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This paper focuses on sensitivity analysis of neural network (NN) parameters in order to improve the performance of NN based short-term electricity price forecasting. Sensitivity analysis of NN parameters include back-propagation learning set (BP-set), learning rate (eta), momentum (alpha) and NN learning days (dNN). Presented work is an extended version of previous work done by authors to integrate...
This paper presents a sensitivity analysis of similar days (SD) parameters to increase the accuracy of artificial neural network (ANN) and SD-based short-term price forecasting. Work presented in this paper is an extended version of previous works done by the authors to integrate ANN and SD method for predicting electricity price. The focus here is on sensitivity analysis of SD parameters while keeping...
This paper presents a sensitivity analysis of similar days (SD) parameters to increase the accuracy of artificial neural network (ANN) and SD based short-term price forecasting. Presented work is an extended version of previous works done by authors to integrate ANN and similar days method for predicting electricity price. Focus here is on sensitivity analysis of similar days parameters while keeping...
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