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Optimizing Solutions for Real-Life Problems [Kõva köide]

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  • Formaat: Hardback, 283 pages, kõrgus x laius: 235x155 mm, 90 Illustrations, color; 31 Illustrations, black and white; IX, 283 p. 121 illus., 90 illus. in color., 1 Hardback
  • Sari: Springer Tracts in Nature-Inspired Computing
  • Ilmumisaeg: 20-May-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 9819632153
  • ISBN-13: 9789819632152
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  • Formaat: Hardback, 283 pages, kõrgus x laius: 235x155 mm, 90 Illustrations, color; 31 Illustrations, black and white; IX, 283 p. 121 illus., 90 illus. in color., 1 Hardback
  • Sari: Springer Tracts in Nature-Inspired Computing
  • Ilmumisaeg: 20-May-2025
  • Kirjastus: Springer Nature Switzerland AG
  • ISBN-10: 9819632153
  • ISBN-13: 9789819632152
Teised raamatud teemal:

This book explores various optimization techniques that can be used to address problems in the real world. These problems can be found in healthcare, engineering, manufacturing, and many other fields. In many real-world situations, from business to science, optimization techniques are similar to problem-solving tools. They help us make the best choices by considering limitations (constraints) and what we are trying to achieve (objectives). These techniques sift through all the possibilities and find the most effective option. Optimization is similar to a toolbox filled with different problem-solving methods, such as linear programming or genetic algorithms. These tools help us make better decisions about allocating resources across many different fields. They do this by finding the most efficient and effective solutions, considering all the limitations and goals involved.

Revolutionizing Optimization in Real-Life Implementation.- Swarm
Intelligence Applications in Spinal Health.- Optimization Techniques for
Critical Issues in Power Amplifiers.- Harnessing Nature-Inspired Optimization
for Enhanced Battery Efficiency and Sustainable Time Management.- Optimized
Approaches for Real-Life Sentiment Analysis in E-Commerce.- From Nature to
Navigation: A Comparative Study of Biologically Inspired Path Planning.-
Optimum Solution for Frequency Regulation of Interconnected Power Grid Using
Hybrid Genetic Firefly Algorithm Optimized PI-PD Cascade Controller.-
Optimization and machine learning algorithms for multivariate geochemical
data analysis and anomaly detection.- Integrating Game Theory and Explainable
AI for Optimized Software Code Analysis.- Enhancing Feature Selection using
Multi-Objective Optimization Concept.- Solving Real-Life Challenges using Bat
Algorithm.
Nilanjan Dey (senior member, IEEE) received the B.Tech., M.Tech. in information technology from West Bengal Board of Technical University and Ph.D. degrees in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, in 2005, 2011, and 2015, respectively. Currently, he is an associate professor with the Techno International New Town, Kolkata, and a visiting fellow of the University of Reading, UK. He has authored over 300 research articles in peer-reviewed journals and international conferences and 40 authored books. His research interests include medical imaging and machine learning. Moreover, he actively participates in programs and organizing committees for prestigious international conferences, including World Conference on Smart Trends in Systems Security and Sustainability (WorldS4), International Congress on Information and Communication Technology (ICICT), International Conference on Information and Communications Technology for Sustainable Development (ICT4SD), etc.