Spatial Analysis Model for Estimation of Population and Other Census Data in India for Forecasts in Demographic, Social and Economic Arena

A. Krishna
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引用次数: 2

Abstract

In general, Population and other forms of data for different states and times in India are taken from census data which will be taken for every 10 years. This data may have spatial autocorrelation which is characterized by a correlation in a signal among nearby locations in space. Spatial autocorrelation is more complex than onedimensional autocorrelation because spatial correlation is multi-dimensional and multi-directional. Thus in this work a model is being used to study population data for its spatial and temporal characteristics. Before the model being considered, the data will be initially studied for its relevance in spatial analysis problem. Once the problem is satisfied for its spatial autocorrelation characteristics, the model is used to generate coefficients from available census data, which will be used to generate data within 10 years span and for future predictions.
用于人口、社会和经济领域预测的印度人口估算和其他普查数据的空间分析模型
一般来说,印度不同邦和时间的人口和其他形式的数据来自每10年一次的人口普查数据。这种数据可能具有空间自相关,其特征是信号在空间中邻近位置之间具有相关性。空间自相关比一维自相关更为复杂,因为空间相关是多维、多向的。因此,在这项工作中,正在使用一个模型来研究人口数据的空间和时间特征。在考虑模型之前,将对数据在空间分析问题中的相关性进行初步研究。一旦问题的空间自相关特征得到满足,该模型就会从现有的人口普查数据中生成系数,这些系数将用于生成10年内的数据和未来的预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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