A multi-scale evolutionary deep learning model based on CEEMDAN, improved whale optimization algorithm, regularized extreme learning machine and LSTM for …

C Ji, C Zhang, L Hua, H Ma, MS Nazir, T Peng - Environmental research, 2022 - Elsevier
With the rapid development of economy, air pollution occurs frequently, which has a huge
negative impact on human health and urban ecosystem. Air quality index (AQI) can directly …

Metaheuristic approaches for prediction of water quality indices with relief algorithm-based feature selection

NL Kushwaha, J Rajput, T Suna, DR Sena… - Ecological …, 2023 - Elsevier
Monitoring and assessing groundwater quality are important for sustainable water resource
management. Therefore, the present study aimed to analyze and predict the water quality …

[HTML][HTML] Multi-steps drought forecasting in arid and humid climate environments: Development of integrative machine learning model

M Karbasi, M Jamei, A Malik, O Kisi… - Agricultural Water …, 2023 - Elsevier
In the current study, the Standardized Precipitation Evaporation Index (SPEI) was forecasted
using a combination of the empirical wavelet transform (EWT), discrete wavelet transforms …

Improving multi-month hydrological drought forecasting in a tropical region using hybridized extreme learning machine model with Beluga Whale Optimization …

MM Hameed, SF Mohd Razali… - … Research and Risk …, 2023 - Springer
Climate change has increased drought frequency globally, which harms the environment,
agriculture, and water resources. This study explores the capacity of a hybrid model based …

Enhancing drought monitoring and prediction in diverse climates by using composite drought indices

S Sharafi, MM Ghaleni - Stochastic Environmental Research and Risk …, 2023 - Springer
In order to improve the reliable monitoring and prediction of drought behavior, it is crucial to
comprehensively consider composite indices. Initially, four univariate drought indices were …

Develo** hybrid data-intelligent method using Boruta-random forest optimizer for simulation of nitrate distribution pattern

M Jamei, S Maroufpoor, Y Aminpour, M Karbasi… - Agricultural Water …, 2022 - Elsevier
One of the critical factors in the optimal design of drip-fertigation systems is determining the
distribution of nitrate in the soil. Handling such a complex non-linear process is challenging …

Integration of flux footprint and physical mechanism into convolutional neural network model for enhanced simulation of urban evapotranspiration

H Chen, JJ Huang, H Liang, W Wang, H Li, Y Wei… - Journal of …, 2023 - Elsevier
Estimating urban evapotranspiration (ET) is of great significance for urban water resource
allocation and assessing the urban heat island effect. However, most current urban ET …

An explainable hybrid framework for estimating daily reference evapotranspiration: Combining extreme gradient boosting with Nelder-Mead method

B Mohammadi, M Chen, MR Nikoo… - Journal of …, 2024 - Elsevier
Accurate estimation of reference evapotranspiration (ETo) is essential for effective water
resources management, irrigation system design, and various hydrological and agricultural …

Standardized precipitation evapotranspiration index (SPEI) estimated using variant long short-term memory network at four climatic zones of China

J Dong, L **ng, N Cui, L Zhao, L Guo… - Computers and Electronics …, 2023 - Elsevier
Although the accurate prediction of the Standardized Precipitation Evapotranspiration Index
(SPEI) is considered meaningful in reducing drought losses, its wide applications are limited …

Nondestructive detection of lead content in oilseed rape leaves under silicon action using hyperspectral image

X Zhou, Y Liu, J Sun, B Li, G **ao - Science of The Total Environment, 2024 - Elsevier
This study explored the feasibility of employing hyperspectral imaging (HSI) technology to
quantitatively assess the effect of silicon (Si) on lead (Pb) content in oilseed rape leaves …