances 0.000 description 1
- 238000009434 installation Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 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
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression 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
- 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
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Strategic Management (AREA)
- Data Mining & Analysis (AREA)
- Tourism & Hospitality (AREA)
- Economics (AREA)
- Human Resources & Organizations (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- General Business, Economics & Management (AREA)
- Marketing (AREA)
- Mathematical Physics (AREA)
- Development Economics (AREA)
- Mathematical Analysis (AREA)
- Computational Mathematics (AREA)
- Operations Research (AREA)
- Health & Medical Sciences (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Probability & Statistics with Applications (AREA)
- Primary Health Care (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- Evolutionary Biology (AREA)
- Game Theory and Decision Science (AREA)
- Quality & Reliability (AREA)
- Life Sciences & Earth Sciences (AREA)
- Bioinformatics & Computational Biology (AREA)
- Algebra (AREA)
- General Health & Medical Sciences (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Traffic Control Systems (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
An embodiment of the present invention provides a kind of density of stream of people prediction techniques, including：The time changing curve for obtaining density of stream of people, is fitted curve to obtain density of stream of people matched curve, corresponding density of stream of people fitting function is obtained according to the density of stream of people matched curve；The density of stream of people data of the road to be predicted are substituted into the density of stream of people fitting function, obtain road fitting Function feature parameter to be predicted by the density of stream of people data for obtaining road to be predicted；Road density of stream of people time changing curve function to be predicted is obtained according to the road fitting Function feature parameter to be predicted, and according to the density of stream of people of the road density of stream of people time changing curve function prediction to be predicted road to be predicted.The embodiment of the present invention additionally provides a kind of active interactive device and non-transient readable storage medium storing program for executing, for realizing the method.The present invention can be widely applied to density of stream of people prediction field, higher to the forecasting efficiency of density of stream of people.
Description
Technical field
The present embodiments relate to big data technical field more particularly to a kind of density of stream of people prediction technique, device and deposit
Storage media.
Background technology
Density of stream of people is a kind of important urban basic data, no matter in urban traffic control or municipal public safety pipe
Particularly important effect is suffered from reason.Hardware approach is belonged to substantially to the acquisition methods of density of stream of people data at present, including
Video detection and inductance loop detection, video detection is vulnerable to the influence of light, and inductance loop need to carry out road cutting construction, pushes away
Extensively extremely it is not easy.Although the data that these methods obtain are more accurate, but if carrying out large-scale data acquisition, then will appear
Performance difficulty, inefficient defect.Therefore, it finds a kind of efficient and is convenient for widely applied density of stream of people prediction technique, just
As industry urgent problem to be solved.
Invention content
In view of the above-mentioned problems existing in the prior art, an embodiment of the present invention provides a kind of density of stream of people prediction technique, dresses
It sets and storage medium.
On the one hand, an embodiment of the present invention provides a kind of density of stream of people prediction techniques, including：Obtain the time of density of stream of people
Change curve is fitted curve to obtain density of stream of people matched curve, be obtained accordingly according to the density of stream of people matched curve
Density of stream of people fitting function；The density of stream of people data for obtaining road to be predicted, by the density of stream of people number of the road to be predicted
According to the density of stream of people fitting function is substituted into, road fitting Function feature parameter to be predicted is obtained；According to the road to be predicted
Fitting function characteristic parameter obtains road density of stream of people time changing curve function to be predicted, and according to the road passerby to be predicted
The density of stream of people of current density time changing curve function prediction road to be predicted.
On the other hand, an embodiment of the present invention provides a kind of active interactive device and a kind of non-transient readable storage medium storing program for executing.
A kind of active interactive device includes：At least one processor；And what is connect with the processor communication at least one deposits
Reservoir, wherein：The memory is stored with the program instruction that can be executed by the processor, and the processor calls described program
Instruction is able to carry out a kind of density of stream of people prediction technique.A kind of non-transient readable storage medium storing program for executing stores program instruction,
For executing a kind of density of stream of people prediction technique.
