RETRACTED: Environmental data analysis based on fuzzy clustering method

Abstract

With the growing complexity of the human living environment, the environment-related industries have also been flourishing. Clustering of environmental data is a key task of environment research. The environmental data are characterized by diversification, boundary fuzzification, incompleteness, etc. This paper conducts a cluster analysis of environmental data based on fuzzy theory. To start with, the basic principle of fuzzy theory is analyzed, and the focus is on studying the membership function and the [Formula: see text]-cut-set knowledge. Following that, the fuzzy clustering method and its process are studied. Finally, fuzzy evaluation is used to build the membership function after experiment on the MATLAB platform to evaluate the environmental quality. The fuzzy C-means clustering algorithm is used to realize the target identification of environmental data. In the process of fuzzy clustering, fuzzy evaluation of the seawater quality is realized, and the redundant data of the monitoring station are removed. Through experiment and analysis, experimental results are in line with the practical situations and show a high consistency with the data characteristics. Compared with the traditional clustering algorithm, fuzzy clustering is more suitable for environmental data processing in environmental data research and analysis.