SAP SE
PROCESSING DATA USING MULTIPLE NEURAL NETWORKS

Abstract:

As discussed herein, multiple neural networks are each trained on time-series data from a different domain. Each of the trained neural networks is used to make a domain-specific prediction for each point in time. Thus, time-series prediction data is generated by each of the trained neural networks. The domain-specific time-series prediction data are combined into a vector and used to train a final model that predicts a value. By breaking down the problem of forecasting into domain-specific forecasting models and a forecasting model, accuracy is improved over traditional document-based forecasting and computational resources are saved over traditional neural network designs.