Thanks in advance. You encounter innumerable problems which are difficult to solve using traditional modeling techniques.
Applications range from mathematics and engineering sciences to medicine and political sciences.
GAs evolve optimum fuzzy membership function parameters and rule structure through a genetic learning procedure. The high level, user friendly programming language combined with built-in functions to handle matrix algebra, Fourier series, and complex valued functions provides the power for large scale number crunching. The EFM objects are provided as .m files. Version M1.1 is designed with emphasis on modularity, flexibility, user friendliness, environment transparency, upgradability, and reliability.