Grey modeling based on the transformation of Aarc cot x+B function

Abstract

Purpose – The purpose of this paper is to utilize the proposed function transformation to make the original data series meet the properties of smooth ratio being lessen and stepwise ratio deviation being reduced, so that to improve the accuracy of grey forecasting model. Design/methodology/approach – According to the characteristics of anti-cotangent functional graph variation, the theory of functional transformation and grey system modeling, the authors proposed a grey model based on the transformation of Aarc cot x+B function. Findings – The calculated result of practical example shows that the proposed method is both valid on improving fitting effectiveness and forecasting accuracy. Practical implications – The proposed method in this paper can effectively improve the accuracy of forecasting of high-growth original data series (derivative of data series is not only greater than 1 but also increasing). Originality/value – The paper succeeds in providing an effective function transformation to make the smooth ratio and stepwise ratio deviation reduced significantly.