Research on power failure classification and identification of low-voltage users in low-voltage distribution network based on Internet of Things technology

Wei Yu, Yifang Su, Yuanhong Liu, Yan Tao, W. Liu, M. Zhao, Jinyu Wang
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Abstract

In China's social and economic development, stable development and suppression of fluctuation are the basic goals of macroeconomic policy. Due to the cyclical characteristics of China's financial and economic development, the construction of cyclical early warning mechanism in practical exploration can not only accurately predict the development trend of financial economy, but also help government departments and market institutions to make effective decisions. This paper is understanding China's financial and economic development trend and risk cycle early warning mechanism. Based on the research situation, the early warning mechanism with BP algorithm is deeply discussed. The final experimental results prove that we should continue to strengthen the research on the early warning mechanism of neural network in the financial and economic cycle.
基于物联网技术的低压配电网低压用户停电分类与识别研究
在中国经济社会发展中,稳发展、抑波动是宏观经济政策的基本目标。由于中国金融经济发展的周期性特点,在实践探索中构建周期预警机制不仅可以准确预测金融经济的发展趋势,还可以帮助政府部门和市场机构做出有效的决策。本文主要是了解中国金融经济发展趋势和风险周期预警机制。结合研究现状,深入探讨了BP算法的预警机制。最终的实验结果证明,我们应该继续加强对神经网络在金融经济周期中的预警机制的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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