Computational Intelligence in Modeling Complex Systems and Solving Complex Problems
László Tamás Kóczy, Jesús Medina, Marek Reformat, Kok Wai Wong, Jin Hee Yoon · Complexity · 2019
In the special issue on computational intelligence (CI) and complex systems a plethora of approaches is presented on how to apply computation intelligence in modeling, control, decision support, and optimization of complex problems.e three main components of CI are fuzzy systems, evolutionary and population based algorithms, and artificial neural networks.In addition, there are other related techniques, among others, chaos theory and subjective probability.O en, the combinations and hybrids of these methods, sometimes complemented by classic mathematical or modeling tools, turn out to be most efficient in the solution of real life problems.In the series of 26 papers, illustrations for almost all of these methods may be found.What is the main goal and target in these research problems?Several years ago the Lead Guest Editor published a study on how to use fuzzy rule based systems as tools in solving what was called (maybe, in a somewhat exaggerating way) the "Key Problem of Engineering," even though "Key Problem of Engineering" is not a term accepted by consensus in the relevant literature.Moreover, the term Engineering has many different interpretations, the narrowest one referring to technological sciences and disciplines only, while in various broader interpretations it includes computer science, agricultural engineering, social engineering, and certain aspects of economic models.In the present special issue, Engineering may be replaced by the concepts "Applied Problems," "Real Life Applications," or similar.