Exploring Critical Approaches Of Evolutionary Computation
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Exploring Critical Approaches of Evolutionary Computation
Modern optimization approaches have attracted an increasing number of scientists, decision makers, and researchers. As new issues in this field emerge, different optimization methodologies must be developed and implemented. Exploring Critical Approaches of Evolutionary Computation is a vital scholarly publication that explores the latest developments, methods, approaches, and applications of evolutionary models in a variety of fields. It also emphasizes evolutionary models of computation such as genetic algorithms, evolutionary strategies, classifier systems, evolutionary programming, genetic programming, and related fields such as swarm intelligence and other evolutionary computation techniques. Highlighting a range of pertinent topics such as neural networks, data mining, and data analytics, this book is designed for IT developers, IT theorists, computer engineers, researchers, practitioners, and upper-level students seeking current research on enhanced information exchange methods and practical aspects of computational systems.
Into a Deeper Understanding of Evolutionary Computing: Exploration, Exploitation, and Parameter Control
Author: Abdul Hanif Abdul Halim
language: en
Publisher: Springer Nature
Release Date: 2024-11-11
This book delves into fundamental and advanced strategies for enhancing evolutionary and metaheuristic algorithms, focusing on the crucial balance between exploration and exploitation in search mechanisms. As technological advancements increase optimization complexity, effectively managing this balance becomes essential for achieving optimal solutions within reasonable computational resources. The book's distinctive structure organizes content according to optimization stages and processes, offering a comprehensive discussion of various approaches supported by extensive literature. The authors note a scarcity of literature addressing the trade-offs between exploration and exploitation with contemporary references, making this work particularly valuable. It aims to deepen the reader's understanding of evolutionary computing, emphasizing exploration, exploitation, and parameter control. It is relevant not only to algorithm developers and the evolutionary computation community but also to students and researchers across scientific disciplines. The book is designed to be accessible to those without extensive algorithm development backgrounds, providing theoretical and practical insights into optimization methods.
Advancing Consumer-Centric Fog Computing Architectures
Due to a rapidly growing number of devices and communications, cloud computing has begun to fall behind on its ability to adequately process today’s technology. Additionally, companies have begun to look for solutions that would help reduce their infrastructure costs and improve profitability. Fog computing, a paradigm that extends cloud computing and services to the edge of the network, has presented itself as a viable solution and cost-saving method. However, before businesses can implement this new method, concerns regarding its security, privacy, availability, and data protection must be addressed. Advancing Consumer-Centric Fog Computing Architectures is a collection of innovative research on the methods and applications of fog computing in technological, business, and organizational dimensions. Thoroughly examining fog computing with respect to issues of management, trust and privacy, governance, and interoperability, this publication highlights a range of topics including access control mechanism, data confidentiality, and service-oriented architecture. This book is ideally designed for academicians, researchers, software developers, IT professionals, policymakers, technology designers, graduate-level students, managers, and business owners.