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"This publication presents a series of practical applications of different Soft Computing techniques to real-world problems, showing the enormous potential of these techniques in solving problems"--Provided by publisher.
Nature provides inspiration and guidance in the creation of techniques, applications and new technologies in the fields of artificial intelligence and soft computing. This book presents various practical applications of soft computing techniques in real-world situations and problems, aiming to show the enormous potential of such techniques in solving all kinds of problems. It explores the latest advances in these techniques in an extensive state-of-the-art review and a vast theoretical study. Ideal for students studying AI and researchers familiarizing themselves with such techniques, it offers recent and novel applications, helping expand and explore new areas of research.
"This reference is a broad, multi-volume collection of the best recent works published under the umbrella of computer engineering, including perspectives on the fundamental aspects, tools and technologies, methods and design, applications, managerial impact, social/behavioral perspectives, critical issues, and emerging trends in the field"--Provided by publisher.
"This reference offers a wide-ranging selection of key research in a complex field of study,discussing topics ranging from using machine learning to improve the effectiveness of agents and multi-agent systems to developing machine learning software for high frequency trading in financial markets"--Provided by publishe
With the recent and enormous increase in the amount of available data sets of all kinds, applying effective and efficient techniques for analyzing and extracting information from that data has become a crucial task. Intelligent Data Analysis for Real-Life Applications: Theory and Practice investigates the application of Intelligent Data Analysis (IDA) to these data sets through the design and development of algorithms and techniques to extract knowledge from databases. This pivotal reference explores practical applications of IDA, and it is essential for academic and research libraries as well as students, researchers, and educators in data analysis, application development, and database management.
Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. - Focuses on the introduction and analysis of key algorithms - Includes case studies for real-world applications - Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.
Bio-inspired models have taken inspiration from the nature to solve challenging problems in an intelligent manner. Major aims of such bio-inspired models of computation are to propose new unconventional computing architectures and novel problem solving paradigms. Computing models such as artificial neural network (ANN), genetic algorithm (GA), and swarm intelligence (SI) are major constituent models of the bio-inspired approach. Applications of these models are ubiquitous and hence proposed to be applied for Semantic Web. The chapter discusses fundamentals of these bio-inspired constituents along with some heuristic that can be used to design and implement these constituents and briefly surveys recent applications of these models for the Semantic Web. The study shows that the objective of the Semantic Web is better met with such approach and the Web can be accessed in more human-oriented way. At the end, a generic framework for web content filtering based on neuro-fuzzy approach is presented. By considering online webpages and fuzzy user profile, the proposed system classifies the webpages into vague categories using a neural network.
This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems. It presents recent results of ANNs in modelling small, large and complex systems under three categories, namely, 1) Networks, Structure Optimisation, Robustness and Stochasticity 2) Advances in Modelling Biological and Environmental Systems and 3) Advances in Modelling Social and Economic Systems. The book aims at serving undergraduates, postgraduates and researchers in ANN computational modelling.
The information infrastructure - comprising computers, embedded devices, networks and software systems - is vital to operations in every sector: chemicals, commercial facilities, communications, critical manufacturing, dams, defense industrial base, emergency services, energy, financial services, food and agriculture, government facilities, healthcare and public health, information technology, nuclear reactors, materials and waste, transportation systems, and water and wastewater systems. Global business and industry, governments, indeed society itself, cannot function if major components of the critical information infrastructure are degraded, disabled or destroyed. Critical Infrastructure Protection XI describes original research results and innovative applications in the interdisciplinary field of critical infrastructure protection. Also, it highlights the importance of weaving science, technology and policy in crafting sophisticated, yet practical, solutions that will help secure information, computer and network assets in the various critical infrastructure sectors. Areas of coverage include: Infrastructure Protection, Infrastructure Modeling and Simulation, Industrial Control System Security, and Internet of Things Security. This book is the eleventh volume in the annual series produced by the International Federation for Information Processing (IFIP) Working Group 11.10 on Critical Infrastructure Protection, an international community of scientists, engineers, practitioners and policy makers dedicated to advancing research, development and implementation efforts focused on infrastructure protection. The book contains a selection of sixteen edited papers from the Eleventh Annual IFIP WG 11.10 International Conference on Critical Infrastructure Protection, held at SRI International, Arlington, Virginia, USA in the spring of 2017. Critical Infrastructure Protection XI is an important resource for researchers, faculty members and graduate students, as well as for policy makers, practitioners and other individuals with interests in homeland security.
In recent years, soft computing techniques have emerged as a successful tool to understand and analyze the collective behavior of service- oriented computing software. Algorithms and mechanisms of self- organization of complex natural systems have been used to solve problems, particularly in complex systems, which are adaptive, ever- evolving, and distributed in nature across the globe. What fits more perfectly into this scenario other than the rapidly developing era of Fog, IoT, and Edge computing environment? Service- oriented computing can be enhanced with soft computing techniques embedded inside the Cloud, Fog, and IoT systems. Soft Computing Principles and Integration for Real-Time Service-Oriented Computing explores soft computing techniques that have wide application in interdisciplinary areas. These soft computing techniques provide an optimal solution to the optimization problem using single or multiple objectives.The book focuses on basic design principles and analysis of soft computing techniques. It discusses how soft computing techniques can be used to improve quality-of-service in serviceoriented architectures. The book also covers applications and integration of soft computing techniques with a service- oriented computing paradigm. Highlights of the book include: A general introduction to soft computing An extensive literature study of soft computing techniques and emerging trends Soft computing techniques based on the principles of artificial intelligence, fuzzy logic, and neural networks The implementation of SOC with a focus on service composition and orchestration, quality of service (QoS) considerations, security and privacy concerns, governance challenges, and the integration of legacy systems The applications of soft computing in adaptive service composition, intelligent service recommendation, fault detection and diagnosis, SLA management, and security Such principles underlying SOC as loose coupling, reusability, interoperability, and abstraction An IoT based framework for real time data collection and analysis using soft computing