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Nature-Inspired Optimization Algorithms - Recent Advances in Natural Computing and Biomedical Applications (Hardcover)
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Nature-Inspired Optimization Algorithms - Recent Advances in Natural Computing and Biomedical Applications (Hardcover)
Series: Intelligent Biomedical Data Analysis
Expected to ship within 12 - 17 working days
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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
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