HIGH-ORDER ADAPTIVE MODEL TO FORECAST REGIONAL ELECTRICITY LOADS

摘要：

Over the past few years, a considerable number of studies have been proposed on load forecasting. This paper aims at proposing a promising model using high-order adaptive fuzzy time-series algorithm to get more efficient forecasting. From the reviewed literature related to fuzzy time-series, there are two points need to be concerned. The first is to determine a reasonable universe of discourse and the length of intervals, and the second is many researchers ignore the information of trend patterns change in the past history. Hence, this paper utilized the trend weighted and high order adaptive model to deal with above drawbacks. The proposed model is applied for forecasting the regional electricity load in Taiwan. The experiment results showed that the proposed model outperforms the listing methods under MAPE (mean absolute percentage error) criteria.

关键词： Fuzzy time-series adaptive ezpectation model linguistic variable load forecasting

作者: YAO-HSIEN CHEN JING-WEI LIU CHIN-HSUE CHENG

作者单位: Department of Information Management.National Yunlin University of Science and Technology,123, secti Department of Information Management.National Yunlin University of Science and Technology,123, secti

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 3277-3282

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）