Computational Intelligence in Modeling Complex Systems and Solving Complex 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. [...]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. (2) The rule base in the “head of the cat” is calculating the likely future position of the mouse at the time of the cat grasping it. (Because of the uncertainty involved, this future position may be given only by an estimated area.) (3) The cat searches the estimated future position area of the mouse systematically until it catches the mouse. [...]accurate modeling of this complicated system and its cost-effective treatment and the reuse decision is very important, because this optimization process is related to economic expenditure, societal health, and environmental deterioration. [...]in the numerical simulations, compared with the ordinary PSO and other more classical population based optimization algorithms, namely, GA and DE, it is evidenced that the proposed LCPSO has lower dimensionality, faster speed of convergence, and higher accuracy, while providing smoother control variables.