This paper presents a Distributed data mining platform on Grid services pool (DDM-GSP), which combines grid services pool with distributed data mining to solve problems of traditional distributed data mining. Meanwhil...
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This paper presents a Distributed data mining platform on Grid services pool (DDM-GSP), which combines grid services pool with distributed data mining to solve problems of traditional distributed data mining. Meanwhile, this paper implements parallel distributed genetic algorithm to resolve complex function optimization on basis of DDM-GSP. Simulation experiments show that for concentrative mining, with the augmentation of population sizes, the convergent speed of standard genetic algorithm is improved by 39 times and computing time is improved by 81 times. However, improvement of population dimensions, the average consumptive time of distributed genetic algorithm on grid is about 31.7% less than standard concentrative genetic algorithm, while about 28.6% by contrast to traditional parallel genetic algorithm.
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