计算机工程与科学2024，Vol.46Issue(8)：1493-1502,10.DOI:10.3969/j.issn.1007-130X.2024.08.018
一种模糊时间序列概率预测方法
A probabilistic forecasting method with fuzzy time series
摘要
Abstract
In time series prediction tasks,the uncertainty of historical observations poses difficulties in forecasting.However,the forecasting methods based on fuzzy time series have unique advantages in dealing with data uncertainty.Probabilistic forecasting,on the other hand,can provide the distribution of the predicted target and quantify the uncertainty of the prediction results.Therefore,a fuzzy time se-ries probabilistic forecasting method based on a probability weighting strategy is proposed to reduce the impact of uncertainty on the forecasting task.The proposed method builds a probability-weighted fuzzy time series prediction model using historical observations of the target variable,and refines the fuzzy rule base of the prediction model by introducing additional observations.Specifically,two operators with low computational cost are used to reconstruct the fuzzy logic relationships.The intersection operator is used to exclude the interfering information,while the union operator merges all information,resulting in two different sets of fuzzy logic relationship groups.The relationship group corresponding to the cur-rent observation value in two sets is the prediction for the fuzzy set in the next moment.Finally,the probability distribution of the next moment is output by defuzzification.Experimental results on public-ly available time series data sets verify the accuracy and validity of this method,and the prediction accu-racy is remarkably improved in comparison to the newly proposed PWFTS prediction method.关键词
模糊时间序列/概率预测/模糊逻辑关系/交算子/并算子Key words
fuzzy time series/probabilistic forecasting/fuzzy logical relationship/intersection opera-tor/union operator分类
信息技术与安全科学引用本文复制引用
董文超,郭强,张彩明..一种模糊时间序列概率预测方法[J].计算机工程与科学,2024,46(8):1493-1502,10.基金项目
国家自然科学基金(61873145) （61873145）
山东省自然科学省属高校优秀青年人才联合基金(ZR2017JL029) （ZR2017JL029）
山东省高等学校青创科技支持计划(2019KJN045) （2019KJN045）
