Computational Intelligence in Engineering Problem Solving – serie

The objective of this edited book is to share the outcomes from various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances in machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation systems, forecasting air quality, healthcare, exchange rate prediction, and image dehazing. It also provides a premier interdisciplinary platform for scientists, researchers, practitioners, and educators to share their thoughts in the context of recent innovations, trends, developments, practical challenges, and advancements in the field of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in the decision-making process in several aspects. To address these objectives, this edited book includes a dozen chapters contributed by authors from around the globe. The authors attempt to solve these complex problems using several intelligent machine-learning techniques. This allows researchers to understand the mechanism needed to harness the decision-making process using machine-learning techniques for their own respective endeavors.

The objective of this edited book is to share the outcomes from various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances in machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation systems, forecasting air quality, healthcare, exchange rate prediction, and image dehazing. It also provides a premier interdisciplinary platform for scientists, researchers, practitioners, and educators to share their thoughts in the context of recent innovations, trends, developments, practical challenges, and advancements in the field of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in the decision-making process in several aspects. To address these objectives, this edited book includes a dozen chapters contributed by authors from around the globe. The authors attempt to solve these complex problems using several intelligent machine-learning techniques. This allows researchers to understand the mechanism needed to harness the decision-making process using machine-learning techniques for their own respective endeavors.

Integration of IoT (Internet of Things) with big data and cloud computing has brought forward numerous advantages and challenges such as data analytics, integration, and storage. This book highlights these challenges and provides an integrating framework for these technologies, illustrating the role of blockchain in all possible facets of IoT security. Furthermore, it investigates the security and privacy issues associated with various IoT systems along with exploring various machine learning-based IoT security solutions. This book brings together state-of-the-art innovations, research activities (both in academia and in industry), and the corresponding standardization impacts of 5G as well. Aimed at graduate students, researchers in computer science and engineering, communication networking, IoT, machine learning and pattern recognition, this book Showcases the basics of both IoT and various security paradigms supporting IoT, including Blockchain Explores various machine learning-based IoT security solutions and highlights the importance of IoT for industries and smart cities Presents various competitive technologies of Blockchain, especially concerned with IoT security Provides insights into the taxonomy of challenges, issues, and research directions in IoT-based applications Includes examples and illustrations to effectively demonstrate the principles, algorithm, applications, and practices of security in the IoT environment

Integration of IoT (Internet of Things) with big data and cloud computing has brought forward numerous advantages and challenges such as data analytics, integration, and storage. This book highlights these challenges and provides an integrating framework for these technologies, illustrating the role of blockchain in all possible facets of IoT security. Furthermore, it investigates the security and privacy issues associated with various IoT systems along with exploring various machine learning-based IoT security solutions. This book brings together state-of-the-art innovations, research activities (both in academia and in industry), and the corresponding standardization impacts of 5G as well. Aimed at graduate students, researchers in computer science and engineering, communication networking, IoT, machine learning and pattern recognition, this book Showcases the basics of both IoT and various security paradigms supporting IoT, including Blockchain Explores various machine learning-based IoT security solutions and highlights the importance of IoT for industries and smart cities Presents various competitive technologies of Blockchain, especially concerned with IoT security Provides insights into the taxonomy of challenges, issues, and research directions in IoT-based applications Includes examples and illustrations to effectively demonstrate the principles, algorithm, applications, and practices of security in the IoT environment

The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects.Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT.This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.

The fusion of AI and IoT enables the systems to be predictive, prescriptive, and autonomous, and this convergence has evolved the nature of emerging applications from being assisted to augmented, and ultimately to autonomous intelligence. This book discusses algorithmic applications in the field of machine learning and IoT with pertinent applications. It further discusses challenges and future directions in the machine learning area and develops understanding of its role in technology, in terms of IoT security issues. Pertinent applications described include speech recognition, medical diagnosis, optimizations, predictions, and security aspects.Features: Focuses on algorithmic and practical parts of the artificial intelligence approaches in IoT applications. Discusses supervised and unsupervised machine learning for IoT data and devices. Presents an overview of the different algorithms related to Machine learning and IoT. Covers practical case studies on industrial and smart home automation. Includes implementation of AI from case studies in personal and industrial IoT.This book aims at Researchers and Graduate students in Computer Engineering, Networking Communications, Information Science Engineering, and Electrical Engineering.

Modeling with differential equations is an effective tool to provide methodical and quantitative solutions to real-world phenomena including investigating measurable features, consolidation and processing of data, and designing and developing complex engineering systems. This book describes differential equations correlation with qualitative and quantitative analysis, and mathematical modeling in the engineering and applied sciences. Given equations are explained from multidimensional characterizations with MATLAB® codes.Features:Addresses differential equation-based approaches to solve varied engineering problemsDiscusses derivation and solution of major equations of engineering and applied scienceReviews qualitative and quantitative (numerical) analysis and mathematical modellingIncludes mathematical models of the discussed problemsDiscusses MATLAB® codesFeatures: code and online materials related to the differential equations.This book is aimed at researchers graduate students in electrical and electronics engineering, control systems, electron devices society, applied physics, and engineering design.

