Computational Intelligence (CI) can be framed as a heterogeneous domain that harmonized and coordinated several technologies, such asprobabilistic reasoning, artificial life, multi-agent systems, neuro-computing, fuzzy systems, and evolutionary algorithms. Integrating several isciplines, such as Machine Learning (ML), Artificial Intelligence (AI), Decision Support Systems (DSS), and Database Management Systems (DBMS) increases the CI power and impact in several engineering applications. This book series provides a well-standing forum to discuss the characteristics of CI systems in engineering. It emphasizes on the development of CI techniques and their role as well as the state-of-the- art solutions in different real world engineering applications. The book series is proposed for researchers, academics, scientists, engineers and professionals who are nvolved in the new techniques of CI. CI techniques including artificial fuzzy logic and neural networks are presented for biomedical image processing, power systems, and reactor applications.
Himansu Das, Jitendra Kumar Rout, Suresh Chandra Moharana, Nilanjan Dey
November 19, 2020
The objective of this edited book is to share the outcomes on various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances of machine intelligent techniques such as data streaming, classification, ...
Sudhir Kumar Sharma, Bharat Bhushan, Narayan C. Debnath
October 08, 2020
Integration of IoT (Internet of Things) with big data and cloud computing has brought forward numerous advantages and challenges such as data analytics, integration, and storage. This book highlights these challenges and provides an integrating framework for these technologies, illustrating the ...
Nilanjan Dey, Sanjeev Wagh, Parikshit N. Mahalle, Mohd. Shafi Pathan
June 05, 2019
The book focuses on how machine learning and the Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are used in heterogeneous IoT environments have been discussed including interpretation, context ...