41 results about "Human population distribution" patented technology

The invention aims at providing a method for collecting spatial population distribution in real time on the basis of mobile phone big data and realizing large passenger flow early warning. The method is characterized by comprising the following steps of obtaining real-time mobile phone big data from a mobile phone communication operator at each statistics moment; dividing a target region into different space regions; at the current statistics moment, mapping the latest space position of each EPID (Electronic Portal Imaging Device) obtained in the first step to each space region of the target region; and obtaining the real population size (the distribution condition of the total population in the whole target region) in each space region at the current statistics moment. The method has the advantages that the sufficient relying on the existing mobile phone big data resources is realized; the continuous encrypted position information of the existing mass anonymous mobile phone users in the mobile communication network is used; the low-cost high-frequency and automatic implementation can be realized; and the popularization distribution data in a large-range urban space range can be continuously obtained in a fast deploying way.

The invention discloses a demographic method and a demographic system for improving spatial resolution and updating a speed, wherein the method comprises a population database establishment step, a regional statistical analysis step, a spatial model analysis step and a grid demographic step, wherein the population database establishment step is used for storing relevant population data with a uniform spatial coordinate parameter, a data format and a metadata standard; the regional statistical analysis step is used for using a land utilization map as a main data source and carrying out spatial region statistical analysis according to a preset region to obtain land utilization area information of a minimal administrative division unit of the preset region; the spatial model analysis step is used for utilizing a population spatialization model to obtain population distribution information of the land utilization type in the minimal administrative division unit according to the land utilization area information of the minimal administrative division unit and demographic information of the minimal administrative division unit, and the grid demographic step is used for acquiring grid demographic information according to the population distribution information of the land utilization type and the land utilization area information.

The present application relates to a traffic fusion analytical prediction method and system and an electronic device. The method includes the following steps of a: acquiring vehicle data information by using a fixed-point electronic photographing device in combination with a mobile intelligent information acquisition device, and acquiring mobile phone signaling data; b: separately extracting vehicle OD data and user OD data according to the vehicle data information and the mobile phone signaling data; c: constructing a network topological graph according to the vehicle OD data and the user OD data, and performing a space-time convolution operation on the network topological graph with space-time correlation by using a deep learning model based on a space-time diagram convolution network to establish traffic flow prediction model; and d: predicting a traffic flow and population distribution through the traffic flow prediction model. The method tracks and identifies the vehicle by means of the fixed-point electronic photographing device and the mobile intelligent information acquisition device, compensates for the limitation of video tracking fixed point identification and provides decision support for traffic control and induction in key areas.

The invention discloses a random forest model-based population data spatialization method. According to the method, population distribution-related variable factors such as surface coverage data and lamp light data are selected; the population distribution-related variable factors are pre-processed, and the pre-processed population distribution-related variable factors are inputted into a random forest model; the relationship between population density and the variable factors, and the importance of the variable factors are determined through using the random forest model; the population density of each grid is obtained through inversion based on the relationship; and an estimation result is corrected through regional density charting, so that a gridded population distribution result can be obtained. With the method adopted, the precision of population data spatialization can be further improved, and the importance of the variable factors are interpreted.

The invention discloses an ODN line distribution management method and system based on a GIS platform. The method includes the steps that through the GIS platform, resource information of an ODN deployment region is collected, and ODN equipment model information and existing station and machine room information are input; according to the resource information, the future population distribution trend and service growth condition of the ODN deployment region and the existing station and machine room information, ODN structure planning is automatically performed, and corresponding ODN equipment is automatically selected to generate the optimal ODN layout distribution. Based on the GIS platform, through inputting a GIS map and existing network stock resources, region division, station selection, equipment model selection, optical cable routing designing, civil designing, optical cable layout and other designing operation are completed on the GIS map, an optical cable routing map, an equipment terminal and fiber core distribution diagram and other series design files and a material and service fee list can be output, in this way, the efficiency of planning designing is greatly improved, and the probability of manual errors is lowered.

