Results 61 to 70 of about 257,922 (221)
Evolutionary Computation Methods and their applications in Statistics
A brief discussion of the genesis of evolutionary computation methods, their relationship to artificial intelligence, and the contribution of genetics and Darwin’s theory of natural evolution is provided.
Francesco Battaglia
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Efficient Computation of Fitness Function for Evolutionary Clustering
Evolutionary algorithms (EAs) are random search heuristics which can solve various optimization problems. There are plenty of papers describing different approaches developed to apply evolutionary algorithms to the clustering problem, although none of ...
Sergey Muravyov +3 more
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Evolutionary Computation for Feature Manipulation in Salient Object Detection [PDF]
Shima Afzali Vahed Moghaddam
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Evolutionary Computation for CSP’s [PDF]
Los problemas de Scheduling son un paradigma de la familia de problemas CSP. En este artículo presentamos algunas técnicas de resolución mediante Algoritmos Genéticos.
Alonso González, César Luis +3 more
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Evolutionary multiobjective optimization: open research areas and some challenges lying ahead
Evolutionary multiobjective optimization has been a research area since the mid-1980s, and has experienced a very significant activity in the last 20 years. However, and in spite of the maturity of this field, there are still several important challenges
Carlos A. Coello Coello +4 more
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Elitism Levels Traverse Mechanism For The Derivation of Upper Bounds on Unimodal Functions [PDF]
In this article we present an Elitism Levels Traverse Mechanism that we designed to find bounds on population-based Evolutionary algorithms solving unimodal functions. We prove its efficiency theoretically and test it on OneMax function deriving bounds c{
Ter-Sarkisov, Aram
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Advent of distributed generation and progression towards an intelligent grid infrastructure within the domain of contemporary electrical power systems have created dynamic load profiles.
Samira Sadeghi +3 more
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Review of Reinforcement Learning and Evolutionary Computation Methods for StrategyExploration [PDF]
Reinforcement learning and evolutionary computation,as two types of nature-inspired learning paradigms,are the mainstream methods for solving strategy exploration problems,and the fusion of these two types of methods provides a general solution for ...
WANG Yao, LUO Junren, ZHOU Yanzhong, GU Xueqiang, ZHANG Wanpeng
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Fitness Approximation Through Machine Learning with Dynamic Adaptation to the Evolutionary State
We present a novel approach to performing fitness approximation in genetic algorithms (GAs) using machine learning (ML) models, focusing on dynamic adaptation to the evolutionary state.
Itai Tzruia +3 more
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IEEE Transactions on Evolutionary Computation Publication Information [PDF]
Carlos Coello Coello +72 more
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