Research of the Gray GM(1,1) Model to Forecast the Temperature of Glass Kiln Based on Genetic Algorithm
Industrial kilns are widely used in various fields, the temperature controlling technology determines the quality of the product directly. This paper takes the glass kiln for example, it studies the application of the Gray GM(1,1) model based on the genetic algorithm, it use the genetic algorithm based on real-coded to replace the traditional least square method in order to optimize the parameter of the GM(1,1) model. The paper constructs the optimized GM(1,1) model of the temperature controlling system of the glass kiln through the matlab simulation and the forecast model attains satisfactory effects. The practical application proves that comparing with the PID controlling model, the GM(1,1) model based on genetic algorithm has improved in the fitting of raw data and the predicting precision of the future data, it provided reference to the optimization of the future fiLmace temperature controlling systems.
Grey system theory GM(1,1) model Genetic algorithm Glass kiln Temperature controlling Forecast
Jiaoyu Liu Yi Deng Kun Chen
College of Automation, Wuhan University of Technology, Wuhan, China 430070
国际会议
The Third International Workshop on Applied Matriz Theory(第三届国际矩阵分析与应用会议)
杭州
英文
773-779
2009-07-09（万方平台首次上网日期，不代表论文的发表时间）