空间数据挖掘方法在人口统计数据分析中的应用

K. Kurowska, Ewa Kietlińska, Hubert Kryszk
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引用次数: 1

摘要

在私营和公共部门机构中进行数据挖掘的主要目的是处理和分析数据,以便为决策产生可靠的信息。决策绩效取决于相关数据的可用性和用户将这些数据用于分析目的的能力。由于所分析因素的复杂性、它们随时间的变化以及它们与空间结构的相关性,空间统计工具的普及程度正在上升。根据空间规划过程的需要,应在人口分析中应用流行的模型。高分辨率的数据和精确的分析工具的可用性提高了空间分析的价值,所描述的模型可以普遍应用于支持决策过程。这项研究的目的是提出在规划过程中分析人口数据所选择的空间统计模型的适用性,并确定这些模型的主要优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Possibilities Use to Selected Methods of Spatial Data Mining in Demographic Data Analytics
The main purpose of data mining in private and public sector institutions is to process and analyse data with the aim of generating reliable information for decision-making. Decision-making performance is determined by the availability of the relevant data and the user’s ability to adapt that data for analytical purposes. The popularity of spatial statistical tools is on the rise owing to the complexity of the analysed factors, their variation over time and their correlations with the spatial structure. Popular models should be applied in demographic analyses for the needs of the spatial planning process. The availability of high-resolution data and accurate analytical tools enhances the value of spatial analyses, and the described models can be universally applied to support the decision-making process. The aim of this study was to present the applicability of selected spatial statistical models for analysing demographic data in the planning process and to identify the main advantages of these models.
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