Load Forecasting based on Fuzzy Time Series

DOI

10.2991/ic3me-15.2015.139How to use a DOI?

Keywords

Fuzzy time series; K-means algorithm; Fuzzidication; Fuzzy relation;Load forecasting

Abstract

Load forecasting is a traditional research issue in the field of electric power system. In this paper, an improved fuzzy time series approach is used to forecast load. Firstly, a method of unequal-sized intervals partitioning based on K-means algorithm is proposed. Secondly, improved fuzzification method is proposed to overcome the defect of traditional fuzzification method. Finally, the model is used to forecast load and the relation between the number of clustering and the prediction accuracy and the relation between the order and the prediction accuracy are studied. The validity of model is verified by prediction results.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Pei Ao
PY  - 2015/08
DA  - 2015/08
TI  - Load Forecasting based on Fuzzy Time Series
BT  - Proceedings of the 3rd International Conference on Material, Mechanical and Manufacturing Engineering
PB  - Atlantis Press
SP  - 715
EP  - 719
SN  - 2352-5401
UR  - https://doi.org/10.2991/ic3me-15.2015.139
DO  - 10.2991/ic3me-15.2015.139
ID  - Ao2015/08
ER  -