Research on the big data mining algorithm based on modified neural network and structure optimized genetic algorithm
Yi Liang, Xiangyun Cai, Zilun Xiong · 2016
Data mining has become one of the widely researched fields off late especially with the increase in technological advancements which have caused the volume of data to be stored and processed for query based applications or decision based processes to increase in great multiplicative measures. Data mining refers to the process of extraction of useful information from a pool of data. Various algorithms have been proposed in the past for the mining process out of which neural based mining algorithms are predominant. The proposed work utilizes BPNN integrated with a genetic optimization algorithm for minimizing and bringing about a optimal search value. An elaborate review of the types and existing techniques has been presented in this paper. The proposed algorithm has been tested with iris data set and results obtain indicate a comparatively higher efficiency based on classification and reduction of computation time. The proposed results have been compared against conventional techniques like SVM classifier based mining and neural network in its stand alone architecture.