Comparison of Hybrid LSTAR-GARCH Model with Conventional Stochastic and Artificial-Intelligence Models to Estimate Monthly Streamflow
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11269-024-03834-8.pdf
Reference51 articles.
1. Adamowski J, Chan HF, Prasher SO et al (2012) Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal, Canada. Water Resour Res 48(1):W01528
2. Alfa MI, Ajibike MA, Adie DB (2018) Reliability assessment of Thomas Fiering’s method of stream flow prediction. Niger J Technol 37(3):818–823
3. Amiri E (2015) Forecasting daily river flows using nonlinear time series models. J Hydrol 527:1054–1072
4. Artrith N, Urban A (2016) An implementation of artificial neural-network potentials for atomistic materials simulations: performance for TiO2. Comput Mater Sci 114:135–589
5. Bae I, Ji U (2019) Outlier detection and smoothing process for water level data measured by ultrasonic sensor in stream flows. Water 11(5):951
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