The variable weight combination load forecasting based on grey model and semi-parametric Regression Model

التفاصيل البيبلوغرافية
العنوان: The variable weight combination load forecasting based on grey model and semi-parametric Regression Model
المؤلفون: Xingying Chen, Shushu Ma, Yingchen Liao, Chen Kai, Ding Xiaohua, Gang Wang
المصدر: 2013 IEEE International Conference of IEEE Region 10 (TENCON 2013).
بيانات النشر: IEEE, 2013.
سنة النشر: 2013
مصطلحات موضوعية: Mathematical optimization, Computer science, business.industry, Load forecasting, Sample (statistics), Regression analysis, Machine learning, computer.software_genre, Term (time), Parametric model, Variable weight, Semi parametric regression, Artificial intelligence, business, computer
الوصف: Grey model using dimensional information update technology always contains the latest information from sample data, it guarantees the accuracy of mid-long term load forecasting. Semi-parametric regression model which combines the advantages of parametric model and nonparametric model, it can fully reflect the complexity and uncertainties of the load change. This paper put forward an improved method which combines grey model with semi-parametric regression model by time-varying weight for load forecasting, the proposed method would make full use of data information and consider its inherent regularity completely, which makes prediction more realistic. At last, a comparison of the error has been made between the single model and the combination model. The test example results show that this method has higher precision.
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::b29ee0a9ed807c3fadaa568642e28dec
https://doi.org/10.1109/tencon.2013.6719040
رقم الأكسشن: edsair.doi...........b29ee0a9ed807c3fadaa568642e28dec
قاعدة البيانات: OpenAIRE