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Short-term prediction of water demand provides basic guarantee of water supply system operation and management. In this study, an effective model for daily water demand forecasting is proposed. Firstly, principle component analysis (PCA) is utilized to simplify the complexity and reduce the correlation between influence variables, and the score values of selected principle components (PCs) turn into...
In this paper, an improved Levenberg-Marquardt (LM) algorithm with adaptive learning rate is proposed to optimize the learning process of RBF neural networks. First, an improved LM algorithm is adopted using a quasi-Hessian matrix and gradient vector which are computed directly. Compared with the conventional LM algorithm, Jacobian matrix multiplication and storage are not required in the improved...
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