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Issue title: Special issue: Fuzzy Systems in Distributed Sensing Applications
Guest editors: Mohamed Elhoseny and X. Yuan
Article type: Research Article
Authors: Si, Haiping | Sun, Changxia | Qiao, Hongbo | Li, Yanling; *
Affiliations: College of Information and Management Science, Henan Agricultural University, Zhengzhou, China
Correspondence: [*] Corresponding author. Yanling Li, College of Information and Management Science, Henan Agricultural University, 450002 Zhengzhou, China. E-mail: haiping@henau.edu.cn.
Abstract: At this stage, with the continuous development of data acquisition technology, the mining of high-dimensional spatial data has become a hot issue. And so on. The spatial data mining component studied in this paper is part of the spatiotemporal data middleware. The main research result is to propose a density-based and grid-based extended adjacent spatial clustering method and apply this method to the space for agricultural informatition. In data mining, we also used the middleware technology to complete the agricultural geographic information system based on MapXtreme, and applied the spatial data mining for agricultural informatization to develop the middleware of agricultural variety division, which solved the agricultural informatization. The practical application is of our country.
Keywords: Data mining, WebGIS, agricultural informatization, middleware, multidimensional space
DOI: 10.3233/JIFS-179499
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 2, pp. 1359-1369, 2020
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