Wavelet Packet-Genetic Programming: A New Model for Meteorological Drought Hindcasting

Ali DANANDEH MEHR; Mir Jafar Sadegh SAFARI; Vahid NOURANI

doi:https://doi.org/10.18400/tekderg.605453

Makale detayları

Wavelet Packet-Genetic Programming: A New Model for Meteorological Drought Hindcasting

Yazarlar:

Ali DANANDEH MEHR | Mir Jafar Sadegh SAFARI | Vahid NOURANI

Yayıncı:

TMMOB İnşaat Mühendisleri Odası

Ana Başlıklar:

İnşaat mühendisliği

Dergi:

Teknik Dergi 2021 Vol.32 Issue 4, pp.11029-11050

Belge Tipi:

Makale

Yayın Tarihi:

6/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000648387

Sıklık:

İki Aylık

pISSN:

1300-3453

DOI:

https://doi.org/10.18400/tekderg.605453

Özet:

 

This study presents developing procedures and verification of a new hybrid model, namely wavelet packet-genetic programming (WPGP) for short-term meteorological drought forecast. To this end, the multi-temporal standardized precipitation evapotranspiration index (SPEI) has been used as the drought quantifying parameter at two meteorological stations at Ankara province, Turkey. The new WPGP model comprises two main steps.  In the first step, the wavelet packet, which is a generalization of the well-known wavelet transform, is used to decompose the SPEI series into deterministic and stochastic sub-signals. Then, classic genetic programming (GP) is applied to formulate the deterministic sub-signal considering its effective lags. To characterize the stochastic component, different theoretical probability distribution functions were assessed, and the best one was selected to integrate with the GP-evolved function. The efficiency of the new model was cross-validated with the first order autoregressive (AR1), GP, and random forest (RF) models developed as the benchmarks in the present study. The results showed that the WPGP is a robust model, superior to AR1 and RF, and significantly increases the predictive accuracy of the standalone GP model.

 

This study presents developing procedures and verification of a new hybrid model, namely wavelet packet-genetic programming (WPGP) for short-term meteorological drought forecast. To this end, the multi-temporal standardized precipitation evapotranspiration index (SPEI) has been used as the drought quantifying parameter at two meteorological stations at Ankara province, Turkey. The new WPGP model comprises two main steps.  In the first step, the wavelet packet, which is a generalization of the well-known wavelet transform, is used to decompose the SPEI series into deterministic and stochastic sub-signals. Then, classic genetic programming (GP) is applied to formulate the deterministic sub-signal considering its effective lags. To characterize the stochastic component, different theoretical probability distribution functions were assessed, and the best one was selected to integrate with the GP-evolved function. The efficiency of the new model was cross-validated with the first order autoregressive (AR1), GP, and random forest (RF) models developed as the benchmarks in the present study. The results showed that the WPGP is a robust model, superior to AR1 and RF, and significantly increases the predictive accuracy of the standalone GP model.

Makale detayları

Wavelet Packet-Genetic Programming: A New Model for Meteorological Drought Hindcasting

Yazarlar: Ali DANANDEH MEHR | Mir Jafar Sadegh SAFARI | Vahid NOURANI

Yayıncı: TMMOB İnşaat Mühendisleri Odası

Ana Başlıklar: İnşaat mühendisliği

Dergi: Teknik Dergi 2021 Vol.32 Issue 4, pp.11029-11050

Belge Tipi: Makale

Yayın Tarihi: 6/2021

Belge Dili: İngilizce

Document ID (Org No.): 2000648387

Sıklık: İki Aylık

pISSN: 1300-3453

DOI: https://doi.org/10.18400/tekderg.605453

Sayı

Yazarlar:

Ali DANANDEH MEHR | Mir Jafar Sadegh SAFARI | Vahid NOURANI

Yayıncı:

TMMOB İnşaat Mühendisleri Odası

Ana Başlıklar:

İnşaat mühendisliği

Dergi:

Teknik Dergi 2021 Vol.32 Issue 4, pp.11029-11050

Belge Tipi:

Makale

Yayın Tarihi:

6/2021

Belge Dili:

İngilizce

Document ID (Org No.):

2000648387

Sıklık:

İki Aylık

pISSN:

1300-3453

DOI:

https://doi.org/10.18400/tekderg.605453