Download Applied Soft Computing Technologies: The Challenge of by Ajith Abraham PDF

By Ajith Abraham

This quantity provides the lawsuits of the ninth on-line international convention on tender Computing in business functions, hung on the area vast net in 2004. It comprises lectures, unique papers and tutorials awarded through the convention. The booklet brings jointly notable learn and advancements in delicate computing, together with evolutionary computation, fuzzy common sense, neural networks, and their fusion, and its functions in technological know-how and expertise.

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Step 1: Before any other MPI functions can be called, the function MPI_Init must be called. It allows systems to do any special set up so that the MPI library can be used. Calling MPI_Comm_rank and MPI_Comm_size respectively returns rank of the processor and the number of processor. Step 2: From a file having information about the architecture, following values are read and memory is allocated accordingly. e. if the processor is Master Processor, it distributes the available number of units among other processors, based on the size of Kohonen layer and total number of processors available.

De Falco et al. subtrees. If a corresponding nonterminal node cannot be found in the second parent, the crossover takes place on different nodes. Differently from classical GP, the mutation works on any obtained offspring by randomly choosing a nonterminal node in the individual to be mutated, and then the corresponding production rule is activated in order to generate a new subtree. Depending on the nonterminal symbol chosen, this operation can result either in the substitution of the related subtree (macro–mutation) or in a simple substitution of a leaf node (micro–mutation).

Two variants of parallel neuro classifier were developed on PARAM 10000. They are Single Architecture Single Processor and Single Architecture Multiple Processor. Further, the weld defect classification application is demonstrated successfully using developed parallel classifiers. The study revealed interesting observations. Systematic data analysis helped in completing data set and also could eliminate the poor data examples. Clean data set gave better performance than original data set. Single Architecture Single Processor found to be better than Single Architecture Multiple Processor in terms of computational time.

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