Multi-pipeline Processing Algorithm for Intensive Data Stream Processing of educational data using Soft Computing Techniques

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Muzammil H Mohammed


Information mining of monetary administration upheld by soft computing techniques can offer some hypothetical help for the supportable improvement of certain undertakings in monitoring smart girds. To consummate this innovation of our country, in this paper, the important speculations were perceived. Further, the framework was built and the information base was developed. Then, at that point, the development undertakings were taken as instances of the examination, and the information mining was completed for financial administration. The examination results give the premise to advancement of the undertaking. The reason for this investigation is to offer specialized help and reference for follow-up research. The information stream in the time of huge information is expanding, straightforwardly prompting the expanded trouble of the clustering examination. Considering this, the grouping calculation of information stream mining dependent on multi-pipeline processing was contemplated and investigated in this paper. Above all else, the clustering cycle was investigated and the multi-pipeline processing has been presented with the qualities of the average grouping calculations by extended particle swarm optimization (PSO). Finally, the regular grouping calculation and the clustering calculation for information stream mining dependent on the pipeline advancement also been addressed. The outcomes show that the grouping calculation dependent on the multi-pipeline is useful to further develop the clustering virtue in control system.

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