Smart and Sustainable Intelligent Systems
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Fuzzy Computing in Data Science
Applications and Challenges
by Various Authors
Part of the Smart and Sustainable Intelligent Systems series
FUZZY COMPUTING IN DATA SCIENCE
This book comprehensively explains how to use various fuzzy-based models to solve real-time industrial challenges.
The book provides information about fundamental aspects of the field and explores the myriad applications of fuzzy logic techniques and methods. It presents basic conceptual considerations and case studies of applications of fuzzy computation. It covers the fundamental concepts and techniques for system modeling, information processing, intelligent system design, decision analysis, statistical analysis, pattern recognition, automated learning, system control, and identification. The book also discusses the combination of fuzzy computation techniques with other computational intelligence approaches such as neural and evolutionary computation.
Audience
Researchers and students in computer science, artificial intelligence, machine learning, big data analytics, and information and communication technology.
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Cognitive Computing Models in Communication Systems
by Various Authors
Part of the Smart and Sustainable Intelligent Systems series
COGNITIVE COMPUTING MODELS IN COMMUNICATION SYSTEMS
A concise book on the latest research focusing on problems and challenges in the areas of data transmission technology, computer algorithms, AI-based devices, computer technology, and their solutions.
The book provides a comprehensive overview of state-of-the-art research work on cognitive models in communication systems and computing techniques. It also bridges the gap between various communication systems and solutions by providing the current models and computing techniques, their applications, the strengths and limitations of the existing methods, and the future directions in this area.
The contributors showcase their latest research work focusing on the issues, challenges, and solutions in the field of data transmission techniques, computational algorithms, artificial intelligence (AI)-based devices, and computing techniques.
Readers will find in this succinctly written and unique book:
• Topics covering the applications of advanced cognitive devices, models, architecture, and techniques.
• A range of case studies and applications that will provide readers with the tools to apply cutting-edge models and algorithms.
• In-depth information about new cognitive computing models and conceptual frameworks and their implementation.
Audience
The book is designed for researchers and electronics engineers, computer science engineers, industrial engineers, and mechanical engineers (both in academia and industry) working in the fields of machine learning, cognitive computing, mobile communication, and wireless network system.
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Computational Intelligence in Sustainable Reliability Engineering
by Various Authors
Part of the Smart and Sustainable Intelligent Systems series
COMPUTATIONAL INTELLIGENCE IN SUBSTAINABLE RELIABILITY ENGINEERING
The book is a comprehensive guide on how to apply computational intelligence techniques for the optimization of sustainable materials and reliability engineering.
This book focuses on developing and evolving advanced computational intelligence algorithms for the analysis of data involved in reliability engineering, material design, and manufacturing to ensure sustainability. Computational Intelligence in Sustainable Reliability Engineering unveils applications of different models of evolutionary algorithms in the field of optimization and solves the problems to help the manufacturing industries. Some special features of this book include a comprehensive guide for utilizing computational models for reliability engineering, state-of-the-art swarm intelligence methods for solving manufacturing processes and developing sustainable materials, high-quality and innovative research contributions, and a guide for applying computational optimization on reliability and maintainability theory. The book also includes dedicated case studies of real-life applications related to industrial optimizations.
Researchers, industry professionals, and post-graduate students in reliability engineering, manufacturing, materials, and design.
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