In this paper, an optimized approximation algorithm (OAA) is proposed to address the overfitting problem in function approximation using neural networks (NNs). The optimized approx...
— This paper presents a new method to generalize strategies in order to control parameters of Evolutionary Algorithms (EAs). A learning process establishes the relationship betwe...
The multi-objective covariance matrix adaptation evolution strategy (MO-CMA-ES) is a variable-metric algorithm for real-valued vector optimization. It maintains a parent population...
In this paper we describe a flexible and efficient new algorithm for model order reduction of parameterized systems. The method is based on the reformulation of the parametric s...
— This paper presents an adaptive Power System Stabilizer (PSS) using an Adaptive Network Based Fuzzy Inference System (ANFIS) and Genetic Algorithms (GAs). Firstly, genetic algo...