Bøger i Computational Intelligence Techniques serien

This book explains different aspects of the current research on computational intelligence technologies applied in the field of medical diagnosis. It discusses critical issues related to the medical diagnosis like uncertainties in the medical domain, problems in the medical data especially dealing with time-stamped data.

Advances in Graph based Natural Language Processing (NLP) and Information Retrieval (IR) tasks have shown the importance of processing Graph of Words.

The book intends to cover various problematic aspects of emerging smart computing and self-adapting technologies comprising of machine learning, artificial intelligence, deep learning, robotics, cloud computing, fog computing, data mining algorithms, including emerging intelligent and smart applications related to these research areas.

This book aims to build and prompt the field of Data Analytics towards decision making in terms of models and algorithms, theoretical concepts, applications, experiments in relevant domains or focussed on specific issues, including concepts of Database Technology, Machine learning, Knowledge-based system, High Performance Computing etc.

This book provides in-depth knowledge to solve engineering, geometrical, mathematical, and scientific problems with the help of advanced computational methods with focus on mechanical and materials engineering. It covers pertinent topics under sections on design and fluids, thermal engineering and materials engineering.

Smart Computational Intelligence in Biomedical and Health Informatics presents state-of-art innovations, research, design and implementation of methodological and algorithmic solutions to data processing problems, designing, and analysing evolving trends in health informatics and computer-aided diagnosis.

This book focusses on computational intelligence approaches as applicable in varied areas of software engineering such as software requirement prioritization, cost estimation, reliability assessment, defect prediction, maintainability and quality prediction, size estimation, vulnerability prediction, test case selection, and so forth.