桂林电子科技大学学报2017，Vol.37Issue(1)：79-86,8.
基于ARIMA与数据累加生成的区间时间序列混合预测模型
Interval time series hybrid prediction model based on ARIMA and data accumulation
摘要
Abstract
In order to improve the accuracy of the interval time series in forecasting model, an improved ARIMA model is proposed.The binary and ternary interval time series are changed into real sequences which contain the equivalent information, and then the cumulative processing method of the gray model is combined with ARIMA model to realize real sequence prediction.Finally the interval prediction can be obtained through the restoring procedure.The data analysis shows that the interval prediction sequence with high precision can be got without the data accumulated processing when the fluctuation of the interval sequence is small.But when the fluctuation of the interval sequence is large, the processing method of data accumulation eliminates the randomness of the original series and can be better to learn about the regular pattern of modeling sequence, so that the prediction sequence with higher precision can be got.关键词
ARIMA模型/灰色模型/区间序列预测/区间中值/区间半径Key words
ARIMA model/gray model/interval time series prediction/interval median/interval radius分类
自科综合引用本文复制引用
赖丽洁,曾祥艳..基于ARIMA与数据累加生成的区间时间序列混合预测模型[J].桂林电子科技大学学报,2017,37(1):79-86,8.基金项目
国家自然科学基金(71561008) （71561008）
广西自然科学基金(2014GXNSFAA118010) （2014GXNSFAA118010）
广西教育厅科研项目(KY2015YB113) （KY2015YB113）
