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Soft Computing

Soft Computing

Intelligent Systems are those that incorporate aspects usually associated to intelligent human behavior, such as perception, reasoning, learning, evolution, adaptation, autonomy, social interaction and pro-activity. Historically speaking, this is the main focus of interest in Artificial Intelligence. However, the dynamic contemporary world has turned such characteristics a requirement in virtually every system. As time evolves and given the fast technological development, intelligent systems are becoming even more feasible as they take part in our daily lives. Additionally, their great potential of application in different knowledge areas and sectors of the society turns its development even more multidisciplinary, with contributions from many different areas, not only engineering, but also from human and social sciences. The rapid increase in complexities in engineering has urged the mankind to exploit advanced and efficient technologies resulting in the emergence of intelligent systems which include Bacterial Foraging Optimization (BFO), Particle Swarm Optimization (PSO), Fuzzy Logic (FL), Genetic Algorithms (GA), Artificial Neural Networks (ANN). Intelligent system is a collection of techniques spanning many fields that fall under various categories in computational intelligence to some extent draw inspiration from natural phenomena. ANN tries to mimic the animal brain, GA is founded on the dynamics of Darwian evolution, FL is motivated by the highly imprecise nature of human , while BFO- PSO are on swarm intelligence.

Bacterial foraging, Particle swarm optimization, Fuzzy logic, Artificial neural networks, Genetic algorithms, Wavelet analysis.