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Neural Computing and Applications, 2022 This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. The algorithm is based on the adoption of random mating concept from Hardy–Weinberg equilibrium and crossover index in order to produce new offspring. In this algorithm, effect of the environmental factor (i.e.
Mohd Herwan Sulaiman +4 more
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New observer-based control design for mismatched uncertain systems with time-delay
Archives of Control Sciences, 2016 In this paper, the state estimation problem for a class of mismatched uncertain time-delay systems is addressed. The estimation uses observer-based control techniques.
Huynh Van Van
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Use of the q-Gaussian mutation in evolutionary algorithms [PDF]
, 2010 Copyright @ Springer-Verlag 2010.This paper proposes the use of the q-Gaussian mutation with self-adaptation of the shape of the mutation distribution in evolutionary algorithms.
Yang, S +5 more
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08051 Executive Summary – Theory of Evolutionary Algorithms [PDF]
, 2008 The 2008 Dagstuhl Seminar "Theory of Evolutionary Algorithms" was the fifth in a firmly established series of biannual events. In the week from Jan. 27, 2008 to Feb.
Arnold, Dirk V. +3 more
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On the Evolution of Evolutionary Algorithms [PDF]
, 2004 In this paper we discuss the evolution of several components of a traditional Evolutionary Algorithm, such as genotype to phenotype mappings and genetic operators, presenting a formalized description of how this can be attained. We then focus on the evolution of mapping functions, for which we present experimental results achieved with a meta ...
Jorge Tavares +4 more
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Bias and Variance Analysis of Contemporary Symbolic Regression Methods
Applied SciencesSymbolic regression is commonly used in domains where both high accuracy and interpretability of models is required. While symbolic regression is capable to produce highly accurate models, small changes in the training data might cause highly dissimilar ...
Lukas Kammerer +2 more
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Population Dynamics in Genetic Programming for Dynamic Symbolic Regression
Applied SciencesThis paper investigates the application of genetic programming (GP) for dynamic symbolic regression (SR), addressing the challenge of adapting machine learning models to evolving data in practical applications.
Philipp Fleck +2 more
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IET Collaborative Intelligent Manufacturing, 2021 Predictive models are increasingly deployed within smart manufacturing for the control of industrial plants. With this arises, the need for long‐term monitoring of model performance and adaptation of models if surrounding conditions change and the ...
Florian Bachinger +2 more
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IEEE AccessA speed controller based on an adaptive super-twisting sliding mode control algorithm (AST) is designed for field-oriented control (FOC) of permanent magnet synchronous motor (PMSM) drive.
Hau Huu Vo, Son Hai Hoang, Vo-Tan Phuoc
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Chaos-Based Optimization - A Review
Journal of Advanced Engineering and Computation, 2017 This paper discusses the utilization of the complex chaotic dynamics given by the selected time-continuous chaotic systems as well as by the discrete chaotic maps, as the chaotic pseudo-random number generators and driving maps for the chaos based ...
Roman Senkerik +2 more
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