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Performance comparison of continuous Wavelet-Fuzzy and discrete Wavelet-Fuzzy models for water level predictions at northern and southern boundary of Bosphorus

机译:连续小波-模糊模型与离散小波-模糊模型在博斯普鲁斯海峡南北边界水位预测中的性能比较

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摘要

In this study, combined Discrete Wavelet Transform-Fuzzy (DWT-Fuzzy) and combined Continuous Wavelet Transform-Fuzzy (CWT-Fuzzy) models are developed for predicting the daily water levels at northern and southern boundary of Bosphorus Strait. The observed daily water level data is decomposed into spectral bands (sub-series) by using wavelet transformation as a pre-processing tool in order to achieve more accurate daily water level predictions with extended lead-times up to 7 days. The time series of daily water level data is decomposed into spectral bands, which are used as inputs into the Fuzzy model and the daily water levels are predicted from the sum of the predicted components (spectral bands). A predictive model is developed using combined DWT-Fuzzy and combined CWT-Fuzzy models to predict water level fluctuations. It is found that CWT-Fuzzy model performed better than DWT-Fuzzy and stand-alone Fuzzy models for prediction lead-times up to 7 days at northern and southern boundary of Bosphorus based on RMSE and CE evaluation criteria. It is concluded that CWT is a better pre-processing technique as it yields more accurate daily water level predictions with improved prediction lead-times than DWT.
机译:在这项研究中,开发了组合离散小波变换-模糊(DWT-Fuzzy)和组合连续小波变换-模糊(CWT-Fuzzy)模型,以预测博斯普鲁斯海峡海峡北部和南部边界的每日水位。通过使用小波变换作为预处理工具,可以将观测到的每日水位数据分解为频谱带(子系列),以实现更准确的每日水位预测,并将交货时间延长至7天。每日水位数据的时间序列被分解为光谱带,这些光谱带用作模糊模型的输入,并且根据预测分量之和(光谱带)来预测每日水位。使用组合的DWT-Fuzzy和组合的CWT-Fuzzy模型开发了预测模型,以预测水位波动。发现基于WTSE和CE评估标准,CWT-Fuzzy模型在预测博斯普鲁斯海峡北部和南部边界长达7天的交货时间方面表现优于DWT-Fuzzy和独立的Fuzzy模型。结论是,CWT是一种更好的预处理技术,因为它产生的每日水位预测比DWT更为准确,且预测提前期有所改善。

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