Consumer Decision-Making Power Based on BP Neural Network and Fuzzy Mathematical Model

In real life, because of the uncertainty of risk, incomplete information, perceived cost, and other factors, there are irrational behaviors in the decision-making power of consumers, so it is of great practical significance to study the decision-making power of consumers in the choice of countermeasures and personalized product recommendation. The purpose of this paper is to analyze the decision-making power of consumers based on the BP neural network and fuzzy mathematical model. First, the basic theory of artificial neural network and the concepts of set theory and fuzzy reasoning of fuzzy mathematics are described. Second, the behavior prediction model with the equal emphasis on rationality and irrationality and the integration of artificial neural network and fuzzy mathematics are constructed. The comments of a certain mobile phone are selected as the experimental objects to analyze the decision-making reasoning and prediction of individual consumers in the network and the decision-making reasoning of group consumers in the network, the experimental results show that through Mamdani reasoning, behavioral intention=5.72. Through the fuzzy set processing, it is finally determined that the consumer's purchase intention is close to the VT mode, which is "very inclined." In the first method, the user's recognition rate of product C1 is 82%, and in the second method, the user's recognition rate is 55%. The comparison of the two methods is in line with the expectation. The first method extracts the user's emotion and evaluation information from the comments, fully considers the personalized needs of consumers, and is closer to the prediction results of the system.