Weighted Combined Water Level Prediction Based on Nonlinear Programming Genetic Algorithm

A single prediction method has its own advantages and disadvantages in different aspects. In order to improve the accuracy of water level prediction, a water level prediction method combining The Autoregressive Integrated Moving Average (ARIMA) Model, Exponential Smoothing (ES) model and Long Short-...

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Vydané v:	2022 7th International Conference on Computational Intelligence and Applications (ICCIA) s. 140 - 145
Hlavní autori:	Wang, Congyou, Cuan, Wanbing, Jia, Lu
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 24.06.2022
Predmet:	Aerospace electronics combined water level prediction Computational modeling Lakes nonlinear programming genetic algorithm Predictive models Programming Resource management Smoothing methods weighted combination
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