Intelligent Algorithms of Automatic text Formation Based on Knowledge Point Association Analysis and Fuzzy Clustering

Intelligent algorithms for college automatic formation of English test paper based on the knowledge point association analysis and fuzzy clustering are designed in this manuscript. As a kind of evolutionary algorithm, differential evolutionary algorithm is based on real-number coding. The mathematical model of this paper mainly focuses on the three kinds of the operations of variation, crossover and selection. The biggest difference between differential evolutionary algorithm and genetic algorithm is that the variation operation in differential evolutionary algorithm is based on the difference vector of the chromosomes. Aiming at the risk that the association between data will be damaged due to the hard association rule processing of the traditional Boolean mining algorithms, fuzzy theory is introduced into the association rule mining model. The proposed method can achieve the test paper automatic formation based on the knowledge point association analysis. The performance is validated through the experimental analysis.