This work analyzes the behavior of evolution strategies and their current mutation variants on a simple rotating dynamic problem. The degree of rotation is a parameter for the involved dynamism which enables systematic examinations. As a result the complex covariance matrix adaptation proves to be superior with slow rotation but with increasing dynamism those adaptation mechanism seldom find th...

The success of evolutionary search depends on adequate parameter settings. Ill conditioned strategy parameters decrease the success probabilities of genetic operators. Proper settings may change during the optimization process. The question arises if adequate settings can be found automatically during the optimization process. Evolution strategies gave an answer to the online parameter control ...

The dynamic constrained optimization problems can be a challenge for the algorithms. They must tackle global optimum detection, as well change of environment. Recently, novel test suite was introduced. Furthermore, three well-performed evolutionary algorithms were compared based on it. experimental results show that each algorithm performed best different type problem. objective our work to dev...

Kernel based techniques have shown outstanding success in data mining and machine learning in the recent past. Many optimization problems of kernel based methods suffer from multiple local optima. Evolution strategies have grown to successful methods in non-convex optimization. This work shows how both areas can profit from each other. We investigate the application of evolution strategies to N...

Abstract Density functional theory (DFT) has become a standard tool for the study of point defects in materials. However, finding most stable defective structures remains very challenging task as it involves solution multimodal optimization problem with high-dimensional objective function. Hitherto, approaches commonly used to tackle this have been mostly empirical, heuristic, and/or based on d...

Activation functions (AFs), which are pivotal to the success (or failure) of a neural network, have received increased attention in recent years, with researchers seeking design novel AFs that improve some aspect network performance. In this paper we take another direction, wherein combine slew known into successful architectures, proposing three methods do so beneficially: (1) generate AF arch...

In this study, a novel hybridization approach, which is called CMASFS and based on the covariance matrix adaptation evolution strategy (CMA-ES) stochastic fractal search (SFS) algorithms. To make proposed algorithm dynamic, Gaussian walk equations involved in diffusion process of SFS have been updated decide to use equations. The effectiveness tested using CEC2017 benchmark functions having uni...

introduction: extracellular matrix (ecm) components significantly influence the growth characteristics of cell, development of spontaneous contractile activity, andmorphologic differentiation. the present study evaluates the effect of ecm ongenotypic and physiologic characteristics of cardiomyocytes derived from embryonic stem (es) cells. material and methods: embryoid bodies derived from mouse...