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A prediction scheme for sunspot series using a Recurrent Neural Network is proposed in this paper. The recurrent neural network adopted in this scheme is the Multiscale-Bilinear Recurrent Neural Network with an adaptive learning algorithm (M-BRNN (AL)). The M-BLRNN(AL) is formulated by a combination of several Bilinear Recurrent Neural Network (BRNN) models in which each model is employed for predicting...
A prediction scheme for sunspot series using a Recurrent Neural Network is proposed in this paper. The recurrent neural network adopted in this scheme is the Bilinear recurrent neural network (BRNN). Since the BRNN is based on the bilinear polynomial, BRNN has been successfully used in modeling highly nonlinear systems with time-series characteristics. Dynamic-BRNN (D-BRNN) further improves the convergence...
A time series prediction method based on a BiLinear Recurrent Neural Network (BLRNN) is proposed in this paper. The proposed predictor is based on the BLRNN that has been proven to have robust abilities in modeling and predicting time series. The learning process is further improved by using a multiresolution-based learning algorithm for training the BLRNN so as to make it more robust for the prediction...
A prediction scheme of sunspot series using a BiLinear Recurrent Neural Network (BLRNN) is proposed in this paper. Since the BLRNN is based on the bilinear polynomial, it has been successfully used in modeling highly nonlinear systems with time-series characteristics and the BLRNN can be a natural choice in predicting sunspot series. The performance of the proposed BLRNN-based predictor is evaluated...
A time series prediction scheme based on multiresolution-based bilinear recurrent neural network (MBLRNN) is proposed in this paper. The proposed predictor is based on the BLRNN that has been proven to have robust abilities in modeling and predicting time series. The learning process is further improved by using a multiresolution-based learning algorithm for training the BLRNN so as to make it more...
A short-term electric load forecasting method using an Adaptive Multiresolution-based BiLinear Recurrent NeuralNetwork (AMBLRNN) is proposed in this paper. The AMBLRNN is based on the BLRNN that has been proven to have robust abilities in modeling and predicting time series. The learning process is further improved by using a multiresolution-based learning algorithm which employs the wavelet transform...
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