Zoning Agricultural Water Resources Utilization Based on Principal Component Analysis and Fuzzy C-Means Clustering Algorithm
Abstract：Quantization partition can be done in Hilly Ground of Middle Sichuan using the method of principal component analysis and fuzzy C-means clustering algorithm,according to partitioning index system（quantitative indicators 16,qualitative indicators 4） of agricultural water resources utilization selecting and building in the light of the key elements of agricultural eco-system environment ＂Water-hydrological cycle-environmental changes＂,water resource properties and content of efficient use of water resources and Productivityproductivity,land use,planting structure and scale cultivation etc.The results of the partition shows that the quantization partition in Hilly Ground of Middle Sichuan has reasonable partitioning indicators,properly partitioning method and reliable partition results,providing a strong comprehensive planning guidance and reference to the arid area in southern seasonal agricultural water resources utilization.
Keywords：agricultural water resourcesefficient usezoningprincipal component analysisfuzzy C-means clustering algorithm
Publication Date：2011-01-01
Online Publishing Date：2026-09-12(First online date of this platform, not the publication date of the document)