This book addresses and disseminates state-of-the-art research and development of differential evolution (DE) and its recent advances, such as the development of adaptive, self-adaptive and hybrid techniques. Differential evolution is a population-based meta-heuristic technique for global optimization capable of handling non-differentiable, non-linear and multi-modal objective functions. Many advances have been made recently in differential evolution, from theory to applications. This book comprises contributions which include theoretical developments in DE, performance comparisons of DE, hybrid DE approaches, parallel and distributed DE for multi-objective optimization, software implementations, and real-world applications. The book is useful for researchers, practitioners, and students in disciplines such as optimization, heuristics, operations research and natural computing.

This book includes the original, peer reviewed research articles from the 2nd International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2020), held in August, 2020 at Goa, India. It covers the latest research trends or developments in areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber physical systems and cybernetics.

This book provides a collection of selected papers presented at the International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2019), which was held in Goa, India, on 16-17 August 2019. It covers the latest research trends and advances in the areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber-physical systems, and cybernetics.

This book includes the original, peer reviewed research articles from the 2nd International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA 2020), held in August, 2020 at Goa, India. It covers the latest research trends or developments in areas of data science, artificial intelligence, neural networks, cognitive science and machine learning applications, cyber physical systems and cybernetics.

This two-volume set constitutes reviewed and selected papers from the 12th International Advanced Computing Conference, IACC 2022, held in Hyderabad, India, in December 2022. The 72 full papers and 6 short papers presented in the volume were thorougly reviewed and selected from 415 submissions. The papers are organized in the following topical sections: ​AI in industrial applications; application of AI for disease classification and trend analysis; design of agricultural applications using AI; disease classification using CNN; innovations in AI; system security and communication using AI; use of AI in human psychology; use of AI in music and video industries.

This two-volume set constitutes reviewed and selected papers from the 12th International Advanced Computing Conference, IACC 2022, held in Hyderabad, India, in December 2022. The 72 full papers and 6 short papers presented in the volume were thorougly reviewed and selected from 415 submissions. The papers are organized in the following topical sections: ​AI in industrial applications; application of AI for disease classification and trend analysis; design of agricultural applications using AI; disease classification using CNN; innovations in AI; system security and communication using AI; use of AI in human psychology; use of AI in music and video industries.

This book addresses and disseminates state-of-the-art research and development of differential evolution (DE) and its recent advances, such as the development of adaptive, self-adaptive and hybrid techniques. Differential evolution is a population-based meta-heuristic technique for global optimization capable of handling non-differentiable, non-linear and multi-modal objective functions. Many advances have been made recently in differential evolution, from theory to applications. This book comprises contributions which include theoretical developments in DE, performance comparisons of DE, hybrid DE approaches, parallel and distributed DE for multi-objective optimization, software implementations, and real-world applications. The book is useful for researchers, practitioners, and students in disciplines such as optimization, heuristics, operations research and natural computing.