Optimized empirical model based on whale optimization algorithm for simulate daily reference crop evapotranspiration in different climatic regions of China

Wu, Zongjun; Chen, Xi; Cui, Ningbo; Zhu, Bin; Gong, Daozhi; Han, Le; Xing, Liwen; Zhen, Shunsheng; Li, Qiling; Liu, Quanshan; Fang, Pei

doi:10.1016/j.jhydrol.2022.128084

Cited by 11 publications

(2 citation statements)

References 63 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…WOA is a novel intelligent algorithm that imitates the hunting behavior of humpback whales. This method not only inherits the advantages of previous intelligent algorithms but also outperforms other algorithms in function extremum problems (Liu et al 2021;Wu et al 2022). Compared with the traditional optimization algorithm, the whale optimization algorithm not only needs to adjust a few parameters, high precision, and fast convergence speed but also has strong global optimization ability, which is widely used in many fields (Li et al 2020b;Zhou et al 2021).…”

Section: Introductionmentioning

confidence: 98%

Monthly runoff prediction using gated recurrent unit neural network based on variational modal decomposition and optimized by whale optimization algorithm

Wang

Chau

et al. 2023

Preprint

View full text Add to dashboard Cite

To further increase the forecast precision of non-stationary non-linear monthly runoff series and improve the effectiveness of pretreatment of monthly runoff series, the whale optimization algorithm (WOA) is introduced to optimize the variational mode decomposition (VMD), and the WOA-VMD-GRU prediction model is constructed by coupling with the gating cycle unit (GRU) neural network. First, the variation modal decomposition is optimized by the whale optimization algorithm, to find the best decomposition modal number k and penalty factor α, then several IMF components are obtained according to VMD processing runoff sequences; finally, results are obtained by adding those of each component. Taking Manwan Hydropower, Hongjiadu Hydropower, and Changshui hydrological station as examples, the BP model, the GRU model, the EMD-GRU model, the CEEMDAN-GRU model, and the VMD-GRU model are compared. Four quantitative indexes were used to estimate the model performance. The results show that the WOA-VMD-GRU model has the best prediction accuracy, with correlation coefficients and Nash coefficients above 0.99 and 0.97 in the prediction results of the three hydrological stations, respectively, and avoids the low efficiency of VMD decomposition parameters in manual trial computation, providing a new way for monthly runoff prediction.

show abstract

Section: Introductionmentioning

confidence: 98%

Monthly runoff prediction using gated recurrent unit neural network based on variational modal decomposition and optimized by whale optimization algorithm

Wang

Chau

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Reference crop evapotranspiration, also known as potential evapotranspiration, forms the basis for estimating crop water requirements. Accurately quantifying reference crop evapotranspiration is of significant importance in calculating crop water requirements, irrigation scheduling, water resource management and planning, water allocation, and determining water balances [8] .…”

Section: Introductionmentioning

confidence: 99%

Monitoring the spatiotemporal changes in annual cropland area and evapotranspiration analysis in the Yellow River Basin from 2001 to 2021

Guo,

He,

Zhang

2024

Fifth International Conference on Geoscience and Remote Sensing Mapping (ICGRSM 2023)

View full text Add to dashboard Cite

Monthly runoff prediction using gated recurrent unit neural network based on variational modal decomposition and optimized by whale optimization algorithm

Wang,

Chau

et al. 2024

Environ Earth Sci

View full text Add to dashboard Cite

Optimized empirical model based on whale optimization algorithm for simulate daily reference crop evapotranspiration in different climatic regions of China

Cited by 11 publications

References 63 publications

Monthly runoff prediction using gated recurrent unit neural network based on variational modal decomposition and optimized by whale optimization algorithm

Monthly runoff prediction using gated recurrent unit neural network based on variational modal decomposition and optimized by whale optimization algorithm

Monitoring the spatiotemporal changes in annual cropland area and evapotranspiration analysis in the Yellow River Basin from 2001 to 2021

Monthly runoff prediction using gated recurrent unit neural network based on variational modal decomposition and optimized by whale optimization algorithm

Contact Info

Product

Resources

About