Electricity Consumption Prediction Model using Neuro-Fuzzy System

被引:0
作者
Abiyev, Rahib [1 ]
Abiyev, Vasif H. [1 ]
Ardil, Cemal [1 ]
机构
[1] Near East Univ, Dept Comp Engn, TRNC, Lefkosha, Turkey
来源
PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 8 | 2005年 / 8卷
关键词
Fuzzy logic; neural network; neuro-fuzzy system; neuro-fuzzy prediction;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type's of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.
引用
收藏
页码:128 / 131
页数:4
相关论文
共 9 条
[1]  
Abiyev Rahib, 2001, EL EL COMP ENG S NEU, P182
[2]  
KOSKO B, 1993, NEURAL NETWORKS FUZZ
[3]  
LAPADES A, 1987, NONLINEAR SIGNAL PRO
[4]   The application of neural techniques to the modelling of time-series of atmospheric pollution data [J].
Nunnari, G ;
Nucifora, AFM ;
Randieri, C .
ECOLOGICAL MODELLING, 1998, 111 (2-3) :187-205
[5]  
PEDRYZ W, 1996, FUZZY MODELLING PARA
[6]   An artificial neural network noise reduction method for chaotic attractors [J].
Smaoui, N .
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2000, 73 (04) :417-431
[7]   TIME-SERIES FORECASTING USING NEURAL NETWORKS VS BOX-JENKINS METHODOLOGY [J].
TANG, ZY ;
DEALMEIDA, C ;
FISHWICK, PA .
SIMULATION, 1991, 57 (05) :303-310
[8]  
Yager R.R., 1994, Fuzzy Sets, Neural Networks and Soft Computing
[9]  
ZHANG YQ, 2000, P INT C NEUR INF PRO, P576