A scalable evolutionary linguistic fuzzy system with adaptive defuzzification in big data
Antonio A. Márquez, Francisco A. Márquez, Antonio Peregrín · 2017
This work deals with the design of scalable methodologies to build the Rule Bases of Linguistic Fuzzy Rule Based Systems from examples for Fuzzy Regression in Big Data environments. We propose a distributed MapReduce model based on the use of an adaptation of a classic data driven method followed by an Evolutionary Adaptive Defuzzification to increase the accuracy of the final fuzzy model.