Pham Huy Thong1,2,3, Florentin Smarandache4, Phung The Huan5, Tran Manh Tuan6, Tran Thi Ngan6,*, Vu Duc Thai5, Nguyen Long Giang2, Le Hoang Son3
Computer Systems Science and Engineering, Vol.46, No.2, pp. 1981-1997, 2023, DOI:10.32604/csse.2023.035692
Abstract Clustering is a crucial method for deciphering data structure and producing new information. Due to its significance in revealing fundamental connections between the human brain and events, it is essential to utilize clustering for cognitive research. Dealing with noisy data caused by inaccurate synthesis from several sources or misleading data production processes is one of the most intriguing clustering difficulties. Noisy data can lead to incorrect object recognition and inference. This research aims to innovate a novel clustering approach, named Picture-Neutrosophic Trusted Safe Semi-Supervised Fuzzy Clustering (PNTS3FCM), to solve the clustering problem with noisy data using neutral and refusal degrees… More >
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