A Review on Artificial Intelligence Methods
Artificial intelligence encompasses a broad body of knowledge that is difficult to define precisely. Expert systems are computer software systems that mimic the tasks routinely carried out by human experts. Computer algebra is an application of knowledge based system in which symbols, rather than merely numbers, can be manipulated by computers and the ensemble of the theory behind is also referred to as symbolic computation. Fuzzy set theory is a generalisation of classical set theory. Fuzzy logic representations try to capture the way humans represent the reason with real world knowledge. Artificial neural networks are simplified models of the nervous system. They are networks of highly interconnected simple computing elements that have the ability to respond to input stimuli and to learn to adapt to the environment. Evolutionary computation (EC) is the name of a collection of stochastic optimisation algorithms loosely based on concepts of biological evolutionary theory. They are based on the evolution of a population of potential solutions to a certain problem. Simulated annealing is an optimisation method that is able to arrive at global optimum.
KeywordsMembership Function Expert System Fuzzy Rule Fuzzy Inference System Inference Engine
Unable to display preview. Download preview PDF.
- Reznik Leonid, Fuzzy Controllers, Newnes, UK, 1997.Google Scholar
- Jang Jyh-Shing Roger, Sun Chuen-Tsai and Mizutani Eiji, Neuro-Fuzzy and Soft Computing, Prentice-Hall Inc, Simon & Schuster/A Viacom Company, USA, 1997.Google Scholar
- Vonk E., Jain L. C. and Johnson R. P., Automatic Generation of Neural Network Architecture Using Evolutionary Computation, World Scientific Publishing Co. Ltd., 1997.Google Scholar