Santosh Kumar Das - Böcker

This book helps to enhance the application of fuzzy logic optimization in the areas of science and engineering. It includes implementation and models and paradigms, such as path planning and routing design for different wireless networks, organization behavior strategies models, and so forth. It also: Explains inventory control management, uncertainties management, loss minimization, game optimization, data analysis and prediction, different decision-making system and management, and so forth Describes applicability of fuzzy optimization techniques in areas of science and management Resolves several issues based on uncertainty using member function Helps map different problems based on mathematical models Includes issues and problems based on linear and nonlinear optimizations Focuses on management science such as manpower management and inventory planningThis book is aimed at researchers and graduate students in signal processing, power systems, systems and industrial engineering, and computer networks.

This book helps to enhance the application of fuzzy logic optimization in the areas of science and engineering. It includes implementation and models and paradigms, such as path planning and routing design for different wireless networks, organization behavior strategies models, and so forth. It also: Explains inventory control management, uncertainties management, loss minimization, game optimization, data analysis and prediction, different decision-making system and management, and so forth Describes applicability of fuzzy optimization techniques in areas of science and management Resolves several issues based on uncertainty using member function Helps map different problems based on mathematical models Includes issues and problems based on linear and nonlinear optimizations Focuses on management science such as manpower management and inventory planningThis book is aimed at researchers and graduate students in signal processing, power systems, systems and industrial engineering, and computer networks.

This new volume presents a range of techniques that aim to enhance the operation of human resource management by applying state-of-the-art artificial intelligence technology. With illustrative case studies, the volume uses examples from several real-life problems and includes their possible solutions using advanced AI technology. The book explores the confluence of smart computing and traditional businesses to foster productivity, profitability, and prosperity and goes on to apply AI techniques in the recruitment process, with enterprise resource planning management software, for manpower optimization systems in colleges, for creating uniformity in HRM across organizations, for creating conflicting strategy management techniques, and more. One pandemicrelated chapter discusses the use of radio frequency-based technology for monitoring social distancing.

This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics.

This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics.

This book provides an overview of the current state of the art in wireless networks around the globe, focusing on utilizing the latest artificial intelligence and soft computing techniques to provide design frameworks for wireless networks. These techniques play a vital role in developing a more robust algorithm suitable for the dynamic and heterogeneous environment, making the network self-managed, self-operational, and self-configurational, and efficiently reducing uncertainties and imprecise information.

This book provides an overview of the current state of the art in wireless networks around the globe, focusing on utilizing the latest artificial intelligence and soft computing techniques to provide design frameworks for wireless networks.

This book presents nature inspired computing applications for the wireless sensor network (WSN). Although the use of WSN is increasing rapidly, it has a number of limitations in the context of battery issue, distraction, low communication speed, and security. This means there is a need for innovative intelligent algorithms to address these issues.The book is divided into three sections and also includes an introductory chapter providing an overview of WSN and its various applications and algorithms as well as the associated challenges. Section 1 describes bio-inspired optimization algorithms, such as genetic algorithms (GA), artificial neural networks (ANN) and artificial immune systems (AIS) in the contexts of fault analysis and diagnosis, and traffic management. Section 2 highlights swarm optimization techniques, such as African buffalo optimization (ABO), particle swarm optimization (PSO), and modified swarm intelligence technique for solving the problems of routing,network parameters optimization, and energy estimation. Lastly, Section 3 explores multi-objective optimization techniques using GA, PSO, ANN, teaching–learning-based optimization (TLBO), and combinations of the algorithms presented. As such, the book provides efficient and optimal solutions for WSN problems based on nature-inspired algorithms.

Section 2 highlights swarm optimization techniques, such as African buffalo optimization (ABO), particle swarm optimization (PSO), and modified swarm intelligence technique for solving the problems of routing,network parameters optimization, and energy estimation.

The book discusses efficiency and robustness of wireless network as a platform for communication and data transmission and also discusses some challenges and security issues such as limited hardware resources, unreliable communication, dynamic topology of some wireless networks, vulnerability and unsecure environment.

The book discusses efficiency and robustness of wireless network as a platform for communication and data transmission and also discusses some challenges and security issues such as limited hardware resources, unreliable communication, dynamic topology of some wireless networks, vulnerability and unsecure environment.

It includes several implementation paradigms such as design and path planning of wireless network, security mechanism and implementation for dynamic as well as static nodes, learning method of cloud computing, data exploration and management, data analysis and optimization, decision taking in conflicting environment, etc.