Load Forecasting based on Fuzzy Time Series
- 10.2991/ic3me-15.2015.139How to use a DOI?
- Fuzzy time series; K-means algorithm; Fuzzidication; Fuzzy relation;Load forecasting
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.
- © 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/).
Cite this article
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 -