A Multi-gene Genetic Programming Fuzzy Inference System for Regression Problems
Adriano Koshiyama, Marley M. B. R. Vellasco, Ricardo Tanscheit · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2015
This work presents a novel Genetic Fuzzy System (GFS), called Genetic Programming Fuzzy Inference System for Regression problems (GPFIS-Regress).It makes use of Multi-Gene Genetic Programming to build the premises of fuzzy rules, including t-norms, negation and linguistic hedge operators.GPFIS-Regress also defines a consequent term that is more compatible with a given premise and makes use of aggregation operators to weigh fuzzy rules in accordance with their influence on the problem.The system has been applied to a set of benchmarks and has also been compared to other GFSs, showing competitive results in terms of accuracy and interpretability.