An improved fast fuzzy c-means using crow search optimization algorithm for crop identification in agricultural
作者：
Highlights：
• An improved FFCM clustering algorithm based on CSA is proposed for PA.
• CSA-FFCM is able to avoid difficulties in the identification of vegetation.
• The aim of CSA is to find best cluster centroids and avoids stuck in local minima.
• CSA has strong ability of the global optimization with fewer parameters.
• The proposed approach obtains better results in comparison with other methods.
摘要
•An improved FFCM clustering algorithm based on CSA is proposed for PA.•CSA-FFCM is able to avoid difficulties in the identification of vegetation.•The aim of CSA is to find best cluster centroids and avoids stuck in local minima.•CSA has strong ability of the global optimization with fewer parameters.•The proposed approach obtains better results in comparison with other methods.
论文关键词：
论文评审过程：Received 21 February 2018, Revised 22 July 2018, Accepted 5 October 2018, Available online 13 October 2018, Version of Record 18 October 2018.
论文官网地址：https://doi.org/10.1016/j.eswa.2018.10.009
