水利安全中混凝土松软程度报警网络模型仿真  

Simulation of concrete soft degree alarm network model in water conservancy safety

作　　者：李茂彤 王雷清 LI Maotong;WANG Leiqing(Shandong Zhuan Engineering Consulting Co.,Ltd.,Jinan 250000,China;Qingdao Ruiyuan Engineering Group Co.,Ltd.,Qingdao 266555,China)

机构地区：[1]山东筑安工程咨询有限公司,山东济南250000 [2]青岛瑞源工程集团有限公司,山东青岛266555

出　　处：《中国高新科技》2024年第13期134-136,共3页

摘　　要：为提高水利安全监测中混凝土松软程度检测准确性,本研究设计了基于神经网络的混凝土松软程度报警网络模型。以Matlab 7.1仿真平台为例,设计了一系列对比实验,通过模拟各种水利环境和干扰条件,对比分析神经网络模型与传统模型在定位准确性、鲁棒性及通信信号误码率方面的表现。结果表明,神经网络模型在各项指标上均优于传统模型,证明了其在水利安全监测上的优越性。In order to improve the accuracy of concrete softness degree detection in water conservancy safety monitoring,this study designed a concrete softness degree alarm network model based on neural network.Taking the Matlab 7.1 simulation platform as an example,a series of comparative experiments were designed to compare and analyze the performance of the neural network model and the traditional model in terms of positioning accuracy,robustness and bit error rate of communication signals by simulating various water environment and interference conditions.The results show that the neural network model is superior to the traditional model in every index,which proves its superiority in water conservancy safety monitoring.

关 键 词：水利安全 报警网络模型 神经网络 

分 类 号：TP309[自动化与计算机技术—计算机系统结构]