The Soft Sets and Fuzzy Sets Based Neural Networks and Application

Zhicai Liu, Zhicai Liu, Jose Carlos R. Alcantud, Keyun Qin, Ling Xiong
2020 IEEE Access  
This paper reviews and compares theories of fuzzy sets and soft sets from the perspective of transformation, and a machine learning model-SF-ANN (the soft sets and fuzzy sets based artificial neural network ) is proposed. Liu et al. proved that every fuzzy set on a universe U can be considered as a soft set, and show that any soft set can be regarded as even a fuzzy set. Inspired by this idea, we construct a neuronlike structure based on soft sets and fuzzy sets, and we get a more practical
more » ... y learning model-SF-ANN. In practical applications, it can be used as a general methodology for establishing the membership function of fuzzy sets, and it also can be applied to pattern recognition, decision-making, etc. In general, it provides a new perspective to observe the relationship between soft sets and fuzzy sets, and it is easy to relate soft set theory and fuzzy set theory to machine learning methods. To a certain extent, it reveals that the research of fuzzy sets and artificial neural networks do lead to the same destination. INDEX TERMS Fuzzy sets, soft sets, neural networks.
doi:10.1109/access.2020.2976731 fatcat:lpti3wka6rgjhf6d6kamj46sem