Early Warning Model of Enterprise Operating Ability Using BP Neural Network

Abstract:

With the increasing risk in electric power bureaus, warning risk of enterprise operating ability in advance is an important work. However it is very difficult to establish stable functions to describe the mapping relationship between operating ability and associated causal influences. Hence, early warning of the operating ability is harder. In this paper, an early warning model based on BP neural network is designed and put forward to forecast the risk of operating ability of an electric power bureau. In addition, illustration by the experiment is given. The stable and accurate analysis result of the experiment shows that this early warning model is applicable to forecast the risk of operating ability of electric power bureaus.

• Periodical: Applied Mechanics and Materials (Volumes 20-23)
• Pages: 948-953
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.20-23.948
• Online since: January 2010
• Authors: Mo Yu Wang, Jie Chen, Xiao Liu Shen, Gui Lin Yu
• Keywords: BP Neural Network (BPNN), Early Warning Model, Electric Power Bureau, Operating Ability

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