Energy Consumption Forecasting Using United Grey System–Bayesian Regularization Neural Network Model

Abstract:

The energy consumption of the enterprise is subject to various factors. To solve the problem, a new grey-neural model is proposed which effectively combines the grey system and Bayesian-regularization neural network and avoids the disadvantages of each other. The case study indicates that the prediction method is not only reasonable in theory but also owns good application value in the energy consumption prediction. Meanwhile, results also exhibit that G-BRNN model has the automated regularization parameter selection capability and may ensure the excellent adaptability and robustness.

• Periodical: Advanced Materials Research (Volumes 524-527)
• Pages: 3087-3092
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.524-527.3087
• Online since: May 2012
• Authors: Xiao Hui Hu, Lv Jun Zhan, Yun Xue, Gui Xi Liu, Zhe Fan
• Keywords: Bayesian Regularization Neural Network, Energy Consumption (EC), Forecast, Grey System

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