An embodiment of the present invention provides a kind of density of stream of people prediction technique, device and storage mediums, quasi- by density of stream of people
Density of stream of people curve is closed out, corresponding density of stream of people fitting function is obtained, obtaining density of stream of people further according to specific road conditions is fitted letter
Then several parameters obtains the available effective density of stream of people fitting function of specific road conditions and predicts density of stream of people situation.It should
Method, apparatus and storage medium can be widely applied to density of stream of people prediction field, higher to the forecasting efficiency of density of stream of people.
Description of the drawings
In order to more clearly explain the embodiment of the invention or the technical proposal in the existing technology, to embodiment or will show below
There is attached drawing needed in technology description to be briefly described, it should be apparent that, the accompanying drawings in the following description is this hair
Some bright embodiments for those of ordinary skill in the art without creative efforts, can be with root
Other attached drawings are obtained according to these attached drawings.
Fig. 1 is the overall flow figure of density of stream of people prediction technique in first embodiment of the invention；
Fig. 2 is density of stream of people curve synoptic diagram in first embodiment of the invention；
Fig. 3 is density of stream of people multimodal matched curve schematic diagram in first embodiment of the invention；
Fig. 4 is the hardware device operating diagram of the embodiment of the present invention.
Specific implementation mode
In order to make the object, technical scheme and advantages of the embodiment of the invention clearer, below in conjunction with the embodiment of the present invention
In attached drawing, technical scheme in the embodiment of the invention is clearly and completely described, it is clear that described embodiment is
A part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art
The every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
An embodiment of the present invention provides a kind of density of stream of people prediction technique, device and storage mediums.It is this referring to Fig. 1, Fig. 1
The overall flow figure of density of stream of people prediction technique in invention first embodiment, including：
S101：The time changing curve for obtaining density of stream of people, is fitted curve to obtain density of stream of people matched curve, root
Corresponding density of stream of people fitting function is obtained according to the density of stream of people matched curve.
By statistical analysis, obtain the density of stream of people in each section with 24 hours in cyclically-varying (that is, density of stream of people
The period of change of time changing curve includes：24 hours are a period of change), and the density of stream of people curve in the monocycle is in more
Peak curve.In many engineering problems, there are two peak values for the figure of the probability density function of stochastic variable.General point
Only there are one peak value or no peak values for cloth function, and carry out multimodal fitting and can be very good to describe this have bimodal or multimodal shape
The variable of state.Multimodal Gauss curve fitting analysis is carried out using origin tools, the multimodal matched curve of density of stream of people can be obtained,
The Gaussian function of fitting is shown below：
Wherein y0For baseline, B is peak area, and w is the halfwidth at the peak, xcFor peak position.
It is density of stream of people curve synoptic diagram in first embodiment of the invention referring to Fig. 2, Fig. 2, including：
Stream of people's metric density axis 201, time shaft 202, average density of stream of people 203 and data smoothing curve 204.
The flow of the people for choosing certain a road section, to be that time interval counts the stream of people per hour, by taking density of stream of people as an example,
By data carry out 5 points it is smooth three times after to obtain curve as shown in Figure 2.As seen from the figure, data smoothing curve 204 and the average stream of people
The basic trend of density 203 is consistent.
It is fitted analysis for density of stream of people, setting peak number is 2, and exports y0, B1, B2, w1, w2, xc1, xc2Deng ginseng
Number, fitting phase knowledge and magnanimity are 0.961.
The Gaussian rough surface curve for by density of stream of people data obtain after multimodal fitting meets following relationship：
In Gaussian function, xcFor peak position, in formula (2), xc1The ebb of expression night density of stream of people, and xc2For noon peak
Or the evening peak moment, this has generality on whole city's road；w1And w2To correspond to the halfwidth at peak, in density of stream of people curve,
The duration of each rush hour section can be considered as unanimously substantially；B1And B2The area surrounded by peak area, that is, peak curve and baseline, should
Value is related with the otherness of road itself, but the statistic due to choosing herein is density of stream of people, i.e. number in unit area
Amount, therefore the peak area of same standard road is with uniformity.
S102：The density of stream of people data for obtaining road to be predicted substitute into the density of stream of people data of the road to be predicted
The density of stream of people fitting function obtains road fitting Function feature parameter to be predicted.
