Intelligent Computing Techniques

The chapter presents various methods that can be qualified as intelligent computing ones. Different bio-inspired methods and techniques in the form of evolutionary algorithms (EAs), artificial immune systems (ANNs), particle swarm optimizers (PSOs) and artificial immune systems (AISs) are described. Moreover, information granularity attitude is introduced to model some uncertainties in material properties, geometry or boundary conditions. Granular computing techniques using interval numbers, fuzzy numbers and random variables are presented. Combinations of EAs and granular computing techniques in the form of fuzzy and stochastic EAS are proposed. Various hybrid computational intelligence algorithms combining different, intelligent or conventional techniques (e.g. gradient optimization methods) are described. A brief comparison of the effectiveness of selected bio-inspired optimization methods (PSO, EA and AIS) for the chosen test functions is also included.

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