Computational intelligence (CI) is a set of nature-inspired computational methodologies and approaches to address complex real-world problems, to which mathematical or traditional modeling is not useful. CI provides a consortium of methodologies that works synergistically and provides, in one form or another, flexible information processing capabilities for handling real life ambiguous situations. Its aim is to exploit the tolerance for imprecision, uncertainty, approximate reasoning and partial truth in order to achieve tractability, robustness, low cost solutions, and close resemblance to human like decision making. Fuzzy Logic, Rough Sets, Artificial Neural Networks and Evolutionary Algorithms are the principal components of CI paradigm. The relevance of CI research in pattern recognition, machine learning, image processing, data mining and control problems, among others, along with different real life applications is evident worldwide.
Due to advent in technology, domains like data mining, natural language processing, e-commerce, bioinformatics, intelligent manufacturing systems, telecommunication, and engineering applications may also be considered as prospective candidates for CI applications.
Fuzzy Set and Systems