Evaluation of Design Behavior Factors Weighting Based on AHP-Entropy Weighting Method in Artificial Intelligence Perspective

In the context of the information era of rapid development of artificial intelligence, the frequency of data updating and the role of data is always in dynamic change, and the research of design behavior is facing new opportunities and challenges. This paper focuses on the study of factors affecting design behavior in the view of artificial intelligence, aiming to analyze the weight of each influencing factor accurately. Through the hierarchical analysis method (AHP), its advantage of quantitative subjective judgment is brought into play, and experts' subjective perception of the importance of design behavior factors is deeply explored. At the same time, combined with the entropy weight method, the weights are determined based on the objective information entropy of the data, which effectively makes up for the lack of subjective assignment. Using the AHP-entropy weight method combined with these two methods, a comprehensive and systematic weight evaluation of design behavior factors is carried out to improve the efficiency of multi-attribute decision-making.