Fuzzy comprehensive evaluation algorithm according to individuals of the same class of things has a greater similarity, based on the principles of individual differences in different classes, make the greater similarity degree of data or indicators with classify, establish clear category boundaries, according to similarity of indicators, to cluster factor, to form relationship clusters of
... [Show full abstract] arbitrary shape, and can freely enter the order Index, analysis applicability "flipped classroom" English Teaching Model accurately. Set fuzzy factor by the membership analysis; obtain an evaluation value algorithm, Reference evaluation analysis indicators. Evaluation results were analyzed, analysis the evaluation results.