The invention discloses an energy-saving environment monitoring system. The system comprises a control center, an air conditioner, a fan, an indoor and outdoor temperature sensor, an indoor and outdoor humidity sensor and an indoor and outdoor ventilation unit, wherein the control center reads four environment factor codes of a dial switch, determines start-stop time of day and night according to real-time date and time and a time zone code, determines start-stop time of a strict monitoring mode and a loose monitoring mode in every 24-hour period according to a population distribution type code and the start-stop time of day and night, determines environment factor control threshold ranges in the strict monitoring mode and the loose monitoring mode according to a geomorphic type code, and is used for controlling the indoor and outdoor ventilation unit according to an indoor and outdoor heat exchange ventilation opening enable code and controlling the air conditioner and the fan according to the environment factor control threshold ranges and data acquired by the indoor and outdoor temperature sensor and the indoor and outdoor humidity sensor. Compared with the conventional scheme, the technical scheme has the advantage that: an energy-saving effect can be further achieved.

The invention provides a population distribution statistical method and device, and relates to the technical field of population distribution, and the method comprises the steps: obtaining personnel data in a building distribution map coverage area according to a preset sampling period; and according to the geographic position of each person identifier and the position coordinate of each building,counting the number of persons corresponding to each building in the current sampling period so as to count the population distribution of the building. According to the mode that the personnel dataare obtained according to the preset sampling period and the personnel number in the building at the current moment is counted through the personnel data, the personnel condition in the building can be accurately and rapidly obtained, the personnel counting efficiency is improved, and meanwhile the labor cost is saved. And meanwhile, personnel distribution related guidance suggestions are providedfor input hardware and software equipment by a third-party mechanism, so that hardware and software resources can be reasonably distributed based on the quantity of personnel, and reasonable utilization of the resources is ensured. The method is wide in application range and has good applicability.

The invention discloses a medical-deficient area identification method based on multi-level medical resource balance. The method comprises the steps of S1, collecting data; S2, establishing a logic framework for 2R grid-hierarchy method; S3, completing permanent resident population data gridding based on administrative unit permanent resident population data and night light image data; S4, calculating the accessibility of the medical space; S5, carrying out multi-level medical resource space superposition and medical-deficient area identification to obtain the spatial accessibility range of medical resources of each level of the research area, and forming a multi-level medical resource space; superposing the multi-level medical resource space layers by utilizing GIS space superposition analysis to obtain a multi-level medical resource space balance distribution diagram of the research area, and identifying the type and the space pattern of the medical-deficient area; and subjecting thegrid distribution diagram of the permanent resident population and the multi-level medical resource space balance distribution diagram to superposition analysis, so that the population distribution and aggregation conditions of the medical-deficient area are accurately identified, and policy suggestions and scientific references are provided for urban public medical resource planning.

The invention is suitable for the field of information technology and provides an evaluation method and system for a village and town area livable benchmark test. The evaluation method for the village and town area livable benchmark test comprises the steps that an evaluation index system is determined, the evaluation index system includes 33 evaluation indexes, and the 33 evaluation indexes relate to five levels of social economy, environment ecology, infrastructure construction, a public service and built environment; distribution information of county territory population and village and town population is determined according to recorded village and town area basic information; a sample capacity of questionnaires is determined according to selected precision and the distribution information of the county territory population and the village and town population, and the questionnaires are designed according to the evaluation indexes included in the evaluation index system; the index total points of a town level and a village level are determined and output according to the recorded questionnaire result information. The evaluation method and system for the village and town area livable benchmark test has the advantages that compared with an existing evaluation method for the village and town area livable benchmark test, the selected livable indexes are more comprehensive, and the livable level of the town area or the village area can be reflected from different views and different targets.

The invention discloses a big data-based unemployed population dynamic monitoring method. The method comprises the following steps of constructing massive individual travel tracks according to time-space record data of individuals; by training prior samples, performing learning to obtain a boundary of unemployed and employed populations in a daily travel mode feature; based on this, identifying all the samples, and judging a current employment state; updating the data in real time, monitoring and updating employment conditions of all the samples, and calculating a ratio of the unemployed population to the samples; and expanding the samples to obtain an unemployed population distribution condition of the whole society in two dimensions of time and space and a statistical result of the unemployed population distribution condition. The method has the advantage that the statistics of real-time unemployed population and unemployment rate in a region can be carried out conveniently and efficiently.

