基于Ga-Bp神经网络的高层建筑信号防雷系统

Zhijun Peng, Yunge Wang
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引用次数: 0

摘要

现在,在快速发展的城市环境中,高层建筑的规模显著增加,也增加了许多信号系统。但在实际的发展过程中,建筑中的偏好系统往往会被雷击破坏,而且随着时间的推移,这种现象不但没有减少,反而呈现出快速增长的趋势。现阶段,中国还没有达到高层建筑严格的防雷设计要求。通过对BP神经层、隐藏层和输出层的设计和调整,建立了BP的BP神经网络模型。根据高层建筑的具体数据和相关专家的判断,收集了高层建筑的防雷系统、报警系统、安全疏散系统和管理因素等安全评价样本。经过4组每组100次的模拟雷电实验,优化后的基于GA-BP神经网络的高层建筑信号防雷系统的有效防雷率在90%以上,报警时间比传统防雷系统快3倍左右,完美满足了高层建筑的防雷需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Signal Lightning Protection System of High-Rise Buildings Based on Ga-Bp Neural Network
Now, in the rapidly developing urban environment, the scale of high-rise buildings increases significantly, which also adds many signaling systems. However, in the actual development process, the preference system in buildings is often destroyed by lightning strikes, and over time, this phenomenon does not decrease, but shows a rapid growth trend. At the present stage, China does not meet the strict lightning protection design requirements of high-rise buildings. Through the design and adjustment of BP neural layer, hidden layer and output layer, the BP neural network model of BP is established. According to the specific data of high-rise buildings and the judgment of relevant experts, the safety assessment samples including the lightning protection system, alarm system, safety evacuation system and management factors of high-rise buildings are collected. After 4 groups of 100 simulated lightning experiments in each group, the effective lightning detection rate of the optimized high-rise building signal lightning protection system based on GA-BP neural network is more than 90%, and the alarm time is about 3 times faster than the traditional lightning protection system, which perfectly meets the lightning protection needs of high-rise buildings.
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