Similarity Measurement and Analysis of Triangular Cloud Models

Abstract

The similarity of triangular fuzzy numbers could be served as a measurement of similarity between two triangular cloud models. However, it has been found that existing methods for describing the similarity of triangular cloud models has the drawbacks that can’t make full use of utilizing graphic information and assigning inappropriate weights to distances through research and analysis. The method proposed in this literature has adjusted the weight of distance similarity aim to ensure that the characteristic information of the model will not be covered. In addition, the proposed method provides a measurement to describe geometric shape bases on the expected curve included angle of the triangular cloud model. On the foundation of taking abundantly the similarity of distance and shape into account, we provide the measurement to achieve better accuracy. The feasibility and effectiveness of the proposed method have been demonstrated through the time series of KNN algorithm.