CN110472771A - Regional population's trend estimate method and its system - Google Patents
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Abstract
The invention discloses regional population's trend estimate method and its systems.Regional population's trend estimate method is the following steps are included: step S1: predicting with subsequent time number of the polynomial fitting to certain region；Step S2: an irregular area P is divided into n sub-regions, the number of a certain moment X of each subregion is denoted as { Y_1, Y_2, Y_3, ..., Y_n }, the number of the subsequent time X^' of each subregion is denoted as { Y_1^', Y_2^', Y_3^' ... ..., Y_n^'}；Step S3: the irregular area P slope K at the i moment is denoted as, and in order to reduce influence of other consecutive points of contrast points to the contrast points, introduces jamproof depopulation function f(x)；Step S4: forecasted population flow tendency.Regional population's trend estimate method and its system disclosed by the invention, the movement of population direction of the given area at available a certain moment carry out size of population early warning operation herein in connection with population forecast and movement of population direction, prevent trouble before it happens.
Description
Technical field
The invention belongs to movement of population trend technical fields, and in particular to a kind of regional population's trend estimate method and one kind
Regional population's trend estimate system.
Background technique
Publication No. CN108830402A, subject name are the application for a patent for invention of Ways of Population Prediction and device, skill
Art scheme, which discloses, " obtains module, for obtaining the achievement data for carrying out a population projection, the achievement data is reflection people
At least one indication information of message breath；Generation module, for generating at least one population forecast task；Module is chosen, is used for
From preset model set, corresponding prediction mould is chosen for each population forecast task at least one of described population forecast task
Type, wherein include the prediction model of at least two types in the preset model set；Prediction module, for for described every
The achievement data of a population forecast task, prediction model and acquisition based on selection carries out a population projection ".
However, by taking above-mentioned patent of invention as an example, existing population forecast algorithm is primarily focused on based on position analysis
Region passenger flow early warning is not bound with population flow law and carries out early warning.It is at present mostly to be based on going through meanwhile in terms of movement of population
History statistical data calculates the population flow law in history, will predict without carrying out future, needs further to give
It improves.
Summary of the invention
The present invention is directed to the situation of the prior art, overcomes disadvantages described above, provide a kind of regional population's trend estimate method and
A kind of regional population's trend estimate system.
The present invention use following technical scheme, regional population's trend estimate method the following steps are included:
Step S1: it is predicted with subsequent time number of the polynomial fitting to certain region；
Step S2: an irregular area P is divided into n sub-regions, the number of a certain moment X of each subregion
It is denoted as { Y_1, Y_2, Y_3 ... ..., Y_n }, the number of the subsequent time X^' of each subregion is denoted as { Y_1^', Y_2^', Y_3
^',……,Y_n^'}；
Step S3: the irregular area P slope K at the i moment is denoted as, in order to which other consecutive points for reducing contrast points are right to this
Than the influence of point, jamproof depopulation function f (x) is introduced；
Step S4: forecasted population flow tendency.
The present invention use following technical scheme, regional population's trend estimate method the following steps are included:
Step T1: for region division to be predicted at n sub-regions, the number of a certain moment X of each subregion is remembered
For { Y1,Y2,Y3,……,Yn, the number of the subsequent time X ' of each subregion is denoted as { Y '1,Y′2,Y′3,……,Y′n}；
Step T2: polynomial regression model is created for each subregion, the polynomial regression model presets multinomial
Formula fitting algorithm；
Step T3: corresponding polynomial regression model is loaded for each subregion；
Step T4: each subregion successively calculates the change rate of the number of the subregion and the number in adjacent subarea domain, together
When introduce jamproof depopulation function f (x)；
Step T5: successively judge whether the population of each subregion has arrived at the population threshold value of the subregion；
Step T6: the maximum value of the absolute value of change rate in all subregions is determined, while according to the change of each subregion
The population of the positive and negative determination subregion of rate is that net inflow state or net flow do well.
According to above technical scheme, as the further preferred technical solution of above technical scheme, in the step T4,
It is denoted as in the change rate K at i moment:
According to above technical scheme, as the further preferred technical solution of above technical scheme, the step T5 is specific
It is embodied as following steps:
Step T5.1: successively judge that the population of each subregion has arrived at the population threshold value of the subregion:
Step T5.2: when the population of the subregion has arrived at the population threshold value of the subregion, then to the subregion into
Row early warning；
Step T5.3: when the population of the subregion does not reach the population threshold value of the subregion, then to the subregion not into
Row early warning.
According to above technical scheme, as the further preferred technical solution of above technical scheme, the step T5 may be used also
It is embodied as following steps:
Step T5.1: successively judge that the population of each subregion will reach the population threshold value and the sub-district of the subregion
The population in domain is also increasing:
Step T5.2: when the population of the subregion will reach the population threshold value of the subregion and the population of the subregion
Also when increasing, then early warning is carried out to the subregion；
Step T5.3: when the population of the subregion will reach the population threshold value of the subregion and the population of the subregion
When not increasing, then to the subregion without early warning.
