基于TensorFlow的LSTM神经网络智能电气火灾预测研究

Research on LSTM Neural Network Intelligent Electrical Fire Prediction Based on TensorFlow

随着智慧城市建设的步伐不断加快以及人工智能技术的高速发展,如何利用大数据技术对电气火灾事件实现精准预测已经成为当前火灾预防研究者特别关注的问题.本文设计并实现了基于TensorFlow智能学习系统的LSTM神经网络电气火灾预测算法,对某地区输电线路上的数据进行了分析,通过多次数据迭代和参数调优对模型进行了训练,实验结果表明,基于TensorFlow的LSTM神经网络算法对于电气火灾的预测不仅具有较高的准确度,而且泛化能力强,预测效果明显好于其他学习算法.

With the accelerating pace of smart city construction and the rapid development of artificial intelligence technology,how to use big data technology to achieve accurate prediction of electrical fire events has become a special concern of fire prevention researchers.This paper designed and implemented a LSTM neural network electrical fire prediction algorithm based on TensorFlow intelligent learning system,analyzed the data on the transmission line in a certain area and trained the model through several data iterations and parameter tuning,the experimental results show that the LSTM neural network algorithm based on TensorFlow for electrical fire prediction not only has high accuracy,and strong generalization ability,prediction effect is much better than other learning algorithms.