PISBN：9780128206737
出版社：Elsevier
出版时间：2021
作者：Sharma,Priyanka
主题词：Streamflow Forecasting,Stochastic Modeling,Datdriven Methods,Artificial Intelligence Techniques,Hybrid Models,Parametric And Noparametric Methods,Arfima,Arma,Artificial Intelligence (Ai)Excess Rainfall,Artificial Intelligence Technique,Artificial Intelligence,Artificial Neural Network (Ann)Deep Neural Network (Dnn)Machine Learning,Artificial Neural Network,Artificial Neural Networks,Automatic Time Series Forecasting,Convolutional Neural Network (Cnn)Gated Recurrent Unit (Gru)Long Shorterm Memory (Lstm) Network,Copula Entropy Method,Datdriven Modeling,Datdriven Models,Elm,Exponential Smoothing,Extreme Learning Machine,Extreme Learning Machines,Flood Forecasting Uncertainties,Flood Forecasts,Flood Hydrograph,Flood,Forecasting,Gamma Test,Gene Expression Programming,Genetic Programming,Hybrid Models,Hydrological Forecasting,Hydrology,Hyetograph,Input Selection,Intelligence,Knowledge,Linear/Nonlinear,M5 Model Tree,Mgarch,Mlr,Model Tree,Modeling Procedure,Multilayer Perceptron (Mlp)Recurrent Neural Network (Rnn)Streamflow Forecasting,Multiple/Multivariate,Orelm,Prediction And Simulation,Principle Component Analysis,Ramganga River Basin,Regional Climate Models (Rcms)Streamflow,Relm,Runoff,Sedre Stream,Sensitivity Analysis,Soft Computing Techniques,Statistical Performance Measures,Streamflow Forecasting,Streamflow,Support Vector Regression (Svr)Tapi Basin,Time Series Model,Time Series Modeling,Time Series Prediction,Uttarakhand,Var/Varx,Wavenet,Wrelm,Advances In Streamflow Forecasting: From Traditional To Modern Approaches
学科：X1 环境科学基础理论
语种：英语
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