Impact of Input Feature Selection on Groundwater Level Prediction From a Multi-Layer Perceptron Neural Network

With the growing use of machine learning (ML) techniques in hydrological applications, there is a need to analyze the robustness, performance, and reliability of predictions made with these ML models. In this paper we analyze the accuracy and variability of groundwater level predictions obtained fro...

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Detalhes bibliográficos

Principais autores:	Reetik Kumar Sahu, Juliane Müller, Jangho Park, Charuleka Varadharajan, Bhavna Arora, Boris Faybishenko, Deborah Agarwal
Formato:	Artigo
Idioma:	Inglês
Publicado em:	Frontiers Media S.A. 2020-11-01
coleção:	Frontiers in Water
Assuntos:	machine learning groundwater level prediction feature selection sensitivty analysis hyperparameter optimization
Acesso em linha:	https://www.frontiersin.org/articles/10.3389/frwa.2020.573034/full
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