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Engineering Optimization Volume 49, 2017 - Issue 7
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Original Articles

Optimization of autoregressive, exogenous inputs-based typhoon inundation forecasting models using a multi-objective genetic algorithm

Huei-Tau OuyangDepartment of Civil Engineering, National Ilan University, Yilan City, TaiwanCorrespondence[email protected]
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Pages 1211-1225 | Received 17 Jun 2016, Accepted 18 Aug 2016, Published online: 20 Sep 2016

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Marwen Elkamel, Ali Ahmadian & Qipeng P. Zheng. (2022) Impact of coronavirus disease 2019 on electricity demand and the unit commitment problem: a long–short-term memory-based machine learning approach. Engineering Optimization 54:11, pages 1835-1852.
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Articles from other publishers (4)

Zahra Hajirahimi & Mehdi Khashei. (2022) Hybridization of hybrid structures for time series forecasting: a review. Artificial Intelligence Review 56:2, pages 1201-1261.
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Hussein Bizimana & Abdüsselam Altunkaynak. (2019) A novel approach for the prediction of the incipient motion of sediments under smooth, transitional and rough flow conditions using Geno-Fuzzy Inference System model. Journal of Hydrology 577, pages 123952.
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H. T. Ouyang. (2017) Characteristics of recursive and non-recursive adaptive network-based fuzzy inference system models for the forecast of typhoon inundation levels. International Journal of Environmental Science and Technology 14:11, pages 2495-2506.
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Huei-Tau Ouyang. (2017) Nonlinear autoregressive neural networks with external inputs for forecasting of typhoon inundation level. Environmental Monitoring and Assessment 189:8.
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