- author = "Adriano S. Koshiyama and Marley M. B. R. Vellasco and Ricardo Tanscheit",
- booktitle = "2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)",
- title = "Development of a fuzzy rule-based system using Genetic Programming for Forecasting problems",
- year = "2015",
- abstract = "This work presents a novel genetic fuzzy system for forecasting, called Genetic Programming Fuzzy Inference System for Forecasting problems (GPFIS-Forecast), which generates an interpretable fuzzy rule base by using Multi-Gene Genetic Programming to define the premises terms of fuzzy rules. The main differences between GPFIS-Forecast and other genetic fuzzy systems lie in its fuzzy inference process, because it: (i) enables premises to be include negation, t-conorm and linguistic hedge operators; (ii) applies methods to define a consequent term more compatible with a given premise; and (iii) makes use of aggregation operators to weigh fuzzy rules in accordance with their influence on the problem. GPFIS-Forecast has been tested in the NN3 Competition, in order to evaluate its performance in a benchmark problem. In this case, it has produced competitive results when compared to other forecasting approaches.",
- keywords = "genetic algorithms, genetic programming",
-
DOI = "
doi:10.1109/FUZZ-IEEE.2015.7338037",
- month = aug,
-
notes = "Dept. of Electr. Eng., Pontifical Catholic Univ. of
Rio de Janeiro, Rio de Janeiro, Brazil
Also known as \cite{7338037}",
