A new linguistic out-sample approach of fuzzy time series for daily forecasting of Malaysian electricity load demand期刊界 All Journals 搜尽天下杂志传播学术成果专业期刊搜索期刊信息化学术搜索

A new linguistic out-sample approach of fuzzy time series for daily forecasting of Malaysian electricity load demand

Affiliation:	1. Mathematics Department, Faculty of Science, Universiti Teknologi Malaysia, Skudai, Johor Bahru 81310, Johor, Malaysia;2. Faculty of Computer Science, Universiti Tun Hussein Onn Malaysia, Batu Pahat 86400, Johor, Malaysia;1. Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore, West Bengal 721102, India;2. Department of Mathematics, Sidho Kanho Birsha University, Purulia, West Bengal 723101, India;1. Centre of Excellence for Fundamental Studies in Structural Engineering, Iran University of Science and Technology, Narmak, Tehran 16, Iran;2. Department of Civil Engineering, University of Zanjan, Zanjan, Iran;1. National Research Council (CNR), Institute of Cognitive Sciences and Technologies, Via Gaifami 18, 95028 Catania, Italy;2. School of Information Systems, Computing and Mathematics, Brunel University, Uxbridge, Middlesex UB8 3PH, United Kingdom;3. Department of Computing Engineering, University of La Laguna, 38271 Santa Cruz de Tenerife, Spain;1. Innovative Information Industry Research Center (IIIRC), School of Computer Science and Technology, Harbin Institute of Technology Shenzhen Graduate School, HIT Campus Shenzhen University Town Xili, Shenzhen 518055, PR China;2. Department of Computer Science and Information Engineering, National University of Kaohsiung, Kaohsiung 811, Taiwan, ROC;3. Department of Computer Science and Engineering, National Sun Yat-sen University, Kaohsiung 804, Taiwan, ROC

Abstract:	The fuzzy logical relationships and the midpoints of interval have been used to determine the numerical in-out-samples forecast in the fuzzy time series modeling. However, the absolute percentage error is still yet significantly improved. This can be done where the linguistics time series values should be forecasted in the beginning before the numerical forecasted values obtained. This paper introduces the new approach in determining the linguistic out-sample forecast by using the index numbers of linguistics approach. Moreover, the weights of fuzzy logical relationships are also suggested to compensate the presence of bias in the forecasting. The daily load data from National Electricity Board (TNB) of Malaysia is used as an empirical study and the reliability of the proposed approach is compared with the approach proposed by Yu. The result indicates that the mean absolute percentage error (MAPE) of the proposed approach is smaller than that as proposed by Yu. By using this approach the linguistics time series forecasting and the numerical time series forecasting can be resolved.

Keywords:	Fuzzy time series Index number Weight Electricity load demand Linguistic time series Out-sample forecast
本文献已被 ScienceDirect 等数据库收录！

设为首页 | 免责声明 | 关于勤云 | 加入收藏