Characteristic Curve Fitting of Capacitive Rainfall Sensor Based on BP Neural Network

被引：0

作者：

Zhang, Long ^{[1
]}

Ye, Song ^{[1
]}

Zhou, Shu-dao ^{[1
]}

Liu, Feng ^{[1
]}

机构：

[1] PLA Univ Sci & Technol, Coll Meteorol & Oceanog, Nanjing 211101, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON ELECTRICAL & ELECTRONICS ENGINEERING AND COMPUTER SCIENCE (ICEEECS 2016) | 2016年 / 50卷

基金：

中国国家自然科学基金;

关键词：

Capacitive Rainfall Sensor; Curve Fitting; Least Square Method; BP Neural Network; Mean Square Error;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Rainfall is a kind of common weather phenomenon. Accurate measurement of rainfall is of great significance for weather and natural disasters forecasting. In this paper, the capacitive sensor was applied to the measurement of rainfall and the working principle was introduced. Furthermore, the output characteristic curve of the sensor was fitted by BP neural network. The sensor's calibration data were taken as training samples and BP network model was established. The results showed that the fitting algorithm based on BP neural network had faster convergence speed and higher accuracy, and its fitting error was much smaller than that of the least square method.

引用

页码：737 / 742

页数：6

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