Get Applied Soft Computing Technologies: The Challenge of PDF

By Ajith Abraham

ISBN-10: 3540316493

ISBN-13: 9783540316497

ISBN-10: 3540316620

ISBN-13: 9783540316626

This quantity offers the lawsuits of the ninth on-line global convention on gentle Computing in commercial functions, hung on the area extensive net in 2004. It contains lectures, unique papers and tutorials offered in the course of the convention. The e-book brings jointly amazing learn and advancements in smooth computing, together with evolutionary computation, fuzzy common sense, neural networks, and their fusion, and its purposes in technological know-how and know-how.

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De Falco1 , E. Tarantino1 , A. Della Cioppa2 and F. Fontanella3 1 Institute of High Performance Computing and Networking – CNR Via P. it 2 Dept. it 3 Dept. it Summary. Most of the classical clustering algorithms are strongly dependent on, and sensitive to, parameters such as number of expected clusters and resolution level. To overcome this drawback, a Genetic Programming framework, capable of performing an automatic data clustering, is presented. Moreover, a novel way of representing clusters which provides intelligible information on patterns is introduced together with an innovative clustering process.

1 Selection of Classifier Neural networks are usually employed to classify patterns based on learning from examples. , are available. The singlelayer Hopfield and Hamming nets are normally used with binary input and output under supervised learning. The Carpenter/Grossberg net, however, implements unsupervised learning. The single-layer perceptron can be used with multi-value input and output in addition to binary data. A serious disadvantage of the single-layer network is that complex decision may not be possible.

V. Barai and P. Agrawal to formulate the classification problem of weld from non-welds, feature extraction was essential. Three features were defined for each object in line image and they are as follows. x The width (x1) x The mean square error between the object and its Gaussian intensity plot (x2) x The peak intensity (x3) Feature space is generally of a much lower dimension than the original data space. The feature extraction algorithm consists of three major steps: x A trough detection algorithm is applied to find the troughs associated with each object detected.

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Applied Soft Computing Technologies: The Challenge of Complexity (Advances in Soft Computing) by Ajith Abraham


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