The invention patent also discloses regional population's trend estimate system, for implementing any of the above item regional population trend
Prediction technique.
Regional population's trend estimate method and its system disclosed by the invention, the beneficial effect is that, it is available a certain
The movement of population direction of the given area at moment carries out size of population early warning behaviour herein in connection with population forecast and movement of population direction
Make, prevents trouble before it happens.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Specific embodiment
The invention discloses a kind of regional population's trend estimate methods and a kind of regional population's trend estimate system, tie below
Preferred embodiment is closed, further description of the specific embodiments of the present invention.
Referring to Figure 1 of the drawings, Fig. 1 shows the stream of regional population's trend estimate method and regional population's trend estimate system
Journey.
Preferred embodiment.
Preferably, present embodiment discloses a kind of regional population's trend estimate methods, comprising the following steps:
Step S1: it is predicted with subsequent time number of the polynomial fitting to certain region；
Step S2: an irregular area P is divided into n sub-regions, the number of a certain moment X of each subregion
It is denoted as { Y1,Y2,Y3,……,Yn, the number of the subsequent time X ' of each subregion is denoted as { Y '1,Y′2,Y′3,……,Y′n}；
Step S3: the irregular area P slope K at the i moment is denoted as, in order to which other consecutive points for reducing contrast points are right to this
Than the influence of point, jamproof depopulation function f (x) is introduced；
Step S4: forecasted population flow tendency.
Further, in step s 4, by comparing slope variation, when slope is bigger, show that this was lower than at the moment
Population trends it is obvious.
Further, in step s 4, using the maximum direction of flow tendency as principal direction.
The related procedure of regional population's trend estimate method is described below.
Wherein, regional population's trend estimate method the following steps are included:
Step T1:(start execute regional population's trend estimate method, simultaneously) for region to be predicted (for example, region
P n sub-regions) are divided into, the number of a certain moment X of each subregion is denoted as { Y1,Y2,Y3,……,Yn, each subregion
The number of subsequent time X ' be denoted as { Y '1,Y′2,Y′3,……,Y′n}；
Step T2: polynomial regression model is created for each subregion, the polynomial regression model presets multinomial
Formula fitting algorithm；
Step T3: corresponding polynomial regression model is loaded for each subregion；
Step T4: each subregion successively calculates the change rate of the number of the subregion and the number in adjacent subarea domain (i.e.
Slope, similarly hereinafter), while jamproof depopulation function f (x) is introduced (to reduce other adjacent subarea domain brings mistake
Difference)；
Step T5: successively judge whether the population of each subregion has arrived at the population threshold value of the subregion (or i.e.
The population of the population threshold value and the subregion that reach the subregion is also being increased)；
Step T6: determine that the maximum value of the absolute value of change rate in all subregions (characterizes the main side of flowing of population
To), while being net inflow state or net outflow according to the population of the positive and negative determination subregion of the change rate of each subregion
State.
Wherein, it in the step T4, is denoted as in the change rate K at i moment:
Wherein, the step T5 is embodied as following steps:
Step T5.1: successively judge that the population of each subregion has arrived at the population threshold value of the subregion:
Step T5.2: when the population of the subregion has arrived at the population threshold value of the subregion, then to the subregion into
Row early warning；
Step T5.3: when the population of the subregion does not reach the population threshold value of the subregion, then to the subregion not into
Row early warning (terminates to execute subregion population trend estimate method).
Wherein, the step T5 may also be embodied as following steps:
Step T5.1: successively judge that the population of each subregion will reach the population threshold value and the sub-district of the subregion
The population in domain is also increasing:
Step T5.2: when the population of the subregion will reach the population threshold value of the subregion and the population of the subregion
Also when increasing, then early warning is carried out to the subregion；
Step T5.3: when the population of the subregion will reach the population threshold value of the subregion and the population of the subregion
When not increasing, then to the subregion without early warning (terminating to execute regional population's trend estimate method).
The present embodiment also discloses regional population's trend estimate system, pre- for implementing any of the above item regional population trend
Survey method.
It is noted that the technologies such as polynomial fitting, depopulation function that present patent application is related to are special
Sign should be considered as the prior art, the specific structures of these technical characteristics, working principle and the control mode that may relate to, sky
Between arrangement use the conventional selection of this field, be not construed as where the inventive point of the invention patent, the present invention is special
Benefit is not done further specific expansion and is described in detail.
For a person skilled in the art, technical solution documented by foregoing embodiments can still be repaired
Change or equivalent replacement of some of the technical features, it is all within the spirits and principles of the present invention, made any to repair
Change, equivalent replacement, improvement etc., should be included in protection scope of the present invention.
Claims (6)
1. a kind of regional population's trend estimate method, which comprises the following steps:
Step S1: it is predicted with subsequent time number of the polynomial fitting to certain region；
Step S2: an irregular area P is divided into n sub-regions, the number of a certain moment X of each subregion is denoted as
The number of { Y_1, Y_2, Y_3 ... ..., Y_n }, the subsequent time X^' of each subregion are denoted as { Y_1^', Y_2^', Y_3
^',……,Y_n^'}；
Step S3: the irregular area P slope K at the i moment is denoted as, in order to reduce other consecutive points of contrast points to the contrast points
Influence, introduce jamproof depopulation function f (x)；
Step S4: forecasted population flow tendency.
