Short-term Load Forecasting Model Using Fuzzy C Means Based Radial Basis Function Network

2006 ◽  
Author(s):  
Youchan Zhu ◽  
Yujun He
Keyword(s):  
Radial Basis Function ◽  
Basis Function ◽  
Radial Basis Function Network ◽  
Load Forecasting ◽  
Forecasting Model ◽  
Short Term ◽  
Fuzzy C Means ◽  
Short Term Load Forecasting ◽  
Radial Basis ◽  
Function Network

Application of SVM-RBF to Prediction of Short-Term Load

2012 ◽  
Vol 614-615 ◽  
pp. 811-814
Author(s):  
Hong Zhang ◽  
Sheng Zhu Li ◽  
Luan Song Yue ◽  
Zhao Yu Pian
Keyword(s):  
Radial Basis Function ◽  
Basis Function ◽  
Input Data ◽  
Rbf Neural Network ◽  
Load Forecasting ◽  
Matlab Simulation ◽  
Short Term ◽  
Forecasting Accuracy ◽  
Short Term Load Forecasting ◽  
Radial Basis

Short Term Load Forecasting is important to power system. It can be economic and reasonable to arrange start and stop of the Generator in wire net, The text adopt radial basis function neural networks. The GA-optimized multi-core radial basis function SVM is applied to extract useful data and short-term load forecasting accuracy based on RBF neural network has been improved. In this paper, The advantages of improving the algorithm is demonstrated by the application of the MATLAB simulation with the input data of the spring load collected from California, United States.

Sign in / Sign up

Export Citation Format

Share Document