Wavelet Packet-Genetic Programming: A New Model for\rMeteorological Drought Hindcasting
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Date
2021
Authors
Ali Danandeh Mehr
Mir Jafar Sadegh Safari
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Abstract
This study presents developing procedures and verification of a new hybrid model namely\rwavelet packet-genetic programming (WPGP) for short-term meteorological drought\rforecast. To this end the multi-temporal standardized precipitation evapotranspiration index\r(SPEI) has been used as the drought quantifying parameter at two meteorological stations at\rAnkara province Turkey. The new WPGP model comprises two main steps. In the first step \rthe wavelet packet which is a generalization of the well-known wavelet transform is used\rto decompose the SPEI series into deterministic and stochastic sub-signals. Then classic\rgenetic programming (GP) is applied to formulate the deterministic sub-signal considering\rits effective lags. To characterize the stochastic component different theoretical probability\rdistribution functions were assessed and the best one was selected to integrate with the GPevolved function. The efficiency of the new model was cross-validated with the first order\rautoregressive (AR1) GP and random forest (RF) models developed as the benchmarks in\rthe present study. The results showed that the WPGP is a robust model superior to AR1 and\rRF and significantly increases the predictive accuracy of the standalone GP model.
Description
Keywords
Meteoroloji ve Atmosferik Bilimler, Drought;SPEI;wavelet packet;genetic programming;stochastic modeling, İnşaat Mühendisliği, Civil Engineering
Fields of Science
0208 environmental biotechnology, 0207 environmental engineering, 02 engineering and technology
Citation
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