| 基于BP神经网络的地下水位预测系统设计 |
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| 作者姓名： | 廖绍欢 赵乃千 詹旭 |
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| 作者单位： | 1.四川省地震局成都地震监测中心站，四川成都6117302.四川轻化工大学自动化与信息工程学院，四川自贡643000 |
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| 基金项目： | 四川省地震局地震科技专项青年项目（LY2225）资助。 |
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| 摘 要： | 为了解四川德阳地下水位动态，进而分析地震前兆动态，本文设计了一个基于BP神经网络的地下水位预测系统。采用SWY-Ⅱ数字式水位仪对德阳地下水位数据进行采集。根据采集的2015年水位数据，利用BP神经网络对地下水位变化进行预测，以一年的采集数据进行训练和测试，采用3个输入节点、1个输出节点设计了BP神经网络结构。为了进一步验证本预测系统，本文对2017年7月1日—10月26日地下水位情况进行了预测。实验表明:该方案能有效实现地下水位的预测，为地震前兆工作提供可靠数据。
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| 关 键 词： | 单片机 BP神经网络 预测 |
| 收稿时间： | 2022-07-21 |
Design of groundwater level prediction system based on BP neural network |
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| Institution: | 1.Chengdu Earthquake Monitoring Center Station, Sichuan Earthquake Agency, Sichuan Chengdu 611730, China2.School of Automation and Information Engineering, Sichuan University of Science & Engineering, Sichuan Zigong 643000, China |
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| Abstract: | In order to understand the dynamic of groundwater level and master the earthquake precursor dynamic, we designed groundwater level prediction system based on BP neural network. According to the groundwater level of Deyang, Sichuan Province, SWY-II digital water level meter is used to collect the groundwater level data of Deyang. Based on the collected water level data in 2015, the BP neural network is used to predict the change of groundwater level, and the data collected for one year are trained and tested. The structure of BP neural network is designed with three input nodes and one output node. In order to further validate the proposal, the groundwater level from July 1 to October 26, 2017 is predicted. The experiment shows that the scheme can predict groundwater level effectively and provide reliable data for earthquake precursor work. |
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