By Ajith Abraham
This quantity provides the lawsuits of the ninth on-line global convention on gentle Computing in commercial functions, hung on the area huge internet in 2004. It contains lectures, unique papers and tutorials provided through the convention. The ebook brings jointly impressive examine and advancements in smooth computing, together with evolutionary computation, fuzzy common sense, neural networks, and their fusion, and its functions in technology and know-how.
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Extra resources for Applied Soft Computing Technologies: The Challenge of Complexity (Advances in Soft Computing)
In a broad sense, NDE can be viewed as the methodology used to assess the integrity of the structure without compromising its performance. Recently, many studies have reported results where signal processing and neural networks (NN) were used in characterizing defects of weld based using NDE data (Rao et al. 2002, Liao and Tang 1997, Nafaa et al. 2000, Stepinski and Lingvall 2000). Radiographic testing is one of the most popular NDE techniques adopted in inspecting welded joints. Usually real-time radiographic weld images are produced during radiographic testing of welded component (Bray and Stanley 1989).
26 Number of misclassified examples 140 45 14 Average error of resubstitution is found to be more than that of K-fold and hold-out. But as in resubstitution the network is tested for the same data set for which it is trained, so the error has to be less than the error from other methods, where network is tested for new data. This raised the question about the accuracy of the original data set. The features of some examples may have some abnormality. To check this, a frequency graph (Figure 1) between “Numbers of times a example is misclassified in 21 different architectures” Vs “Number of examples” is drawn.
R. Soc. Sci. Lettres de Varsovie, 23, 1930, 51-77. 8. M. Mendel, On a 50% savings in the computation of the centroid of a symmetrical interval type-2 fuzzy set , Information Sciences, In press, Available online 2 July 2004. 9. R. Moore, Interval Analysis, Prentice Hall, Englewood Cliffs, NJ, 1966. 10. K. Pal, A. ), Rough Fuzzy Hybridization. A New trend in Decision-Making, Springer Verlag, Singapore, 1999. 11. Z. Pawlak, Rough sets, Int. J. Comput. Inform. Sci. 11, 1982, 341–356. 12. Z. Pawlak, Rough Sets.