Investigation of Kriging-based SAEAs’ metamodel samples for computationally expensive optimization problems

IF 2.3 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Evolutionary Intelligence Pub Date : 2023-07-05 DOI:10.1007/s12065-023-00862-y

Mônica A. C. Valadão, André L. Maravilha, Lucas S. Batista

引用次数: 0

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基于kriging的saea元模型样本在计算代价昂贵的优化问题中的研究

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来源期刊

Evolutionary Intelligence COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

6.80

自引率

0.00%

发文量

108

期刊介绍： This Journal provides an international forum for the timely publication and dissemination of foundational and applied research in the domain of Evolutionary Intelligence. The spectrum of emerging fields in contemporary artificial intelligence, including Big Data, Deep Learning, Computational Neuroscience bridged with evolutionary computing and other population-based search methods constitute the flag of Evolutionary Intelligence Journal.Topics of interest for Evolutionary Intelligence refer to different aspects of evolutionary models of computation empowered with intelligence-based approaches, including but not limited to architectures, model optimization and tuning, machine learning algorithms, life inspired adaptive algorithms, swarm-oriented strategies, high performance computing, massive data processing, with applications to domains like computer vision, image processing, simulation, robotics, computational finance, media, internet of things, medicine, bioinformatics, smart cities, and similar. Surveys outlining the state of art in specific subfields and applications are welcome.