Nature-Inspired Optimization Algorithms: Recent Advances in Natural Computing and Biomedical Applications
Aditya Khamparia (Ed.)
ISBN 10: 3110676060 ISBN 13: 9783110676068
Edité par De Gruyter, 2021
Neuf(s)
Couverture rigide
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A propos de cet article
Description :
2021. Hardcover. . . . . . N° de réf. du vendeur V9783110676068
Synopsis :
This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems.
Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications.
Tentative Table of Contents/Topic Coverage:
- Neural Computation
- Evolutionary Computing Methods
- Neuroscience driven AI Inspired Algorithms
- Biological System based algorithms
- Hybrid and Intelligent Computing Algorithms
- Application of Natural Computing
- Review and State of art analysis of Optimization algorithms
- Molecular and Quantum computing applications
- Swarm Intelligence
- Population based algorithm and other optimizations
À propos de l?auteur:
A. Khamparia, Lovely Professional Univ.; A. Khanna, M. Agrasen Inst. of Techn., India; N. Nhu, B. Nguyen, Duy Tan University, Vietnam.
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Détails bibliographiques
Titre : Nature-Inspired Optimization Algorithms: ...
Éditeur : De Gruyter
Date d'édition : 2021
Reliure : Couverture rigide
Etat : New