Construction of Intelligent University Quality Evaluation System for Ideological Work and Its Computer Applications

Construction of the intelligent university quality evaluation system for the ideological work and its computer applications is finalized in this paper. Novelties are reflected from listed points of views. (1) The similarity measurement between each sample point is the primary problem in the clustering algorithm. The similarity measure has the same meaning as the “distance” between the commonly mentioned samples, the novel calculation model for data distance is proposed. (2) For the three operators of the standard genetic algorithm, the choice of the operating system consumption is the largest, it is optimized by using the kernel functions. The experimental analysis has proven that the proposed model can achieve the better evaluation.