基于直觉模糊线性方程组的IFTS 预测方法

针对模糊时间序列预测理论对不确定性数据集的实时模糊变化趋势研究存在的不足, 规范了直觉模糊时间序列的定义, 提出了基于直觉模糊线性方程组的直觉模糊时间序列预测方法. 所提出的算法将模型的求解转化为一系列带有约束的线性规划问题, 准确地反映了序列数据随时间发展变化的模糊关联规律, 简化了预测模型的复杂度, 提高了时间序列预测的精度, 扩展了直觉模糊时间序列预测理论的应用范围. 最后, 通过仿真实验验证了所提出方法的有效性和优越性.

Forecasting method of IFTS based on intuitionistic fuzzy linear equations

To the study deficiency of the fuzzy time series forecasting theory for real-time fuzzy variation trend of uncertain data sets, the intuitionistic fuzzy time series forecasting model is presented by using the intuitionistic fuzzy system of linear equations. In the proposed approach, the solution to the models is transformed into the linear programming problem. Then, the fuzzy connection rules of the sequence dates changing with time are reflected precisely. Meanwhile, the forecasting accuracy of time series in the complex environment is improved, thus greatly extending the intuitionistic fuzzy time series forecasting application. Finally, the classical instance verifies the effectiveness and superiority of the proposed method.