A bibliometric analysis on the relevancies of artificial neural networks (ANN) techniques in offshore engineering

IF 2.1 Q2 ENGINEERING, MULTIDISCIPLINARY

Cogent Engineering Pub Date : 2023-08-07 DOI:10.1080/23311916.2023.2241729

Muhammad Daniel Abdul Shahid, M. M. Mohd Hashim, Najwa Mohd Fadzil, Muhd Hariz Ahmad Rushdi, Amin Al-Fakih, Mohd Fakri Muda

引用次数: 0

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海洋工程中人工神经网络技术相关性的文献计量分析

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cogent Engineering ENGINEERING, MULTIDISCIPLINARY-

CiteScore

4.00

自引率

5.30%

发文量

213

审稿时长

13 weeks

期刊介绍： One of the largest, multidisciplinary open access engineering journals of peer-reviewed research, Cogent Engineering, part of the Taylor & Francis Group, covers all areas of engineering and technology, from chemical engineering to computer science, and mechanical to materials engineering. Cogent Engineering encourages interdisciplinary research and also accepts negative results, software article, replication studies and reviews.