It is a well-known fact that improving forecasting accuracy is an important yet often
challenging issue. Extensive research has been conducted using neural networks (NNs) to …

Abstract Machine learning algorithms are inherently multiobjective in nature, where
approximation error minimization and model's complexity simplification are two conflicting …

In this paper, we propose a neural tree classifier, called the convex objective function neural
tree (COF-NT), which has a specialized perceptron at each node. The specialized …

In this paper, the universal approximation propriety is proved for the Flexible Beta Basis
Function Neural Tree (FBBFNT) model. This model is a tree-encoding method for designing …

In this paper, a Multi-Objective Extended Genetic Programming (MOEGP) algorithm is
developed to evolve the structure of the Hierarchical Flexible Beta Fuzzy System (HFBFS) …

In this paper, a PSO-based update memory for Improved Harmony Search (PSOUM-IHS)
algorithm is proposed to learn the parameters of Flexible Beta Basis Function Neural Tree …

The automated evolutionary design of an optimal hierarchical fuzzy system combined with
the use of Interval Type-2 Fuzzy Systems and the Beta basis function is considered in this …

This paper provides an overview on a new evolutionary approach based on an intelligent
multi-agent architecture to design Beta fuzzy systems (BFSs). The Methodology consists of …

Multi-Agent System (MAS) is a very active field that ensures global coherence between
agents' interactions in a distributed way and implicit global control. Under the awareness of …