Distributed Representations, Simple Recurrent Networks, And Grammatical Structure
Machine Learning - Connectionist approaches to language learning
Extraction of rules from discrete-time recurrent neural networks
Neural Networks
Neural Networks in the Capital Markets
Neural Networks in the Capital Markets
Time Series Analysis
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
IEEE Transactions on Neural Networks
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A full customised case-oriented Multi-Layered Recurrent Neural Network (MLRNN) has been proposed to predict the Capacity of Crude Oil Distillation in OPEC Member Countries. Recurrent neural networks use feedback connections and have the potential to represent certain computational structures in a more parsimonious fashion. Moreover, a cluster based training procedure, in which proper opportunity achieves for network to sense complicated nonlinear relations in data, has been supplied. The results of proposed MLRNN were promising in comparison with the results of a Multi-Layered Feed-Forward Neural Network (MLFFNN) on the aforementioned case study.