By Da Duan, Paolo F Fantoni, Martine De Cock, Mike Nachtegael, Etienne E Kerre
FLINS, initially an acronym for Fuzzy good judgment and clever applied sciences in Nuclear technological know-how, is now prolonged to utilized synthetic Intelligence for utilized study. The contributions to the 7th within the sequence of FLINS meetings contained during this quantity conceal cutting-edge study and improvement in utilized synthetic intelligence for utilized examine more often than not and for power/nuclear engineering specifically.
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Extra info for Applied Artificial Intelligence
II] T. Berners-Lee, J. Hendler, O. Lassila, "The Semantic Web", Scientific American, May 2001. T H E ROLE OF SOFT C O M P U T I N G I N A P P L I E D SCIENCES P. P. edu This talk intends to introduce a spectrum of applications of the soft computing methodologies in applied sciences, which include the areas of computational biology, bioinformatics, chemistry, geology, mechanics, automatic and intelligent controls, operations research and economics. In particular, the fusion of several pillars of soft computing will be emphasized, especially those integrations which provide improved performance of the overall systems.
Sci. 136 (1-4) (2001). 6. M. E. Kerre, A new class of fuzzy modifiers, Proceedings of IEEE-ISMVL (2000). 7. J. Valente de Oliveira, Semantic constraints for membership function optimization, IEEE Trans. Systems, Man, Cybern. 29 (1999). 8. H. Shi, R. Ward, N. Kharma, Expanding the definitions of linguistic hedges, IFSA World Congress and 20th NAFIPS Int. Conf. (2001). 9. F. Herrera, M. L. Verdegay, Tackling real-coded genetic algorithms: Operators and tools for behavioral analysis, Artificial Intell.
There are three possible outcomes in applying soft computing methods in many examples of applications. The first class of examples illustrate a similar performance as compared with the conventional methods. The second class of examples illustrate much better performance by using soft computing methods. Finally, there is a class of examples in which the conventional techniques simply do not exist. In other words, soft computing methodologies offer the only viable solution due to their ability to deliver solutions for non-reductionistic and highly nonlinear problems.