A communication system aimed at easily and quickly collecting data regarding macroscopic population distribution, and easily and quickly obtaining survey results. An RNC of a communication system includes a signal-counting module that counts the number of signals indicating a quantity of signals transmitted and received between a mobile station and a BTS. An information analysis device includes a population distribution calculation module that calculates population distribution based on the number of the signals that the signal-counting module counts, and an output module that outputs the population distribution that the population distribution calculation module calculates.

The invention relates to the technical field of POI big data processing, in particular to a population data spatialization method, device and equipment based on multi-source information fusion, and the method comprises the steps: obtaining night light data, urban POI data and population data of a research region, dividing a spatial distribution grid in the research region according to a preset rule, and building a population data spatialization model with sub-population data as a dependent variable, wherein the sub night light data is a multivariate linear regression model of independent variables; according to a multivariate linear regression model taking the sub night light data as an independent variable, determining an initial estimated value of population distribution of each spatialdistribution grid according to the multivariate linear regression model, taking the sub population data of the administrative region as a constraint condition to correct the initial estimated value ofthe spatial distribution grid in the administrative region, and determining a population prediction value. According to the method, night light data and POI data are combined, a regression analysis model is constructed according to demographic data, demographic spatial modeling is carried out, demographic spatial distribution simulation and prediction are realized, the data has no hysteresis quality, and the model accuracy is relatively high.

The invention provides a method for controlling a time length of a traffic light according to a population distribution thermodynamic diagram. The method comprises the following steps: step 1, obtaining a map with a plurality of traffic light locations within a region location; step 2, obtaining a real-time population distribution thermodynamic diagram corresponding to the map; step 3, matching aroad corresponding to the traffic light with the real-time population distribution thermodynamic diagram to obtain the real-time population distribution thermodynamic diagram corresponding to the traffic light road; and step 4, adjusting the time length of the traffic light according to the congestion rate of the road facing the traffic light. The road congestion rate is combined with the real-time population distribution thermodynamic diagram, so that the calculation of the road congestion rate is more accurate, the calculation amount is smaller, and data can be obtained in real time and analyzed easily.

The embodiment of the invention discloses a method, device and apparatus for displaying population data. The scheme comprises the steps of obtaining population data information, wherein the populationdata information at least comprises position information; screening out the population data information of which the position information is located in the first region to form a population data set;obtaining an analysis result according to the population data information in the population data set, wherein the analysis result comprises population quantity, population distribution or populationmigration; and displaying the analysis result at a position corresponding to the first region on a 3D map. According to the embodiment of the invention, the 3D map and the population data are combinedfor improving the intuitiveness and interactivity of population data display, and a user can conveniently, intuitively, accurately and efficiently manage the population data.

The invention relates to the technical field of infectious disease prevention and control, and discloses an infectious disease time-space diffusion evolution and artificial prevention and control simulation method based on discrete grids. The method specifically comprises the following steps: performing population distribution and population division in a region, constructing an infectious disease space-time diffusion model, and constructing an artificial prevention and control measure model. The invention provides an infectious disease epidemic situation space-time diffusion and artificial prevention and control measure simulation method under a discrete grid. Aiming at the problems that an existing artificial prevention and control measure simulation method is less in integration of space-time information and model parameters lack description of space-time evolution, a time sequence-based infectious disease model is combined with geography, a geographic area is divided by utilizing discrete grids, and a space-time diffusion model of infectious diseases is designed according to correlation between patients and the grids. Meanwhile, an intervention measure model is mapped to a corresponding grid, so that a simulation model can correspond to an actual geographic space while quantitative analysis is carried out by utilizing an infectious disease model.

The invention provides a population space partition fitting method based on multi-source data, and aims to solve the problems that the spatial resolution is low and the spatial resolution of population distribution cannot be depicted finely when administrative units such as streets, towns and villages are used as division boundaries for statistical population data. The invention provides a population space partition fitting method based on multi-source data. In order to improve the precision of population spatialization and comprehensively consider the heterogeneity of space, various high-precision novel data such as Esri10m land coverage, NPP / VIIRS-like night light, Gade POI and Qipu village and town population are selected, population influence factors of each district and county are counted to serve as model independent variables, population spatialization is performed on a 1km grid through a geographically weighted regression model, and the population spatialization accuracy is improved. Performing precision evaluation on the result; and counting counties which do not meet the precision requirement, and carrying out secondary zoning and spatialization again. A population space partition fitting method is adopted, the overall precision of a research area is obviously improved, and reference can be provided for population spatialization research.

