Abstract
Fuzzy systems are used in modeling and implementation of many real-world applications operating under an imprecise and uncertain environment. Such systems have effective learning and reasoning capabilities. By integration ML techniques, the fuzzy systems can work with better performance. The paper is a review on the application of the different types of machine learning techniques into fuzzy systems. Many research outcomes are extracted in the hybridization zone of the fuzzy systems and machine learning. The advantages and future scope are also discussed on the mutual integration of fuzzy systems and machine learning techniques.
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Prasad, R., Shukla, P.K. (2022). A Review on the Hybridization of Fuzzy Systems and Machine Learning Techniques. In: Bansal, J.C., Engelbrecht, A., Shukla, P.K. (eds) Computer Vision and Robotics. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-8225-4_32
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