雜志介紹

Evolutionary Intelligence雜志介紹

《Evolutionary Intelligence》是一本以English為主的未開放獲取國際優秀期刊，中文名稱進化智能，本刊主要出版、報道領域的研究動態以及在該領域取得的各方面的經驗和科研成果，介紹該領域有關本專業的最新進展，探討行業發展的思路和方法，以促進學術信息交流，提高行業發展。該刊已被國際權威數據庫SCIE收錄，為該領域相關學科的發展起到了良好的推動作用，也得到了本專業人員的廣泛認可。該刊最新影響因子為2.3，最新CiteScore 指數為6.8。

本刊近期中國學者發表的論文主要有：

• 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

英文介紹

Evolutionary Intelligence雜志英文介紹

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.