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Artificial Intelligence and Natural Algorithms

Artificial Intelligence and Natural Algorithms

Rijwan KhanDr. Pawan SharmaDr. Sugam SharmaProf. Santosh Kumar

This book informs the reader about applications of ArtificialIntelligence (AI) and nature-inspired algorithms in different situations. Eachchapter in this book is written by topic experts on AI, nature-inspired algorithmsand data science. Chapters are structured to provide an introduction to the topic, the computational methodology required for experimentation and analysis, and a discussion of results results The basic concepts relevant to these topics are explained, includingevolutionary computing (EC), artificial neural networks (ANN), swarmintelligence (SI), and fuzzy systems (FS). Additionally, the book also covers optimizationalgorithms for data analysis. The contents include algorithms that can be used in systems designedfor plant science research, environmental analysis, computer vision andhealthcare. There are a variety of use cases highlighted in the book that demonstrate how computer algorithms can be used to simulate and understand natural phenomena, such as moving object detection, COVID-19 detection, genetic diversity, physiology and much more. Additionally, the contributors provide useful tips specific to some algorithsm such as load balancing techniques and fuzzy PID controls. The goal of the book is to equip the reader – students and data analysts– with the information needed to apply basic AI algorithms to resolve actualproblems encountered in a professional environment. This book informs the reader about applications of ArtificialIntelligence (AI) and nature-inspired algorithms in different situations. Eachchapter in this book is written by topic experts on AI, nature-inspired algorithmsand data science. Chapters are structured to provide an introduction to the topic, the computational methodology required for experimentation and analysis, and a discussion of results results The basic concepts relevant to these topics are explained, includingevolutionary computing (EC), artificial neural networks (ANN), swarmintelligence (SI), and fuzzy systems (FS). Additionally, the book also covers optimizationalgorithms for data analysis. The contents include algorithms that can be used in systems designedfor plant science research, environmental analysis, computer vision andhealthcare. There are a variety of use cases highlighted in the book that demonstrate how computer algorithms can be used to simulate and understand natural phenomena, such as moving object detection, COVID-19 detection, genetic diversity, physiology and much more. Additionally, the contributors provide useful tips specific to some algorithsm such as load balancing techniques and fuzzy PID controls. The goal of the book is to equip the reader – students and data analysts– with the information needed to apply basic AI algorithms to resolve actualproblems encountered in a professional environment.

$ 79.00

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