The Improvement Study Of Fuzzy Comprehensive Evaluation Algorithm And Application Based On Factor Analysis

Currently, with the cloud become more and more popular, "big data" has been more concerned. But the arrival of "big data" era, on the one hand it gives us amounts of wealth, on the other hand it also requires us about the hardware and software conditions strictly. Handle massive unstructured data, can’t suitable for all of the traditional statistical analysis techniques. Traditional technologies encounter new challenges that require innovation in order to survive.As the characteristics of "big data", the preliminary results that find out from the data, will be the basis for analyzing follow-up. Such operations, fuzzy comprehensive evaluation method can be fully qualified, but the only thing is the data is far too large, it is inefficient, and therefore factor analysis techniques, use for reducing dimension, can appear to play a significant role in this matter.From those purpose above, in order to improve the efficiency of data analysis and reduce manual operation, we follow the core idea of factor analysis, and get the achievements as follows:1. Factors set recombination, using factor analysis to make a scientific analysis of the target‘s factors, decomposition and recombined into a new factor set, the mutual exclusion between factors;2. Dynamic comprehensive evaluation, using the characteristics of big data, instead the expert opinion by the characteristics of the sample, reduce man-made interference and makes the whole evaluation process is more fit to reality;3. Common factor weight vectors, using common factor, as the weight of fuzzy comprehensive evaluation algorithm, to avoid the manual operation, make the result more scientific and more accuracy;4. Steps adjustment, change the order of steps to make the improved algorithm more clear, cohesive more closely, and also more reasonable.Ultimately presents a new algorithm that include computer-implemented, data analysis and fast decision-making, mostly used to quickly get fuzzy comprehensive assessment which process involves anti-fuzzy, principal component extraction, calculate the composite score, result fuzzy, and the end of this article, show out the whole process of new algorithm by certain examples.