摘要
文章研究通过采用深度学习中的长短时记忆网络(LSTM)和支持向量机等先进算法,建立了高效的监测与预测系统。实验结果表明,所提出的方法在模型准确性和实时性方面取得了显著的进展,为水利水电行业提供可行的智能化解决方案。
This paper establishes an efficient monitoring and prediction system by adopting advanced algorithms in deep learning,such as long short-term memory(LSTM)and support vector machine(SVM).The experimental results show that the proposed method has made significant progress in model accuracy and real-time performance,providing feasible intelligent solutions for the water conservancy and hydropower industry.
作者
汲晓飞
JI Xiaofei(Junan Stone Lotus Seed Water Conservancy Service Center,Linyi 276600,China)
关键词
人工智能
水利水电设备
状态监测
artificial intelligence
water conservancy and hydropower equipment
status monitoring
