Abstract   Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...

Objective: In this study, we aimed to evaluate the effectiveness of training on emotion regulation skills and emotion regulation strategies to overcome anxiety in female students. Methods: We used a quasi-experimental design with pre-test and post-test evaluations to compare the experimental group with a control group. A total of 30 students were selected by multistage cluster sampling and wer...

Genetic Algorithms (GAs) purport to mimic the behavior of natural selection. Many GAs, however, try to optimize their populations by means of a static fitness function — one that is derived from performance on a fixed set of examples. We propose an architecture for an online genetic algorithm (OLGA) for classification. An OLGA differs from standard genetic algorithms in that it does not repeate...

This paper introduces a new constraint-handling method called InvertedShrinkable PAES (IS-PAES), which focuses the search effort of an evolutionary algorithm on specific areas of the feasible region by shrinking the constrained space of single-objective optimization problems. IS-PAES uses an adaptive grid as the original PAES (Pareto Archived Evolution Strategy). However, the adaptive grid of I...

In the context of function optimization, self-adaptation features of evolutionary search algorithms have been explored only with evolution strategy (ES) and evolutionary programming (EP). In this paper, we demonstrate the self-adaptive feature of real-parameter genetic algorithms (GAs) using the simulated binary crossover (SBX) operator. The connection between the working of selfadaptive ESs an...

This study concerns with a trust-region-based method for solving unconstrained optimization problems. The approach takes the advantages of the compact limited memory BFGS updating formula together with an appropriate adaptive radius strategy. In our approach, the adaptive technique leads us to decrease the number of subproblems solving, while utilizing the structure of limited memory quasi-Newt...

A flexible-joint robot manipulator is a complex system because it is nonlinear, multivariable, highly coupled along with joint flexibility and uncertainty. To overcome flexibility, several methods have been proposed based on flexible model. This paper presents a novel method for controlling flexible-joint robot manipulators. A novel control law is presented by compensating flexibility to form a...

Adaptive radiation is one of the most important outcomes of the process of evolution, and islands are places where it is best observed. The term itself was fi rst used by H. F. Osborn in  in describing parallel adaptations and convergence of species groups on different land masses. Since then, adaptive radiation has been widely recognized and defi ned in multiple ways to emphasize the contr...