An Intelligent Gray Prediction Model Based on Fuzzy Theory

Abstract

In order to improve the forecasting effect of the gray prediction model, this paper combines the fuzzy theory to construct the gray prediction model and explores its forecasting accuracy. Moreover, this paper uses the entropy weight method to obtain the objective weight to correct the subjective weight, which makes the weight calculation more reasonable. In view of the uncertainty of the control signal of the research object, this paper introduces the gray system theory to conduct cluster analysis on the fire control computer and mainly introduces the general whitening weight function. Furthermore, this paper adopts the center point mixed with a triangular whitening weight function to carry out gray clustering according to the difficulty of defining the gray class boundary and gives the solution steps to obtain the intelligent gray prediction model. Finally, this paper verifies that the intelligent gray prediction model based on fuzzy theory has a good effect through experiments, which can effectively improve the prediction effect of the intelligent prediction model.