It is density of stream of people multimodal matched curve schematic diagram in first embodiment of the invention referring to Fig. 3, Fig. 3, including：
Density of stream of people axis 301, time shaft 302, the second peak fitting curve 303, the first peak value matched curve 304, multimodal
Matched curve 305 and data smoothing curve 306.The parameter that two curves are exported is B1, B2, w1, w2, xc1, xc2.Wherein, B1、
w1And xc1It is the output parameter of the first peak value matched curve 304.B2、w2And xc2It is the output ginseng of the second peak fitting curve 303
Amount.
S103：Road density of stream of people time change to be predicted is obtained according to the road fitting Function feature parameter to be predicted
Curvilinear function, and it is close according to the stream of people of the road density of stream of people time changing curve function prediction to be predicted road to be predicted
Degree.
The density of stream of people indicatrix function that any one road can be obtained by above-mentioned output parameter, for the moment by the road
Density of stream of people data (the x at quarter1, y1) formula is substituted into, y can be acquired0, so as to obtain any time x in 24 hours by calculating
Corresponding density of stream of people y, such as following formula：
Second embodiment of the invention is based on first embodiment.Wherein, the time changing curve for obtaining density of stream of people, packet
It includes：Count typical road density of stream of people data (in another embodiment, it is described statistics typical road density of stream of people data,
Including：Density of stream of people data are obtained according to the length of electric vehicle and spacing.Wherein, the spacing includes：Front-and-rear vehicle distance and
Left and right spacing.In another embodiment, the density of stream of people data of the statistics typical road, including：According to the sociodistance of people
Obtain density of stream of people data), it is for statistical analysis to the density of stream of people data of the typical road to obtain the time of density of stream of people
Change curve.
Third embodiment of the invention is based on second embodiment.Wherein, the density of stream of people data of the statistics typical road, packet
It includes：
It sums the length of electric vehicle and front-and-rear vehicle distance to obtain people longitudinal direction occupy-place distance, the width of electric vehicle is asked with left and right spacing
With obtain people's transverse direction occupy-place distance, by the people longitudinal direction occupy-place distance with people's transverse direction occupy-place apart from quadrature, then take described
Long-pending inverse obtains density of stream of people data.
Specifically, for being primarily present form by the stream of people on road as electric vehicle of riding.The length of electric vehicle is assumed to be
1.875m pardons and is set as 0.85m, and height is assumed to be 1.1m, and front-and-rear vehicle distance and left and right spacing are 1m, and uploading 1 people by vehicle calculates, then
It is 1/ [(1.875+1) * (0.85+1)]=0.188 people/m per square meter people's quantity2。
Fourth embodiment of the invention is based on second embodiment.Wherein, the density of stream of people data of the statistics typical road, packet
It includes：
Using the half of the sociodistance of the people as social radius, the area of social circle is obtained with the social radius,
Then the inverse of the area of the social circle is taken to obtain density of stream of people data.
Specifically, by taking the main existence form of the stream of people on road is walking as an example.The sociodistance of people is assumed to be 1.2m, then
It is 1/ [3.14*0.6*0.6]=0.885 people/m per square meter people's quantity2。
It is the hardware device operating diagram of the embodiment of the present invention referring to Fig. 4, Fig. 4, the hardware device includes：A kind of people
Current density prediction meanss 401, processor 402 and storage medium 403.
Density of stream of people prediction meanss 401：A kind of density of stream of people prediction meanss 401 realize that a kind of density of stream of people is pre-
Survey method.
Processor 402：The processor 402 loads and executes the instruction in the storage medium 403 and data for real
A kind of existing density of stream of people prediction technique.
Storage medium 403：403 store instruction of the storage medium and data；The storage medium 403 is for realizing described
A kind of density of stream of people prediction technique.
The apparatus embodiments described above are merely exemplary, wherein the unit illustrated as separating component can
It is physically separated with being or may not be, the component shown as unit may or may not be physics list
Member, you can be located at a place, or may be distributed over multiple network units.It can be selected according to the actual needs
In some or all of module achieve the purpose of the solution of this embodiment.Those of ordinary skill in the art are not paying creativeness
Labour in the case of, you can to understand and implement.
