Optimizing Solutions for Real-Life Problems by Nilanjan Dey ISBN 9789819632152, 9819632153 instant download

Optimizing Solutions for Real-Life Problems by Nilanjan Dey ISBN 9789819632152, 9819632153 instant download

This book includes 10 chapters:

Chap 1 offers incisive advice on how to use optimization algorithms to solve issues and promote innovation in a variety of industries.

Chap 2 shows the potential of evolutionary approaches to shape the future of cybersecurity through a thorough analysis of existing uses and future possibilities.

Chap 3 presents the idea of differentiating between different amplifier technologies and optimizing the operating and design characteristics of each linearizer or amplifier stage.

Chap 4 investigates how game theory and explainable artificial intelligence (XAI) may be combined to optimize software systems.

Chap 5 demonstrates how automated sentiment analysis systems can improve customer satisfaction by using a combination of classic machine learning models and a rule-based classifier to provide insights into consumer opinions.

Chap 6 evaluates a number of biologically inspired algorithms in an attempt to replicate real-world AMR navigation issues.

Chap 7 addresses the response analysis of the proportional integral derivative (PID)-optimized hybrid genetic firefly algorithm for frequency regulation in a two-area hybrid power system.

Chap 8 describes two real-world examples from the two exploratory geochemical projects to highlight some of the most popular machine learning algorithms for the optimization of multivariate geochemical data processing.

Chap 9 discusses the idea of the Bat algorithm and how it has been used to alter several real-world problem domains.

Chap 10 offers a comparative analysis between multiobjective and single-objective feature selection.