Extended homeostatic adaptation model with metabolic causation in plasticity mechanism—toward constructing a dynamic neural network model for mental imagery

2013 ◽  
Vol 21 (4) ◽  
pp. 263-273 ◽  
Author(s):  
Hiroyuki Iizuka ◽  
Hideyuki Ando ◽  
Taro Maeda
Keyword(s):  
Neural Network ◽  
Mental Imagery ◽  
Network Model ◽  
Neural Network Model ◽  
Dynamic Neural Network ◽  
Plasticity Mechanism ◽  
Adaptation Model

An Improved RBF Neural Network for Short Term Load Forecasting

2014 ◽  
Vol 1008-1009 ◽  
pp. 709-713 ◽  
Author(s):  
Chuang Li ◽  
Zhi Qiang Liang ◽  
Min You Chen
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Discriminant Function ◽  
Neural Network Model ◽  
Rbf Neural Network ◽  
Load Forecasting ◽  
Static Model ◽  
Short Term ◽  
Dynamic Neural Network ◽  
Short Term Load Forecasting

Neural network is widely used in the load forecasting area,but the traditional methods of load forecasting usually base on static model,which cannot change as time goes on. And the accuracy is worse and worse. To solve the problem, a dynamic neural network model for load forecasting is proposed .By way of introduce Error discriminant function, to control the error of load forecasting and dynamically modify the predicting model. Through the contrast of the short-term load forecasting result based on static neural network model and dynamic neural network model proposed, the error of load forecasting is decrease effectively.

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