The invention discloses a fine population analysis unit division method based on an urban form and a population convergence mode, and the method comprises the following steps: S1, considering the spatial structure of the urban and the fine-grained demand of population analysis, facing the functional heterogeneity of a micro-scale population activity area, fitting the natural form of the urban, and dividing basic analysis units; s2, constructing a population convergence preference model by considering spatial distribution characteristics of urban population flow in local convergence and long-term stable characteristics depending on dynamic changes of entrances and exits; and S3, according to the microstructure elements in the basic analysis unit, dividing an FPAZ (Fine Population Analysis Zone) suitable for expressing and analyzing population distribution and change characteristics. According to the method, the FPAZ suitable for expressing the population distribution and change characteristics is divided based on the urban form elements and the population convergence preference model by considering the urban form characteristics and the population convergence mode, analysis and mining of the population distribution and change spatio-temporal mode are facilitated, and fine management of urban population is further supported.

The invention discloses a population distribution prediction method based on physical space and social network space interaction, and the method comprises the steps: obtaining historical fine space-time scale population data, and carrying out the preprocessing of the historical fine space-time scale population data, and obtaining preprocessed data; generating a space interaction fusion matrix according to the preprocessed data; generating a population distribution prediction model according to the spatial interaction fusion matrix; and obtaining population distribution prediction data according to the population distribution prediction model. According to the population distribution prediction method provided by the embodiment of the invention, the interaction between the physical space and the social network space is considered at the same time, and the fine space-time scale population distribution data can be predicted more accurately.

The invention discloses a method and a system for predicting future population fine spatial distribution and a computer readable storage medium. According to the method, on one hand, the population scale is predicted, and on the other hand, a to-be-predicted area is subjected to research area division, a population spatialization model is constructed by combining a weight value of a population distribution indicative factor and a simulated land utilization type, and a predicted population scale is input into the population spatialization model to obtain future population fine spatial distribution, so that the problem of coupling of a population prediction method and the population spatialization model is solved, and the future population fine spatial distribution is predicted.

The invention discloses an environmental risk assessment method and device based on population distribution, and computer equipment, relates to the field of information processing, and can solve the technical problem that current environmental risk assessment is inaccurate and unreasonable. The method comprises the following steps: acquiring regional sample data in a preset region, and training a population distribution prediction model by using the regional sample data; extracting first feature data in the target area, inputting the first feature data into the trained population distribution prediction model, obtaining a prediction result corresponding to second feature data, the first feature data at least comprise night light data, a normalized vegetation index, data elevation model data, a slope, an interest point and insurance data, and the prediction result corresponds to the second feature data, the second feature data comprise population distribution data; and determining pollutant concentration data in the target area, and performing data overlay analysis on the population distribution data and the pollutant concentration data to obtain an environmental risk assessment result.

The invention discloses a method and system for configuring vaccine resources. By obtaining information on the division of administrative planning areas of a city, data on population distribution of urban residents, and geographical location information of places that meet vaccine distribution qualifications; according to the administrative planning areas of the places, Geographical location information and the population distribution data in the said place, divide each place into regions; according to the principle of the shortest travel distance and the highest popularity index of the place, build a revenue evaluation model; combine the location information of each place and its popularity index Substituting into the income evaluation model to screen out vaccine distribution sites; and allocate vaccine resources according to the screened out vaccine distribution sites. The method and system disclosed in the present invention can select as few places far away from each other as possible, cover as many living places as possible, and realize balanced distribution of vaccine resources under the premise of resource optimization allocation.

