深度学习在洪水流量预测中的应用
Application of Deep Learning in Flood Flow Prediction
王柏璎 1陈纲 1杨智慧 1莫光达 1王静1
作者信息
摘要
阐述深度学习在一元非线性回归中的适用性.在案例中,将适线法、自定义函数法、一元多次方程法、深度学习算法应用到设计流量计算中.通过对比分析,深度学习算法具有良好的适用性,并且具有计算速度快,拟合度高的优点.
Abstract
This paper describes the applicability of deep learning in univariate nonlinear regression.In the case,it applies the line fitting method,custom function method,univariate multiple equation method,and deep learning algorithm to design traffic calculation.Through comparative analysis,deep learning algorithms have good applicability and the advantages of fast computation speed and high fitting degree.
关键词
机器学习/深度学习/非线性/回归/设计流量Key words
machine learning/deep learning/nonlinearity/regression/design traffic引用本文复制引用
基金项目
南宁职业技术学院模块化课程体系课题(ZI2021060203)
南宁职业技术学院模块化课程体系课题(ZI2021060204)
出版年
2024
NETL
NSTL
万方数据