Comparison Some Estimation Methods Of GM(1,1) Model With Missing Data and Practical Application

Abstract

This paper presents a grey model GM(1,1) of the first rank and a variable one and is the basis of the grey system theory , This research dealt  properties of grey model and a set of methods to estimate parameters of the grey model GM(1,1)  is the least square Method (LS) , weighted least square method (WLS), total least square method (TLS) and gradient descent method  (DS). These methods were compared based on two types of standards: Mean square error (MSE), mean absolute percentage error (MAPE), and after comparison using simulation the best method was applied to real data represented by the rate of consumption of the two types of oils a Heavy fuel (HFO) and diesel fuel (D.O) and has been applied several tests to make sure the accuracy of grey model GM(1,1). The most important results we have reached  (LS) is the best method to estimate the parameters of this model, as when applied proved to obtaining the best results and used this method in the process of addressing one of the problems of this data and missing values, and also used in the forecasting process for   future values.