Intelligence Theories And Applications

This book is an up-to-date collection, in AI and environmental research, related to the project ATLAS. AI is used for gaining an understanding of complex research phenomena in the environmental sciences, encompassing heterogeneous, noisy, inaccurate, uncertain, diverse spatio-temporal data and processes. The first part of the book covers new mathematics in the field of AI: aggregation functions with special classes such as triangular norms and copulas, pseudo-analysis, and the introduction to fuzzy systems and decision making. Generalizations of the Choquet integral with applications in decision making as CPT are presented. The second part of the book is devoted to AI in the geo-referenced air pollutants and meteorological data, image processing, machine learning, neural networks, swarm intelligence, robotics, mental well-being and data entry errors. The book is intended for researchers in AI and experts in environmental sciences as well as for Ph.D. students.

Intelligence allows people to understand events and to shape their surrounding environment. This book delves deeper into the theories and applications of intelligence, showing it is a multifaceted concept —defined and explained differently by prestigious experts of various disciplines in their own research. The book provides interdisciplinary connections of intelligence as it relates to a variety of clearly outlined subject areas, and should lead to a deep understanding of the phenomenon as it pertains to practical applications in different domains. Contributors in this volume present results from evolutionary biology, mathematics, artificial intelligence, medicine, psychology, cultural studies, economy, political sciences and philosophy. Individual scientific models are integrated in an interdisciplinary concept of wisdom. This volume will help enhance the common understanding of intelligence for fellow researchers and scientists alike.

The first work to cover the entire field of intelligence--from historical beginnings through conceptual and practical development to the latest research. Experts in the field descibe various theories on intelligence from a historical perspective. Then, they discuss methods of measurement and controversial issues concerning the use of intelligence tests in clinical and educational fields. The final chapters cover the application of intelligence tests in every possible area.

Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering Presents coverage of key topics such as heuristic methods for data clustering, deep learning methods for data classification, and neural networks Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense

Howard Gardner's brilliant conception of individual competence is changing the face of education today. In the ten years since the publication of his seminal Frames of Mind , thousands of educators, parents, and researchers have explored the practical implications of Multiple Intelligences (MI) theory—the powerful notion that there are separate human capacities, ranging from musical intelligence to the intelligence involved in understanding oneself. Multiple Intelligences: The Theory in Practice brings together previously published and original work by Gardner and his colleagues at Project Zero to provide a coherent picture of what we have learned about the educational applications of MI theory from projects in schools and formal research over the last decade.

Presents extensions of papers reported in the proceedings of the 1989 SPIE symposium. In the applications group articles cover the use of expert systems in computer aided education, hydrocarbon (oil) exploration, satellite image analysis for oceanography, particle beam accelerator tuning, design of internal combustion engines. Papers in the theory group cover theories, algorithms, architectures and software tools that can be used for modules within future systems.

This book examines the fundamentals and technologies of Artificial Intelligence (AI) and describes their tools, challenges, and issues. It also explains relevant theory as well as industrial applications in various domains, such as healthcare, economics, education, product development, agriculture, human resource management, environmental management, and marketing. The book is a boon to students, software developers, teachers, members of boards of studies, and researchers who need a reference resource on artificial intelligence and its applications and is primarily intended for use in courses offered by higher education institutions that strive to equip their graduates with Industry 4.0 skills. FEATURES: Gender disparity in the enterprises involved in the development of AI-based software development as well as solutions to eradicate such gender bias in the AI world A general framework for AI in environmental management, smart farming, e-waste management, and smart energy optimization The potential and application of AI in medical imaging as well as the challenges of AI in precision medicine AI’s role in the diagnosis of various diseases, such as cancer and diabetes The role of machine learning models in product development and statistically monitoring product quality Machine learning to make robust and effective economic policy decisions Machine learning and data mining approaches to provide better video indexing mechanisms resulting in better searchable results ABOUT THE EDITORS: Prof. Dr. P. Kaliraj is Vice Chancellor at Bharathiar University, Coimbatore, India. Prof. Dr. T. Devi is Professor and Head of the Department of Computer Applications, Bharathiar University, Coimbatore, India.

This book presents selected proceedings of ICCI-2017, discussing theories, applications and future directions in the field of computational intelligence (CI). ICCI-2017 brought together international researchers presenting innovative work on self-adaptive systems and methods. This volume covers the current state of the field and explores new, open research directions. The book serves as a guide for readers working to develop and validate real-time problems and related applications using computational intelligence. It focuses on systems that deal with raw data intelligently, generate qualitative information that improves decision-making, and behave as smart systems, making it a valuable resource for researchers and professionals alike.