Evolutionary Intelligence

杂志介绍

Evolutionary Intelligence杂志介绍

《Evolutionary Intelligence》是一本以English为主的未开放获取国际优秀期刊，中文名称进化智能，本刊主要出版、报道领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为2.3，最新CiteScore 指数为6.8。

本刊近期中国学者发表的论文主要有：

• Hybrid chaotic system-oriented artificial fish swarm neural network for image encryption

  Author: Liu, Junjun; Zhang, Jun; Yin, Shoulin

• Multi-objective evolutionary algorithm for vehicle routing problem with time window under uncertainty

  Author: Tan, Fei; Chai, Zheng-yi; Li, Ya-lun

• A novel fully convolutional network based on marker-controlled watershed segmentation algorithm for industrial soot robot target segmentation

  Author: Ju, Aiyun; Wang, Zhongli

• Grey wolf optimization algorithm based on dynamically adjusting inertial weight and levy flight strategy

  Author: Chen, Yehua; Xi, Junfu; Wang, Haibin; Liu, Xia

英文介绍

Evolutionary Intelligence杂志英文介绍

Evolutionary Intelligence is an international academic journal dedicated to evolutionary computing and its applications in the field of artificial intelligence. This magazine is published by Springer Press and aims to publish high-quality research articles related to evolutionary algorithms, genetic programming, swarm intelligence, multi-objective optimization, and more. The journal covers theoretical research, algorithm development, experimental analysis, and practical application cases, aiming to promote scientific development and technological innovation in the field of intelligent computing.

The magazine's readership includes academic researchers, engineers, computer scientists, as well as graduate and undergraduate students interested in evolutionary computing. Journals provide a platform for the academic community to exchange ideas, showcase innovation, and discuss future research directions by publishing cutting-edge research results. In addition, the magazine also focuses on the application of intelligent computing in solving complex engineering problems, data analysis, machine learning, and other fields, promoting the close integration of theory and practice.