Through the above description of the embodiments, those skilled in the art can be understood that each embodiment can
It is realized by the mode of software plus required general hardware platform, naturally it is also possible to pass through hardware.Based on this understanding, on
Stating technical solution, substantially the part that contributes to existing technology can be expressed in the form of software products in other words, should
Computer software product can store in a computer-readable storage medium, such as ROM/RAM, magnetic disc, CD, including several fingers
It enables and using so that a computer installation (can be personal computer, server or network equipment etc.) executes each implementation
Method described in certain parts of example or embodiment.
Finally it should be noted that：The above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although
Present invention has been described in detail with reference to the aforementioned embodiments, it will be understood by those of ordinary skill in the art that：It still may be used
With technical scheme described in the above embodiments is modified or equivalent replacement of some of the technical features；
And these modifications or replacements, various embodiments of the present invention technical solution that it does not separate the essence of the corresponding technical solution spirit and
Range.
Claims (10)
1. a kind of density of stream of people prediction technique, which is characterized in that including：
The time changing curve for obtaining density of stream of people, is fitted curve to obtain density of stream of people matched curve, according to the people
Current density matched curve obtains corresponding density of stream of people fitting function；
It is close to be substituted into the stream of people by the density of stream of people data for obtaining road to be predicted for the density of stream of people data of the road to be predicted
Fitting function is spent, road fitting Function feature parameter to be predicted is obtained；
Road density of stream of people time changing curve function to be predicted is obtained according to the road fitting Function feature parameter to be predicted,
And according to the density of stream of people of the road density of stream of people time changing curve function prediction to be predicted road to be predicted.
2. according to the method described in claim 1, it is characterized in that, it is described obtain density of stream of people time changing curve, including：
The density of stream of people data of typical road are counted, it is for statistical analysis to the density of stream of people data of the typical road to obtain people
The time changing curve of current density.
3. according to the method described in claim 2, it is characterized in that, it is described statistics typical road density of stream of people data, including：
Density of stream of people data are obtained according to the length of electric vehicle and spacing.
4. according to the method described in claim 3, it is characterized in that, the spacing, including：
Front-and-rear vehicle distance and left and right spacing.
5. according to the method described in claim 2, it is characterized in that, it is described statistics typical road density of stream of people data, including：
Density of stream of people data are obtained according to the sociodistance of people.
6. according to the method described in claim 4, it is characterized in that, it is described statistics typical road density of stream of people data, including：
It sums the length of electric vehicle and front-and-rear vehicle distance to obtain people longitudinal direction occupy-place distance, width and the left and right spacing of electric vehicle is summed
To people's transverse direction occupy-place distance, then the people longitudinal direction occupy-place distance is taken into the product with people's transverse direction occupy-place apart from quadrature
Inverse obtains density of stream of people data.
7. according to the method described in claim 5, it is characterized in that, it is described statistics typical road density of stream of people data, including：
Using the half of the sociodistance of the people as social radius, the area of social circle is obtained with the social radius, then
The inverse of the area of the social circle is taken to obtain density of stream of people data.
8. according to the method described in claim 1, it is characterized in that, the period of change of the time changing curve of the density of stream of people
Including：24 hours are a period of change.
9. a kind of active interactive device, which is characterized in that including：
At least one processor；And
At least one processor being connect with the processor communication, wherein：
The memory is stored with the program instruction that can be executed by the processor, and the processor calls described program to instruct energy
Enough methods executed as described in claim 1 to 8 any claim.
