Optimization of autoregressive, exogenous inputs-based typhoon inundation forecasting models using a multi-objective genetic algorithm
作者： Huei-Tau Ouyang
DOI: 10.1080/0305215X.2016.1230207
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摘要: ABSTRACTThree types of model for forecasting inundation levels during typhoons were optimized: the linear autoregressive with exogenous inputs (LARX), nonlinear wavelet function (NLARX-W) and sigmoid (NLARX-S). The forecast performance was evaluated by three indices: coefficient efficiency, error in peak water level relative time shift. Historical typhoon data used to establish water-level models that satisfy all objectives. A multi-objective genetic algorithm employed search Pareto-optimal set satisfies objectives select ideal indices. Findings showed optimized (NLARX-W NLARX-S) outperformed (LARX). Among models, NLARX-W achieved a more balanced on indices than NLARX-S and...
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