Computational Intelligence In Machine Learning
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Computational Intelligence for Machine Learning and Healthcare Informatics
Author: Rajshree Srivastava
language: en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date: 2020-06-22
This book presents a variety of techniques designed to enhance and empower multi-disciplinary and multi-institutional machine learning research in healthcare informatics. It is intended to provide a unique compendium of current and emerging machine learning paradigms for healthcare informatics, reflecting the diversity, complexity, and depth and breadth of this multi-disciplinary area.
Computational Intelligence in Machine Learning
Author: Vinit Kumar Gunjan
language: en
Publisher: Springer Nature
Release Date: 2025-08-02
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.
Computational Intelligence in Recent Communication Networks
This book focuses on the use of Artificial Intelligence and Machine Learning (AI/ML) based techniques to solve issues related to communication networks, their layers, as well as their applications. The book first offers an introduction to recent trends regarding communication networks. The authors then provide an overview of theoretical concepts of AI/ML, techniques and protocols used in different layers of communication. Furthermore, this book presents solutions that help analyze complex patterns in user data and ultimately improve productivity. Throughout, AI/ML-based solutions are provided, for topics such as signal detection, channel modeling, resource optimization, routing protocol design, transport layer optimization, user/application behavior prediction, software-defined networking, congestion control, communication network optimization, security, and anomaly detection. The book features chapters from a large spectrum of authors including researchers, students, as well as industrials involved in research and development.