Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System

IF 2 4区 计算机科学 Q2 Computer Science Intelligent Automation and Soft Computing Pub Date : 2023-01-01 DOI:10.32604/iasc.2023.040291
Laith Abualigah, Serdar Ekinci, Davut Izci, Raed Abu Zitar
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引用次数: 8
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基于改进精英对抗的人工蜂鸟算法设计FOPID控制巡航控制系统
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来源期刊
Intelligent Automation and Soft Computing
Intelligent Automation and Soft Computing 工程技术-计算机:人工智能
CiteScore
3.50
自引率
10.00%
发文量
429
审稿时长
10.8 months
期刊介绍: An International Journal seeks to provide a common forum for the dissemination of accurate results about the world of intelligent automation, artificial intelligence, computer science, control, intelligent data science, modeling and systems engineering. It is intended that the articles published in the journal will encompass both the short and the long term effects of soft computing and other related fields such as robotics, control, computer, vision, speech recognition, pattern recognition, data mining, big data, data analytics, machine intelligence, cyber security and deep learning. It further hopes it will address the existing and emerging relationships between automation, systems engineering, system of systems engineering and soft computing. The journal will publish original and survey papers on artificial intelligence, intelligent automation and computer engineering with an emphasis on current and potential applications of soft computing. It will have a broad interest in all engineering disciplines, computer science, and related technological fields such as medicine, biology operations research, technology management, agriculture and information technology.
期刊最新文献
Development of IoT Based Fish Monitoring System for Aquaculture Marketing Model Analysis of Fashion Communication Based on the Visual Analysis of Neutrosophic Systems An Improved Time Feedforward Connections Recurrent Neural Networks Modified Elite Opposition-Based Artificial Hummingbird Algorithm for Designing FOPID Controlled Cruise Control System Correction: Stock Market Index Prediction Using Machine Learning and Deep Learning Techniques
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