利用混合SOMA–PSO技术改进自主机器人的导航参数和控制

IF 2.6 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Evolutionary Intelligence Pub Date : 2023-01-17 DOI:10.1007/s12065-023-00820-8

M. Muni, Pragyan Kumar Pradhan, P. R. Dhal, Saroj Kumar, Rabinarayan Sethi, S. K. Patra

引用次数: 1

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Improving navigational parameters and control of autonomous robot using hybrid SOMA–PSO technique

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

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.