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In this paper, the evaluation (Eva) layer based on NVTD is added to the Elman and BP networks.
For enhancing the accuracy of predicted value and avoiding the localized problems, the improved BP model adds the Eva layer combining with NVTD. The form of improved BP neural network (N-BP) is 6-10-6-3 (6 input neurons, 10 hidden neurons, 6 Eva neurons, and 3 output neurons), as shown in Figure 10.
Chaos and hysteresis of chilled water temperatures from NVTD are selected as constraint conditions for the network output.
However, CP model using the N-Elman overcomes this problem, NVTD provides the variation trend of data, and it is especially suitable for the interval of less data span.
During the training period, the predicted data of N-BP network model are more concentrated than BP network; the reason is that NVTD provides the variation trend of data.
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