A Component-wise Load Forecasting by Adaptable Artificial Neural Network

적응력을 갖는 신경회로망에 의한 성분별 부하 예측

The degree of forecast accuracy with BP-algorithm largely depends upon the neuron number in hidden layer. In order to construct the optimal structure, first, we prescribe the error bounds of learning procedure, and then, we provid the method of incrementing the number of hidden neurons by using the derivative of errors with respect to an output neuron weights. For the case study, we apply the proposed method to forecast the component-wise residential load, and compare this results to that of time series forecasting.