A Theil coefficient-based combination prediction method with interval heterogeneous information for wind energy prediction

Author:

Wu Qiongling1,Lin Jian2,Zhang Shaohan1,Tian Zhiyong3

Affiliation:

1. College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou, China

2. The Digital Fujian Research Institute of Big Data for Agriculture and Forestry, Fujian Agriculture and Forestry University, Fuzhou, China

3. Beijing Intelligent Logistics System Collaborative Innovation Center, Beijing Wuzi University, Beijing, China

Abstract

This paper constructs the continuous-Young optimal weighted arithmetic averaging (C-YOWA) operator and the continuous-Young optimal weighted geometric (C-YOWG) operator based on definite integral and Young inequality. A series of special cases and main properties of the proposed aggregation operators are also investigated. In order to integrate heterogeneous interval data and obtain more accurate prediction results, the heterogeneous interval combination prediction (HICP) model based on C-YOWA operator, C-YOWG operator and Theil coefficient is proposed. The HICP model consider not only the existence of both additive and multiplicative interval information, but also the preference information of experts. Finally, the model is applied to the empirical analysis of wind energy prediction. The comparison of results shows that the established model can effectively improve the accuracy of prediction.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference41 articles.

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