10. a kind of non-transient readable storage medium storing program for executing, which is characterized in that the non-transient readable storage medium storing program for executing stores program instruction,
Described program instruction is for executing the method as described in claim 1 to 8 any claim.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810469742.7A CN108681791B (en) | 2018-05-16 | 2018-05-16 | People flow density prediction method, device and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810469742.7A CN108681791B (en) | 2018-05-16 | 2018-05-16 | People flow density prediction method, device and storage medium |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108681791A true CN108681791A (en) | 2018-10-19 |
| CN108681791B CN108681791B (en) | 2021-04-23 |
Family
ID=63806643
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201810469742.7A Active CN108681791B (en) | 2018-05-16 | 2018-05-16 | People flow density prediction method, device and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108681791B (en) |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110222886A (en) * | 2019-05-28 | 2019-09-10 | 东南大学 | A kind of commercial building by when density of personnel prediction technique |
| CN111540162A (en) * | 2020-04-17 | 2020-08-14 | 佛山科学技术学院 | Pedestrian flow early warning system based on raspberry group |
| WO2022097246A1 (en) * | 2020-11-05 | 2022-05-12 | 日本電信電話株式会社 | Movement prediction device, movement prediction method, and movement prediction program |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104680789A (en) * | 2015-03-04 | 2015-06-03 | 蔡诚昊 | Rapid road congestion index estimation and prediction method |
-
2018
- 2018-05-16 CN CN201810469742.7A patent/CN108681791B/en active Active
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104680789A (en) * | 2015-03-04 | 2015-06-03 | 蔡诚昊 | Rapid road congestion index estimation and prediction method |
Non-Patent Citations (1)
| Title |
|---|
| 冯悦: "基于集成学习的区域人流密度预测研究", 《中国优秀硕士学位论文全文数据库基础科学辑》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110222886A (en) * | 2019-05-28 | 2019-09-10 | 东南大学 | A kind of commercial building by when density of personnel prediction technique |
| CN111540162A (en) * | 2020-04-17 | 2020-08-14 | 佛山科学技术学院 | Pedestrian flow early warning system based on raspberry group |
| WO2022097246A1 (en) * | 2020-11-05 | 2022-05-12 | 日本電信電話株式会社 | Movement prediction device, movement prediction method, and movement prediction program |
| JP7435820B2 (en) | 2020-11-05 | 2024-02-21 | 日本電信電話株式会社 | Movement prediction device, movement prediction method, and movement prediction program |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108681791B (en) | 2021-04-23 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108681791A (en) | A kind of density of stream of people prediction technique, device and storage medium | |
| CN107124394B (en) | Power communication network security situation prediction method and system | |
| CN106529723A (en) | Method for realizing photovoltaic power station cleaning period estimation based on monitoring platform | |
| CN104102700A (en) | Categorizing method oriented to Internet unbalanced application flow | |
| CN104361110A (en) | Mass electricity consumption data analysis system as well as real-time calculation method and data mining method | |
| CN105071992B (en) | Substation's adapted electric industry business communication bandwidth prediction technique | |
| García Valverde et al. | Water demand estimation and outlier detection from smart meter data using classification and Big Data methods | |
| CN105303460A (en) | Identification method of key nodes and key branches in power grid | |
| CN108428342A (en) | A kind of vehicle density prediction technique, device and storage medium | |
| CN104182803A (en) | Wind power data preprocessing method, wind power forecast method and system | |
| CN110400462A (en) | Track traffic for passenger flow monitoring and pre-alarming method and its system based on fuzzy theory | |
| CN106816872B (en) | Coalmine high-voltage power network self-adaptive parallel short circuit calculation method based on genetic algorithm | |
| CN105740636A (en) | Mountain torrent disaster critical rainfall probability analysis method | |
| CN104732278A (en) | Deep neural network training method based on sea-cloud collaboration framework | |
| CN106600144A (en) | Anti-electricity-theft early warning analysis method with single anomaly analysis | |
| CN107330576A (en) | A kind of power distribution network efficiency rating method based on border power supply capacity | |
| CN109606183A (en) | The charging method and device of electric car | |
| CN102394868B (en) | Detection method for DDoS attacked address of dynamic threshold | |
| CN110413622A (en) | A kind of data processing method based on electric power big data platform | |
| Sun et al. | Knowledge representation for disruption management problems in urban distribution systems | |
| CN107527057A (en) | A kind of wind speed power rejecting abnormal data method and device | |
| CN104376366A (en) | Method and device for selecting optimal network maximum flow algorithm | |
| CN108899905B (en) | Identification method and device for key nodes in complex power grid | |
| Teres | Histogram visualization of smart grid data using MapReduce algorithm | |
| CN106845708B (en) | multi-objective optimization method of data stream processing system based on uncertainty |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |