35 results about "Socio economic data" patented technology

A system for providing a registered land asset includes a property transaction database in communication with a computer network the property transaction database provides information related to transactions associated with each registered land asset parcel, each land parcel having a registered land asset identifier representing global coordinates particular to the parcel. The system also includes a location characteristic database in communication with the computer network. The location characteristic database provides socioeconomic data regarding the location wherein the land parcel associated with the registered land asset is situated. A registered land asset contract may give a leaseholder an option to purchase the land by the end of a given term. A computer receives data from the property transaction database and the location characteristic database via the computer network and calculates prices and values associated with a registered land asset contract associated with the land parcel and a registered land asset contract is recorded in association with the land asset identifier corresponding to the land parcel in an electronic land title registry in communication with the computer network.

The invention discloses a mesh-based flood control command studying and judging system. The system comprises the steps that firstly, mesh generation is performed in an area under administration at first, meshed are adopted as units, and one or more water and rainfall condition information monitoring stations are arranged in each mesh; the water and rainfall condition information monitoring stations inside each mesh transmit current water and rainfall condition data to the system in real time; the water and rainfall condition data of the corresponding meshes is input into a hydrological prediction model for performing prediction analysis, and future rainfall predication data of each mesh is obtained; similarity analysis is performed through the flood control command studying and judging system, and historical water and rainfall condition data with the highest similarity with the current water and rainfall condition data inside the corresponding meshes is obtained; the current water and rainfall condition data, the historical water and rainfall condition data with the highest similarity with the current water and rainfall condition data and the future rainfall predication data of each mesh, socioeconomic data and basic level flood control system data are visually displayed in a GIS map through the flood control command studying and judging system. By mesh generation of the area under administration, the multiple meshes are formed, and the flood control early warning is more visualized.

The invention provides simulation prediction method for dynamic evolution simulation of urban greenbelt based on geo-cellular automata and multi-agent, which belongs to a technical field of geographic modeling and urban planning. Firstly, change data is obtained by overlay analysis and transition analysis of urban greenbelt thematic maps at two periods of time. Time and space configuration rules of the urban greenbelt are established by combining with a statistical model of urban greenbelt change and based on a multi-agent system theory, and a dynamic simulation model of the dynamic urban greenbelt is configured by adopting cellular automata; a logistic regression model is configured by combining with evolution of nature rules; parameters of the module according to social economic data are adjusted and reasonable expansion and transition rules are determined ; and a model builder toolset is established based on a powerful spatial modeling and analysis capability of GIS, by which simulation and prediction of the urban greenbelt change trend is carried out. The method in the invention realizes dynamic evolution simulation for the urban greenbelt, and is capable of providing assistant decision supports for making land use policy for government and city planners.

The invention discloses a statistical method and system for analyzing passenger flow characteristic information on the basis of a mobile communication terminal. The statistical method comprises the following steps: obtaining position information of the mobile communication terminal; performing historical accumulative counting on the position information of the mobile communication terminal to form a position information database; and according to population census and social and economical census data of areas under administration, provided by government departments at various levels, through combination with the position information database of the mobile communication terminal, analyzing the passenger flow statistical characteristic information of each area in corresponding time periods. According to the statistical method for analyzing the passenger flow characteristic information on the basis of the mobile communication terminal, acquired position information data is positioned by use of the mobile terminal and then statistical analysis of passenger flow information characteristics is performed through combination with the population census and social and economic data, such that the method is low in cost and high in accuracy, the sample quantity is large and is close to the quantity of total samples, and passenger flow statistical analysis of any one area in any period can be realized.

The invention provides a comprehensive evaluation method for a dengue risk. The method comprises the steps that dengue case data, mosquito-borne data, meteorological data, map data, environment factordata, social economy data, demography data and surrounding country or area epidemic situation data are collected; a basic risk value, a nearby risk value and a future prediction risk value are calculated, and weight coefficients of the three risk values are calculated; the comprehensive evaluation method is established, and a total dengue risk value is calculated; with reference to meteorologicaldisaster level early warning, the total risk value is evaluated for the dengue risk, and grading is conducted; based on a generalized addition model, a smooth function can be used for conducting non-linear processing on variables; the variables such as meteorological factors, dengue case numbers and mosquito-borne factors are comprehensively considered and comprise more information related to attack; in combination with the three risk values, a dengue risk evaluation model is established, the dengue spreading risk is identified at multiple angles, the influence of multiple factors on dengue spreading is comprehensively considered, and the accuracy of dengue risk evaluation is effectively improved.

The invention discloses a planning and site selection method and system for a freight airport. According to the method, a preset algorithm is adopted to obtain the regional air freight prediction quantity of a preset region on the basis of the social and economic data and air freight historical data of the preset region, so that the urban air freight prediction quantity of a target city in the preset region is determined; the optimal site coordinates of the target city are determined by adopting a gravity center method model according to the geographic coordinates of the target city and the corresponding city air freight prediction quantity; linear distances between the geographic coordinates of each candidate freight airport site and optimal site coordinates and each condition in preset freight airport planning and site selection basic conditions are weighted and scored; the comprehensive score of each candidate freight airport site is obtained; and the candidate freight airport sitewith the highest comprehensive score is determined as an optimal site for freight airport construction. With the method and system adopted, quantitative deep research on the planning and site selection of freight airports is realized, and the problem of insufficient research on the planning and site selection of the freight airports at the present stage is solved.

The invention provides a method for predicting county-level unit timing sequence GDP based on deep learning. The method comprises the steps that firstly, collecting and managing multi-source remote sensing data, county-level vector boundary data and annual county-level GDP data of a time sequence in a research area based on a GEE platform; then, performing data processing based on a GEE platform,providing a feature extraction method based on histogram statistics, packaging features into tensors needed by deep learning, and dividing the data into a training set and a verification set accordingto time; establishing a deep learning system structure based on a convolutional neural network, inputting the data feature tensor into the network, performing training by using historical data, and storing the trained model; and finally, inputting the verification actual data into the model to obtain a prediction result. According to the method provided by the invention, the prediction precisioncan be improved, the labor cost is saved, and related departments and governments can be helped to count accurate social and economic data, so that industrial assistance is provided in a targeted manner and policies are formulated.

The invention discloses a calculation and risk judgment method for a service dominance degree of a local ecological system. The calculation and risk judgment method comprises the following steps: on the research basis of service consumption of an ecological system, calculating ecological system service provided by ecological system functions in an area and corresponding service consumption essential for living of human beings inside the area, establishing a local ecological system service dominance degree model, taking the ecological system endurance capability and the sustainable developmentpotential into account, judging a service dominance degree threshold which can affect the risks of the ecological system by using a positive/negative bidirectional watershed algorithm, quantitativelypre-judging the risk degree of the ecological system, and performing degree quantitative analysis upon the ecological system service risk situations according to calculation results. The evaluation conclusions of ecological system service are highly related to natural environment data and social economic data of an evaluated area, reasonable utilization of local ecological resources is effectivelyinstructed, excessive consumption of ecological resources is warned in advance, and disordered damage of social economic activities to ecological environments is avoided.

The invention discloses a management object-oriented natural resource data fusion system. The natural resource data fusion system comprises a control module, a data classification module, a data bloodrelationship analysis module, a data use object analysis module, a spatial information comparison module, a spatial fusion module, an element materialization processing module, an element attribute fusion module and a service data fusion module. Wherein the control module is respectively connected with the data classification module, the data blood relationship analysis module, the data use object analysis module, the spatial information comparison module, the spatial fusion module, the element materialization processing module, the element attribute fusion module and the business data fusionmodule; firstly, natural resource management objects are sorted out, and existing natural resource current situation data, planning data, management data and social and economic data are divided intocurrent situation data, management unit data and business process data from the perspective of the natural resource management objects. According to the invention, the problem of multiple counting doors is solved, natural resource management is better served, and data fusion development is realized.

The invention provides a data processing method and device applied to industrial big data analysis. The method comprises the steps of capturing social economic data, enterprise data and industrial economic data within a preset capturing range, and converting the captured data into structured data; screening and processing the structured data to remove redundant data, and loading the data into a database; calling preset supplementary data to be added into the database; selecting out initial values corresponding to t three-level indexes of a to-be-evaluated area respectively from the database; converting the initial value of each three-level index into a utility value; performing addition on the utility values of all the three-level indexes to obtain a comprehensive score of the to-be-evaluated area; and according to the initial values of all the three-level indexes of the to-be-evaluated area, the utility values of all the three-level indexes, the comprehensive score of the to-be-evaluated area and historical data in the database, generating a data analysis report. The data analysis method and device has the advantages that the data range is more comprehensive, the data analysis ismore scientific, and the data analysis modes are more diversified.

The invention provides a method oriented to land utilization and traffic multi-scale simulation, and belongs to the technical field of urban planning. The method is characterized in that a macroscopic model is combined with a microscopic model on the basis of a land utilization and traffic integration theory, a system dynamics model theory, an irregular cellular automata model theory and a scenario planning theory, and urban social economic data is adopted, so that urban land evolution and traffic system evolution can be simulated. An aggregation result generated by the macroscopic model is applied to the allocation of the microscopic model in order to construct a model which has a system aspect, an individual aspect and macroscopic and microscopic features and is more accordant with the urban general development law and the people-oriented urban planning thought. A frontier research irregular cellular automata model in the neighborhood of an urban model is combined with a conventional traffic four-phase model in order to construct a microscopic land utilization and traffic integration model based on a specific evolution rule, so that different scenario planning can be analyzed and predicted more specifically.

The invention discloses a standard data-based agricultural pollution source in-water body load measuring and calculating method. The method comprises the following steps: acquiring rainfall, water quality, DEM, land utilization, soil texture, soil type and social economic data of a to-be-researched region; according to the hydrological data of the to-be-studied region, dividing the to-be-studied region into a plurality of drainage basin partitions; calculating a pollutant influence factor of each drainage basin partition; carrying out standardization treatment on the pollutant influence factors of each drainage basin subregion; calculating a water inlet body coefficient of each drainage basin partition according to the pollutant influence factors after standardization treatment; obtaining the discharge amount of agricultural source pollutants in the to-be-studied region, and calculating the water-entering load amount of the agricultural source pollutants; and selecting a specific drainage basin partition, and verifying the water inlet body load capacity obtained by calculation and an actual measurement result. The method can solve the problem that the prior art lacks a method for effectively calculating the load capacity of pollutants in a large-scale region in the water body, and is good in consistency, reliable in calculation and large in range.

The invention provides a carbon emission medium and long term prediction method based on social economic data. Comprising the following steps: (1) predicting a primary energy demand: firstly predicting a numerical value of future energy intensity by simulating a correlation between primary energy consumption in the previous year and actual GDP, industrial structure and industrial energy intensity, and then predicting the primary energy consumption in the future year according to the simulated correlation; (2) energy structure prediction: according to each energy consumption structure in the previous year, calculating the energy structure in each year in the future by using a Markov prediction method; the energy consumption in the future is obtained; (3) calculating the carbon dioxide emission by using the carbon dioxide formula estimation coefficient; and (4) carbon emission prediction: predicting the carbon emission in the future year in combination with the carbon dioxide emission coefficient and the energy consumption. According to the method, the carbon emission in the future year is obtained by predicting the primary energy consumption and the energy structure in the future year and combining the carbon emission estimation coefficient.

The invention discloses a social economy analysis and prediction method, belongs to the technical field of economics, and aims to solve the problems that a traditional economics prediction method is low in accuracy and single in the considered influence factor. The social economy analysis and prediction method comprises the steps: a, obtaining social economic data; b, performing spatial discretization on the macroeconomic data and the microeconomic data; c, determining an influence relationship between the macro-economic data and the micro-economic data on the social economy; d, comparing, auditing and analyzing reasons causing difference by combining the analysis results of the step b and the step c; and e, analyzing the economic fluctuation data finally obtained in the step d and the regional social and economic index distribution condition, simulating the future development trend of the social economy, obtaining a future social and economic development optimization scheme, and completing social and economic analysis and prediction. According to the social economic analysis and prediction method, the relative magnitude of the importance of all influence factors in a certain period can be relatively and accurately judged, and the prediction accuracy is improved.

The embodiment of the invention relates to a method for analyzing influence factors of doctor seeing of remote patients. The method comprises the following steps: acquiring case data, geographic element data and social economic data of the remote patients seeing a doctor in a target city; based on the case data, the geographic element data and the social economic data, determining a plurality of first influence factors of medical seeing of the remote patient; screening the plurality of first influence factors by using a multiple regression model to obtain a plurality of second influence factors; taking the doctor seeing rate of the patient flowing out of the prefecture-level city to the target city as a dependent variable, taking multiple second influence factors as independent variables, performing fitting analysis on the dependent variable and the independent variables by utilizing an OLS regression model, a GWR regression model and an MGWR regression model, and determining a target regression model with the highest fitting degree; and determining a target influence factor from the second influence factors based on the significance test variable of the target regression model so as to analyze the target influence factor. According to the technical scheme provided by the invention, the influence factor condition of medical treatment of the remote patient can be accurately analyzed.

The invention provides an environment quality prediction method based on social economic data, which establishes a quantitative coupling relation between economy and environment by introducing economic data with higher timeliness and more predictable trend. The method comprises the following steps: firstly, predicting the trend of economic data to obtain a next-period economic data predicted value; then, calculating a prediction result according to a certain pollutant emission coefficient, and superposing a policy factor on the basis to obtain a pollutant emission prediction value; and finally, calculating a corresponding environment quality predicted value through the pollutant emission predicted value. According to the method, the problems of poor data timeliness and insufficient prediction accuracy of an existing environment quality prediction method can be solved, the timeliness and prediction accuracy of environment quality prediction data are improved, and the ability and the level of an ecological environment department participating in macroscopic decision making are improved.

The invention relates to a method for determining a spatial interpolation model of cancer data. The method comprises the following steps: acquiring cancer data and related data of a to-be-analyzed area; the cancer data comprising cancer death rate data, the related data comprising basic geographic data, mining industry distribution data, social economic data, daily value meteorological data and PM2.5 pollution data, and the basic geographic data comprises village boundary vector data, road data, river data and topographic data; based on the cancer death rate data, the basic geographic data and the mining distribution data, determining the interpolation precision of the inverse distance weighting model, the interpolation precision of the trend surface analysis model and the interpolation precision of the common Kriging model; based on the cancer death rate data and the related data, determining the interpolation precision of the polynomial regression model and the interpolation precision of the collaborative Kriging model; and determining the model corresponding to the highest interpolation precision as an optimal spatial interpolation model. According to the scheme of the invention, the optimal cancer data spatial interpolation model can be rapidly determined, and the interpolation precision and the depicted data precision are improved.

The present disclosure pertains to a system configured to prepare and use prediction models for socioeconomic data and missing value prediction. Some embodiments may: extract, from received population segment data, a training set of socioeconomic parameter values for each population segment; provide, to a prediction model as input, first parameter values of the respective training set for the prediction of additional parameter values of the training set such that the prediction of the additional parameter values is performed without reliance on the additional parameter values; provide, for each of the training sets, the additional parameter values to the prediction model as reference feedback for the prediction model's prediction of the additional parameter values to train the prediction model; and predict, based on a working set of parameter values for a population segment, additional values for the working set using the prediction model subsequent to its training.

The invention relates to a mutation detecting method for an industrial agglomeration spatial pattern, comprising: firstly generating an industrial geospatial spatial factor field and establishing an industrial geospatial and related social economic database; secondly introducing a Ripley's K function of the spatial point pattern analysis method to quantitatively estimate the Ripley's K function value of the industrial agglomeration spatial pattern; then using the L function to normalize the Ripley's K function value, and further acquiring the multi-scale spatial pattern marginal L function value sequence of the industrial geospatial or industrial economic layout; and finally determining the spatial pattern mutation point and mutation position of the industrial geospatial or economic layoutby the mutation detection for the spatial pattern marginal L function value sequence of the industrial geospatial or economic layout by using the Mann-Kendall change point analysis method in mathematical statistics. The invention is capable of effectively revealing the range of spatial spillover effects of industrial agglomeration while acquiring the changing characteristics of the industrial agglomeration spatial pattern.