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针对滑坡泥石流灾害的预测与监控问题,提出一种基于无线传感器网络(WSN)和网络分析法(ANP)模型的边坡灾害预测和监控系统(WADPMS)。首先,通过WSN采集检测环境的各种致灾因子数据并传输给处理器。然后,利用ANP构建预测模型,根据致灾因子数据预测灾害发生概率。此外,系统可将压缩图像和灾害信息通过无线网络发送到各种移动终端,提高灾害预防和救灾效率。实验结果表明,相比BP神经网络和多元统计分析法,提出的预测模型获得了更高的预测准确率。
Aiming at the problem of landslide debris flow disaster prediction and monitoring, a slope disaster prediction and monitoring system (WADPMS) based on wireless sensor network (WSN) and network analysis (ANP) model is proposed. First of all, through the WSN detection environment, a variety of hazard data acquisition and transmission to the processor. Then, the ANP is used to construct the forecasting model to predict the disaster probability according to the hazard data. In addition, the system can send compressed images and disaster information to various mobile terminals through the wireless network to improve disaster prevention and disaster relief efficiency. Experimental results show that compared with BP neural network and multivariate statistical analysis, the proposed prediction model achieves higher prediction accuracy.