A Method of Combination Forecasting Based on Inclusion Degree

Determining the weights in a combination forecasting is an important problem. We can translate the problem of computing weights into estimating the importance of attributes. Inclusion degree is one of the methods of computing importance of attributes. So this paper introduces a new method of computing weights based on inclusion degree. The example illustrates that the weights computed by inclusion degree have better usability than the weights computed by knowledge dependence property and entropy of information.