A Prediction Method of Power Energy Saving Potential Based on Rough Set Neural Network

Abstract:

Power industry is the key field of implementing energy saving and pollutant emission reduction in china, strengthen power energy saving is helpful to establish a resource-saving and environment-friendly society and promote a sustainable development of economic society. This paper synchronizes respective advantages of rough set and neural network, puts forward a prediction model-RSBPNN which uses rough set knowledge reduction method to prune the redundant and neural network to build a forecasting model.

• Periodical: Applied Mechanics and Materials (Volumes 44-47)
• Pages: 3795-3799
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.44-47.3795
• Online since: December 2010
• Authors: Jin Ying Li, Ya Jun Wei, Jin Chao Li, Yu Zhi Zhao
• Keywords: Neural Network (NN), Power Energy Saving Potential, Prediction, ROSETTA, Rough Set (RS)

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