Application of Immune Genetic Algorithm on Standard Library Building

摘要

Based on the analysis of standard system construction current situation, this paper proposes an improved genetic algorithm by combining the fuzzy neural network and the immune genetic algorithm, which can be used to solve the standard feature vector clustering, and better overcomes the premature phenomenon of general intelligent algorithms. Furthermore, this paper also builds a service-oriented standards library, which takes standard feature vectors as the main clustering index. The practical experiment shows that this smart genetic algorithm, with strong robustness, reliability and accuracy, is of certain reference value to the standard system construction innovation and development.