A Hybrid CNN-LSTM Approach for Monthly Reservoir Inflow Forecasting
Author:
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11269-023-03541-w.pdf
Reference49 articles.
1. Amnatsan S, Yoshikawa S, Kanae S (2018) Improved forecasting of extreme monthly reservoir inflow using an analogue-based forecasting method: a case study of the sirikit dam in Thailand. Water 10(11):1614
2. Babaei M, Moeini R, Ehsanzadeh E (2019) Artificial neural network and support vector machine models for inflow prediction of dam reservoir (case study: Zayandehroud dam reservoir). Water Resour Manag 33:2203–2218
3. Behzad M, Asghari K, Eazi M, Palhang M (2009) Generalization performance of support vector machines and neural networks in runoff modeling. Expert Syst Appl 36(4):7624–7629
4. Bozorg-Haddad O, Aboutalebi M, Ashofteh PS, Loáiciga HA (2018) Real-time reservoir operation using data mining techniques. Environ Monit Assess 190(10):1–22
5. Box GEP, Jenkins GM, Reinsel GC (2008) Time series analysis: forecasting and control, 4th edn. Wiley and Sons, New Jersey
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