2. a kind of regional population's trend estimate method, which comprises the following steps:
Step T1: for region division to be predicted at n sub-regions, the number of a certain moment X of each subregion is denoted as { Y1,
Y2,Y3,……,Yn, the number of the subsequent time X ' of each subregion is denoted as { Y '1,Y′2,Y′3,……,Y′n}；
Step T2: polynomial regression model is created for each subregion, it is quasi- that the polynomial regression model presets multinomial
Hop algorithm；
Step T3: corresponding polynomial regression model is loaded for each subregion；
Step T4: each subregion successively calculates the change rate of the number of the subregion and the number in adjacent subarea domain, draws simultaneously
Enter jamproof depopulation function f (x)；
Step T5: successively judge whether the population of each subregion has arrived at the population threshold value of the subregion；
Step T6: the maximum value of the absolute value of change rate in all subregions is determined, while according to the change rate of each subregion
The population of the positive and negative determination subregion be that net inflow state or net flow do well.
3. regional population's trend estimate method according to claim 2, which is characterized in that in the step T4, at the i moment
Change rate K be denoted as:
4. regional population's trend estimate method according to claim 2, which is characterized in that the step T5 is embodied as
Following steps:
Step T5.1: successively judge that the population of each subregion has arrived at the population threshold value of the subregion:
Step T5.2: when the population of the subregion has arrived at the population threshold value of the subregion, then the subregion is carried out pre-
It is alert；
Step T5.3: when the population of the subregion does not reach the population threshold value of the subregion, then to the subregion without pre-
It is alert.
5. regional population's trend estimate method according to claim 2, which is characterized in that the step T5 can also be specifically real
It applies as following steps:
Step T5.1: successively judge that the population of each subregion will reach the population threshold value of the subregion and the subregion
Population is also increasing:
Step T5.2: when the population that the population of the subregion will reach the population threshold value of the subregion and the subregion also exists
When increase, then early warning is carried out to the subregion；
Step T5.3: when the population that the population of the subregion will reach the population threshold value of the subregion and the subregion does not increase
Added-time, then to the subregion without early warning.
6. a kind of regional population's trend estimate system, which is characterized in that for implementing any one of claim 2-5 claim
Regional population's trend estimate method.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113642807A (en) * | 2021-09-01 | 2021-11-12 | 智慧足迹数据科技有限公司 | Population mobility prediction method and related device |
| CN116861197A (en) * | 2023-09-01 | 2023-10-10 | 北京融信数联科技有限公司 | Big data-based floating population monitoring method, system and storage medium |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106878952A (en) * | 2017-03-20 | 2017-06-20 | 上海迪爱斯通信设备有限公司 | The Forecasting Methodology and device of area people quantity |
| CN107301467A (en) * | 2017-04-11 | 2017-10-27 | 程在舒 | Chinese Future population number predicted method |
| CN107992958A (en) * | 2016-10-26 | 2018-05-04 | 航天信息股份有限公司 | Population super-limit prewarning method based on ARMA |
| CN109978249A (en) * | 2019-03-19 | 2019-07-05 | 广州大学 | Population spatial distribution method, system and medium based on two-zone model |
-
2019
- 2019-07-09 CN CN201910615714.6A patent/CN110472771A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107992958A (en) * | 2016-10-26 | 2018-05-04 | 航天信息股份有限公司 | Population super-limit prewarning method based on ARMA |
| CN106878952A (en) * | 2017-03-20 | 2017-06-20 | 上海迪爱斯通信设备有限公司 | The Forecasting Methodology and device of area people quantity |
| CN107301467A (en) * | 2017-04-11 | 2017-10-27 | 程在舒 | Chinese Future population number predicted method |
| CN109978249A (en) * | 2019-03-19 | 2019-07-05 | 广州大学 | Population spatial distribution method, system and medium based on two-zone model |
Non-Patent Citations (1)
| Title |
|---|
| 刘帅宾等: "基于人口流的中国省域城镇化空间关联特征及形成机制", 《地理学报》 * |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113642807A (en) * | 2021-09-01 | 2021-11-12 | 智慧足迹数据科技有限公司 | Population mobility prediction method and related device |
| CN113642807B (en) * | 2021-09-01 | 2022-04-12 | 智慧足迹数据科技有限公司 | Population mobility prediction method and related device |
| CN116861197A (en) * | 2023-09-01 | 2023-10-10 | 北京融信数联科技有限公司 | Big data-based floating population monitoring method, system and storage medium |
| CN116861197B (en) * | 2023-09-01 | 2024-04-05 | 北京融信数联科技有限公司 | Big data-based floating population monitoring method, system and storage medium |
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Application publication date: 20191119 |