Modeling with differential equations is an effective tool to provide methodical and quantitative solutions to real-world phenomena including investigating measurable features, consolidation and processing of data, and designing and developing complex engineering systems. This book describes differential equations correlation with qualitative and quantitative analysis, and mathematical modeling in the engineering and applied sciences. Given equations are explained from multidimensional characterizations with MATLAB® codes.Features:Addresses differential equation-based approaches to solve varied engineering problemsDiscusses derivation and solution of major equations of engineering and applied scienceReviews qualitative and quantitative (numerical) analysis and mathematical modellingIncludes mathematical models of the discussed problemsDiscusses MATLAB® codesFeatures: code and online materials related to the differential equations.This book is aimed at researchers graduate students in electrical and electronics engineering, control systems, electron devices society, applied physics, and engineering design.

Industrial Power Systems: Evolutionary Aspects provides evolutionary and integrated aspects of industrial power systems including review of development of modern power systems from DC to microgrid. Generation options of thermal and hydro power including nuclear and power from renewables are discussed along with concepts for single-line diagram, overhead transmission lines, concepts of corona, sag, overhead insulators and over voltage protective devices. Subsequent chapters cover analysis of power systems and power system protection with basic concept of power system planning and economic operations.Features: Covers the fundamentals of power systems, including its design, analysis, market structure and economic operations Discusses performance of transmission lines with associated parameters, determination of performance and load flow analysis Reviews residual generation/load imbalance as handled by the automatic generation control (AGC) Includes different advanced technologies including HTLS overhead conductor, XLPE cable, vacuum/SF6 circuit breaker, solid state relays, among others Explores practical aspects required for field level work such as installation of cable network for power distribution purposes, types of earthing and tariff mechanismThis book will be of interest to graduate students, researchers and professionals in power engineering, load flow and power systems protection.

Industrial Power Systems: Evolutionary Aspects provides evolutionary and integrated aspects of industrial power systems including review of development of modern power systems from DC to microgrid. Generation options of thermal and hydro power including nuclear and power from renewables are discussed along with concepts for single-line diagram, overhead transmission lines, concepts of corona, sag, overhead insulators and over voltage protective devices. Subsequent chapters cover analysis of power systems and power system protection with basic concept of power system planning and economic operations.Features: Covers the fundamentals of power systems, including its design, analysis, market structure and economic operations Discusses performance of transmission lines with associated parameters, determination of performance and load flow analysis Reviews residual generation/load imbalance as handled by the automatic generation control (AGC) Includes different advanced technologies including HTLS overhead conductor, XLPE cable, vacuum/SF6 circuit breaker, solid state relays, among others Explores practical aspects required for field level work such as installation of cable network for power distribution purposes, types of earthing and tariff mechanismThis book will be of interest to graduate students, researchers and professionals in power engineering, load flow and power systems protection.

Semantic web technologies (SWTs) offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. This book provides a roadmap for semantic web technologies (SWTs) and highlights their role in a wide range of domains including cloud computing, Internet of Things, big data, sensor network, and so forth. It also explores the prospects of these technologies including different data interchange formats, query languages, ontologies, Linked Data, and notations. The role of SWTs in ‘epidemic Covid-19’, ‘e-learning platforms and systems’, ‘block chain’, ‘open online courses’, and ‘visual analytics in healthcare’ is described as well. This book:Explores all the critical aspects of semantic web technologies (SWTs) Discusses the impact of SWTs on cloud computing, Internet of Things, big data, and sensor network Offers a comprehensive examination of the emerging research in the areas of SWTs and their related domains Provides a template to develop a wide range of smart and intelligent applications Includes latest applications and examples with real data This book is aimed at researchers and graduate students in computer science, informatics, web technology, cloud computing, and Internet of Things.

Semantic web technologies (SWTs) offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. This book provides a roadmap for semantic web technologies (SWTs) and highlights their role in a wide range of domains including cloud computing, Internet of Things, big data, sensor network, and so forth. It also explores the prospects of these technologies including different data interchange formats, query languages, ontologies, Linked Data, and notations. The role of SWTs in ‘epidemic Covid-19’, ‘e-learning platforms and systems’, ‘block chain’, ‘open online courses’, and ‘visual analytics in healthcare’ is described as well. This book:Explores all the critical aspects of semantic web technologies (SWTs) Discusses the impact of SWTs on cloud computing, Internet of Things, big data, and sensor network Offers a comprehensive examination of the emerging research in the areas of SWTs and their related domains Provides a template to develop a wide range of smart and intelligent applications Includes latest applications and examples with real data This book is aimed at researchers and graduate students in computer science, informatics, web technology, cloud computing, and Internet of Things.

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.