Early-Warning Research on Resource Economy Sustainable Development Based on BP Artificial Neural Network - The Case of Yulin of Shaanxi Province

Abstract:

Resource economy sustainable development degree of Yulin, Shaanxi Province during Year 2000-2014 was estimated and pre-warned by building BP neural network early-warning model and applying the written Matlab7.1 calculation program and AHP method. The early-warning results indicated that, economy sustainable development tendency of Yulin, Shaanxi during Year 2000-2014 is under huge warning, serious warning, medium warning and light warning these four states, respectively; early-warning model based on BP neural network has strong simulation ability, which is more appropriate for non-linear system early-warning research of solving resource economy sustainable development.

• Periodical: Advanced Materials Research (Volumes 524-527)
• Pages: 3070-3074
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.524-527.3070
• Online since: May 2012
• Authors: Min Song, Xue Min Liu
• Keywords: BP Neural Network (BPNN), Early-Warning, Resource Economy

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