Fishery landing forecasting using wavelet-based autoregressive integrated moving average models
The accuracy of the wavelet-ARIMA (WA) model in monthly fishery landing forecasting is investigated in the study. In the first part of the study, the discrete wallet transform (DWT) is used to decompose fishery landing time series data. Then ARIMA, as a powerful forecasting tool, is implemented to p...
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| Format: | Article |
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Hindawi Publishing
2015
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