The Adaptive Chemotactic Foraging with Differential Evolution algorithm

Universal approximation propriety of Flexible Beta Basis Function Neural Tree

“…The new representation called Flexible Beta Basis Function Neural Tree (FBBFNT) [9], [10], [11], [12], is more flexible than the classical BBFNN seen that it can find automatically the number of nodes as well as the number of hidden layers. The FBBFNT is evolved by a hybrid algorithm with two levels: structure evolution and parameter evolution using evolutionary computation [13], [14], [15]. The performance of the evolving FBBFNT is tested for approximating some nonlinear systems.…”

Fuzzy modeling system based on hybrid evolutionary approach

“…Recently, computational Intelligence techniques such as fuzzy logic [1], artificial neural networks [2,3] and evolutionary algorithms (EAs) [4][5][6] are becoming popular research subjects. They can deal complex problems which are difficult to be solved by classical techniques [7].…”