Development of an efficient input selection method for NN based streamflow model
Author:
Affiliation:
1. Department of Civil Engineering, K.N. Toosi University of Technology, Tehran, Iran
Publisher
Informa UK Limited
Subject
Water Science and Technology
Link
https://www.tandfonline.com/doi/pdf/10.1080/23249676.2022.2088631
Reference84 articles.
1. Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting
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4. Prediction of Suspended Sediment Load Using Data-Driven Models
5. Performance Assessment of the Linear, Nonlinear and Nonparametric Data Driven Models in River Flow Forecasting
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