关键词: 空间模糊聚类, 精准农业, 土壤肥力评价, 属性加权

Abstract:

【Objective】 As a traditional fuzzy clustering algorithm has its shortages, an improved algorithm was presented in the paper. 【Method】 First, access to the weighted value of each attribute using AHP, and then add weighted value to the spatial fuzzy dynamic clustering algorithm, finally, use F- distribution of probability statistics to determine the best classification number in order to improve the algorithm intelligence. 【Result】 The weighted spaces fuzzy dynamic cluster algorithm was compared with the fuzzy equivalent relations transitive closure algorithm, the result shows that F-value is the largest and the classification results is best when λ=0.993. This time, the weighted F- value is 4.898, unweighted F- value is 2.957, that shows the weighted gap between class are more obvious that unweighted one, that is, the accuracy of the clustering algorithm is significantly higher than unweighted fuzzy clustering algorithm. 【Conclusion】 Tests show that the clustering algorithm’s accurate rate is higher than the unweighted fuzzy clustering algorithm.

Key words: space fuzzy clustering algorithm, precision agriculture, evaluation of soil fertility, attribute weights