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<p class="MsoNormal" style="line-height: 115%;"><span lang="EN-US" style="font-family: 'Times New Roman',serif; color: #002060;">This book features selected proceedings from the International Conference on Computational Intelligence in Machine Learning (ICCIML 2023). It covers the latest research trends and developments in various fields, including machine learning, smart cities, the Internet of Things (IoT), artificial intelligence, cyber-physical systems, cybernetics, data science, neural networks, and cognition, among others. The book also emphasizes the comprehensive nature of computational intelligence, artificial intelligence, machine learning, and deep learning by highlighting their roles in modeling, identification, optimization, prediction, forecasting, and controlling future intelligent systems. This volume serves as a valuable resource for researchers in both academia and industry, offering in-depth insights from fundamental research contributions. It focuses on methodological and application perspectives, enhancing the understanding of AI and ML approaches and their capabilities in addressing a diverse range of problems across various industries and real-world applications.</span><span lang="EN-US" style="font-family: 'Times New Roman',serif; color: #1f497d;">&#xa0;</span></p><p>&#xa0;</p><p>&#xa0;</p>

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Computational Intelligence in Machine Learning

  • 会议论文集

  • 发表日期：

    2025年

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摘要

This book features selected proceedings from the International Conference on Computational Intelligence in Machine Learning (ICCIML 2023). It covers the latest research trends and developments in various fields, including machine learning, smart cities, the Internet of Things (IoT), artificial intelligence, cyber-physical systems, cybernetics, data science, neural networks, and cognition, among others. The book also emphasizes the comprehensive nature of computational intelligence, artificial intelligence, machine learning, and deep learning by highlighting their roles in modeling, identification, optimization, prediction, forecasting, and controlling future intelligent systems. This volume serves as a valuable resource for researchers in both academia and industry, offering in-depth insights from fundamental research contributions. It focuses on methodological and application perspectives, enhancing the understanding of AI and ML approaches and their capabilities in addressing a diverse range of problems across various industries and real-world applications.