Handbook Of Research On Advanced Hybrid Intelligent Techniques And Applications

Conventional computational methods, and even the latest soft computing paradigms, often fall short in their ability to offer solutions to many real-world problems due to uncertainty, imprecision, and circumstantial data. Hybrid intelligent computing is a paradigm that addresses these issues to a considerable extent. The Handbook of Research on Advanced Hybrid Intelligent Techniques and Applications highlights the latest research on various issues relating to the hybridization of artificial intelligence, practical applications, and best methods for implementation. Focusing on key interdisciplinary computational intelligence research dealing with soft computing techniques, pattern mining, data analysis, and computer vision, this book is relevant to the research needs of academics, IT specialists, and graduate-level students.

Data is more valuable than ever in the twenty-first century, and tremendous amounts of data are being generated every second. With a fast-growing information industry, engineers are required to develop new tools and techniques that increase human capabilities of mining useful knowledge from the vast amounts of data. Optimized Genetic Programming Applications: Emerging Research and Opportunities is an essential reference source that explores the concept of genetic programming and its role in managing engineering problems. It also examines genetic programming as a supervised machine learning technique, focusing on implementation and application. As a resource that details both the theoretical aspects and implementation of genetic programming, this book is a useful source for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.

Recent improvements in business process strategies have allowed more opportunities to attain greater developmental performances. This has led to higher success in day-to-day production and overall competitive advantage. The Handbook of Research on Manufacturing Process Modeling and Optimization Strategies is a pivotal reference source for the latest research on the various manufacturing methodologies and highlights the best optimization approaches to achieve boosted process performance. Featuring extensive coverage on relevant areas such as genetic algorithms, fuzzy set theory, and soft computing techniques, this publication is an ideal resource for researchers, practitioners, academicians, designers, manufacturing engineers, and institutions involved in design and manufacturing projects.

Nature-inspired computation is an interdisciplinary topic area that connects the natural sciences to computer science. Since natural computing is utilized in a variety of disciplines, it is imperative to research its capabilities in solving optimization issues. The Handbook of Research on Natural Computing for Optimization Problems discusses nascent optimization procedures in nature-inspired computation and the innovative tools and techniques being utilized in the field. Highlighting empirical research and best practices concerning various optimization issues, this publication is a comprehensive reference for researchers, academicians, students, scientists, and technology developers interested in a multidisciplinary perspective on natural computational systems.

Soft computing and nature-inspired computing both play a significant role in developing a better understanding to machine learning. When studied together, they can offer new perspectives on the learning process of machines. The Handbook of Research on Soft Computing and Nature-Inspired Algorithms is an essential source for the latest scholarly research on applications of nature-inspired computing and soft computational systems. Featuring comprehensive coverage on a range of topics and perspectives such as swarm intelligence, speech recognition, and electromagnetic problem solving, this publication is ideally designed for students, researchers, scholars, professionals, and practitioners seeking current research on the advanced workings of intelligence in computing systems.

Optimization techniques have developed into a modern-day solution for real-world problems in various industries. As a way to improve performance and handle issues of uncertainty, optimization research becomes a topic of special interest across disciplines. Problem Solving and Uncertainty Modeling through Optimization and Soft Computing Applications presents the latest research trends and developments in the area of applied optimization methodologies and soft computing techniques for solving complex problems. Taking a multi-disciplinary approach, this critical publication is an essential reference source for engineers, managers, researchers, and post-graduate students.

Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.