Language models for financial news recommendation
Proceedings of the ninth international conference on Information and knowledge management
Demand forecast in a supermarket using a hybrid intelligent system
Design and application of hybrid intelligent systems
Improved supply chain management based on hybrid demand forecasts
Applied Soft Computing
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Adding recurrence to neural networks improves their time series forecasts. Well chosen inputs such as a window of time-delayed inputs, or intelligently preprocessed inputs, are more important than recurrence. Neural networks do well on moderately noisy and chaotic time series, such as sunspot data. A single neural network or genetic program generalizes poorly on weekly stock market indices due to the low signal-to-noise ratio. When the responses of a number of networks are averaged, the resulting forecast shows substantial profits on historical data.