Investigation of Performance Effect of Input Diversity on Long Term Electricity Demand Forecasting

被引：0
|
作者：
Altinoz, O. Tolga [1 ]
Mengusoglu, Erhan [2 ]
机构：
[1] Ankara Univ, Elekt Elekt Muhendisligi Bolumu, Ankara, Turkey
[2] TED Univ, Bilgisayar Muhendisligi Bolumu, Ankara, Turkey
来源：
2015 23RD SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2015年
关键词：
long term forecasting; electricity demand; neural network; ARTIFICIAL NEURAL-NETWORKS;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The long term electricity demand forecasting is evaluated by using past demand and weather data. The aim of this study is to present the effect of the variety of inputs on performance. Therefore neural network models are evaluated due to their performance and common acceptance. Different varieties of inputs are applied to the model and results are compared with each other.
引用
收藏
页码：1098 / 1101
页数：4
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