The invention discloses a hospitalizing recommendation method based on multi-source data analysis. The hospitalizing recommendation method includes registering information of medical and health organizations in a community through a network; collecting hospitalizing item information and location information of users, and sending hospitalizing recommendation requests; according to the hospitalizing recommendation requests, performing multi-source data fusion according to information of the medical and health organizations, current population distribution densities of the medical and health organizations and the location information of the users to acquire possibilities that the medical and health organizations are selected by the users within a certain time period; ranking the medical and health organizations according to values of the selection possibilities; releasing the top ten of the medical and health organizations and the geographical locations of the users by calling a map application programming interface; navigating according to routes of the medical and health organizations finally selected by the users on a map. The hospitalizing recommendation method achieves real-time hospitalizing recommendation, and provides the users with hospitalizing recommendations more suitable for users' needs and convenient navigation services.

The invention discloses a method and system for determining the size of a population distribution grid. The method includes: acquiring luminous remote sensing data, performing first preprocessing on the luminous remote sensing data to generate luminous remote sensing pattern spots; acquiring land cover data, and performing the first preprocessing on the luminous remote sensing data; The second preprocessing is performed on the land cover data to generate the map spots of building construction areas at all levels; the luminous remote sensing map spots and the map spots of the building construction areas at all levels are intersected and superimposed to generate the overlapping area of ​​map spots; based on the The grid scale of population distribution is calculated by the intersection area of ​​map spots. This method realizes the determination of the population grid scale in the study area without using population data.

The invention discloses a multi-model fusion-based population distribution estimation method and device, and a storage medium. The method comprises the following steps of dividing a population distribution estimation region into a plurality of geographic units; obtaining a population distribution influence factor of each geographic unit; generating a first-order adjacency matrix based on the adjacency relation between the geographic units, and generating the multi-source spatial representation data of each geographic unit according to the population distribution influence factor of each geographic unit and the first-order adjacency matrix of each geographic unit; respectively taking the multi-source spatial representation data of each geographic unit and the population distribution influence factor as the input of a preset population distribution estimation model, and respectively outputting a population estimation value of each geographic unit by the population distribution estimation model, wherein the population distribution estimation model comprises a space matrix feature coding model, a global attribute feature coding model, a data fusion model and a classifier model. According to the method, the spatial information and the attribute information are considered, and a very good population distribution estimation effect can be obtained.

The invention discloses an energy-saving environment monitoring system. The system comprises a control center, an air conditioner, a fan, an indoor and outdoor temperature sensor, an indoor and outdoor humidity sensor and an indoor and outdoor ventilation unit, wherein the control center reads four environment factor codes of a dial switch, determines start-stop time of day and night according to real-time date and time and a time zone code, determines start-stop time of a strict monitoring mode and a loose monitoring mode in every 24-hour period according to a population distribution type code and the start-stop time of day and night, determines environment factor control threshold ranges in the strict monitoring mode and the loose monitoring mode according to a geomorphic type code, and is used for controlling the indoor and outdoor ventilation unit according to an indoor and outdoor heat exchange ventilation opening enable code and controlling the air conditioner and the fan according to the environment factor control threshold ranges and data acquired by the indoor and outdoor temperature sensor and the indoor and outdoor humidity sensor. Compared with the conventional scheme, the technical scheme has the advantage that: an energy-saving effect can be further achieved.

For easily and quickly collecting data regarding macroscopic population distribution, and easily and quickly obtaining the survey results, an RNC includes: a location registration signal receiver that receives location registration signals, and a signal number counting module that counts the number of the location registration signals for each sector, and an information analyzing apparatus includes: a population distribution calculation module that calculates population distribution information based on the number of the location registration signals; and an output module that outputs the population distribution information.

The invention provides a construction method of a population distribution prediction model, and belongs to the technical field of Internet. The method comprises the steps of optimizing a learning rate of each learning task and a parameter value of each model parameter based on a parameter value of each intermediate state in an optimization process of each model parameter, and obtaining an optimized learning rate of each learning task and an optimized parameter value of each model parameter; and adjusting the optimized parameter values of the model parameters based on the optimized learning rate of the target learning task to obtain a population distribution prediction model. According to the invention, meta-training is carried out based on the initial value of each model parameter and the initial learning rate of each learning task, the parameter value of the optimized model parameter containing meta-knowledge and the learning rate of the optimized learning task are obtained, and then the parameter value of the optimized model parameter is finely adjusted according to the learning rate of the optimized target learning task, so that the learning efficiency of the target learning task is improved. Therefore, a relatively accurate population distribution prediction model is constructed based on a small number of population prediction samples.