基于COWA算子的相关性区间组合预测优化模型及其近似求解

Optimization model of correlation interval combination forecasting based on COWA operator and its approximate solutions

在Holt指数平滑模型、多层感知器(MLP)模型及支持向量机(SVM)模型三种区间预测方法的基础上,通过引进COWA算子和相关系数的概念,构建基于相关系数的区间型最优组合预测模型,探讨了模型的若干性质.同时利用相关系数作为测度单点预测方法在组合预测中的贡献指标,结合合作对策中的Shapley值,给出相应的最优组合预测模型的近似求解.利用西德克萨斯中质原油现货价格数据验证了模型的可行性与有效性,并分析了COWA算子中的态度参数的灵敏度.

On the basis of Holt exponential smoothing model,multi-layer perceptron(MLP)model and support vector machine(SVM)model,an interval optimal combination forecasting model was built by introducing the concept of COWA operator and correlation coefficient and some properties of the model were discussed.At the same time,the correlation coefficient was used as the contribution index of the single point forecasting method in the combined forecasting,and the Shapley value in the cooperative game was combined to give the approximate solution of the corresponding optimal combined forecasting model.The data of WTI spot price were used to demonstrate the feasibility and effectiveness of the model,and the attitude parameters on COWA operator was done with the sensitivity analysis.