Forecasting CO2 Output from Gas Furnace by Grey Prediction Model IGMC (1, n)

Abstract

A new prediction model, the interval grey prediction model with convolution integral, abbreviated as IGMC (1, n), is presented in this paper. Improvements upon the existing grey prediction model GM (1, n) are made to a large extent and the messages for a system can be supplied sufficiently. The relationship between input series and output series is constructed sufficiently by IGMC (1, n) and high accuracy of indirect measurement or prediction for a dynamic system can be broadly anticipated. A measure for assessing the reliability of the predicted values is required and a common approach is through the use of interval prediction. These are the upper and lower confidence limits of the predicted values. The point and interval forecasts of the CO2 output from gas furnace can be made by IGMC (1, n) with the input methane gas rate acting as the associated series. The results show that the prediction accuracy of the CO2 output from gas furnace is satisfactory.