Construction of Winter Wheat Optimal Irrigation Yield Prediction Model Based on DM Algorithm
Lu Hong Huang, Xiaodong Li · Procedia Computer Science · 2022
The practice shows that there is a close and nonlinear correlation between the greenness and yield of winter wheat. As we all know, the agricultural production system is a complex system with a high degree of uncertainty, including soil fertility grade, climate, domain management and many other factors, which brings difficulties to the prediction of winter wheat yield. This paper studies the construction of winter wheat optimal irrigation yield prediction model based on DM algorithm. In this article, ANN technique is used to fit and describe the relationship between green degree and yield of winter wheat, and a yield model is established. The algorithm used in this paper is BP neural network, which uses physical devices to simulate some organizations and functions of biological neural network, that is, many neurons with simple functions are interconnected to form a network system that can simulate human learning, decision-making, recognition and other functions. The steepest descent means is used to continuously adjust the weight and threshold of the network through back propagation to minimize the sum of squares of errors of the network. Through the research of this paper, the algorithm in this paper is effective and suitable for use.