PSoC design in GM(1,1) error analysis and its application in temperature prediction

In the study of prediction filed, no matter what methods we used, the main purpose is to minimize the prediction error; however, the goals cannot be fulfilled completely. Even we choose GM(1,1) model, which in the newest soft computing method, we also need to minimize the prediction error. Hence, in this paper, we focus on the influence parameter alpha in GM(1,1) model in the first, then, analyze the characteristics of alpha step by step, and use numerical method to find the prediction error corresponding with alpha value. Second, after the mathematics model is presented, we use PSoC to design a GM(1,1) error analysis model, which based on the characteristic of GM(1,1) model. Also an example, which is temperature prediction case is given to assist us to implement our approach in the final section.