机电工程技术2025，Vol.54Issue(11)：113-118,148,7.DOI:10.3969/j.issn.1009-9492.2025.11.021
基于灰色关联和神经网络的剩余电流预测模型
Residual Current Prediction Model Based on Gray Correlation and Neural Network
于红 1任行 2雷迪豪2
作者信息
- 1. 湖南经研电力设计有限公司,长沙 410116
- 2. 昆明理工大学电力工程学院,昆明 650500
- 折叠
摘要
Abstract
In order to improve the early warning capability of electrical fires in power Internet of Things systems,a residual current modeling method that combines gray correlation and neural networks is proposed.By analyzing 27 985 sets of data in the intelligent fire monitoring system,it demonstrates the use of advanced sensor technology for effective data collection and processing in the Internet of Things environment.The model is based on correlation analysis and gray prediction algorithm,using a trained neural network to predict residual current.This method not only improves the efficiency and accuracy of data processing in the Internet of Things,but also highlights the importance of sensor technology in electrical monitoring and fire prevention.Through comparative analysis of the predicted residual current and the actual residual current,the error range is 0.18%～3.21%,confirming the accuracy of the model and the practicality of the sensor-based method in IoT applications.关键词
电气火灾预警/剩余电流预测/灰色模型/神经网络Key words
electrical fire early warning/residual current prediction/gray model/neural network分类
信息技术与安全科学引用本文复制引用
于红,任行,雷迪豪..基于灰色关联和神经网络的剩余电流预测模型[J].机电工程技术,2025,54(11):113-118,148,7.
