Hybridized artificial intelligence models with nature-inspired algorithms for river flow modeling: A comprehensive review, assessment, and possible future research …

H Tao, SI Abba, AM Al-Areeq, F Tangang… - … Applications of Artificial …, 2024 - Elsevier
River flow (Q flow) is a hydrological process that considerably impacts the management and
sustainability of water resources. The literature has shown great potential for nature-inspired …

A review of the application of hybrid machine learning models to improve rainfall prediction

SQ Dotse, I Larbi, AM Limantol, LC De Silva - Modeling Earth Systems …, 2024 - Springer
Rainfall is one of the most important meteorological phenomena that impacts many fields,
including agriculture, energy, water resources management, and mining, among others …

Application of an artificial intelligence technique enhanced with intelligent water drops for monthly reference evapotranspiration estimation

F Ahmadi, S Mehdizadeh, B Mohammadi… - Agricultural Water …, 2021 - Elsevier
Reference evapotranspiration (ET 0) is one of the most important parameters, which is
required in many fields such as hydrological, agricultural, and climatological studies …

Developing novel robust models to improve the accuracy of daily streamflow modeling

B Mohammadi, F Ahmadi, S Mehdizadeh… - Water Resources …, 2020 - Springer
Streamflow plays a major role in the optimal management and allocation of available water
resources in each region. Reliable techniques are therefore needed to be developed for …

Hybrid models to improve the monthly river flow prediction: Integrating artificial intelligence and non-linear time series models

F Fathian, S Mehdizadeh, AK Sales, MJS Safari - Journal of Hydrology, 2019 - Elsevier
Prediction of river flow as a fundamental source of hydrological information plays a crucial
role in various fields of water projects. In this study, at first, the capabilities of two time series …

Drought modeling using classic time series and hybrid wavelet-gene expression programming models

S Mehdizadeh, F Ahmadi, AD Mehr, MJS Safari - Journal of Hydrology, 2020 - Elsevier
The standardized precipitation evapotranspiration index (SPEI) at three different time scales
(ie, SPEI-3, SPEI-6, and SPEI-12) from six meteorology stations located in Turkey are …

Hybrid artificial intelligence-time series models for monthly streamflow modeling

S Mehdizadeh, F Fathian, JF Adamowski - Applied Soft Computing, 2019 - Elsevier
In recent years, many efforts have been made to develop hybrid models for hydrological time
series modeling. The present study introduces novel hybrid models by hybridizing time …

Estimation of daily reference evapotranspiration (ETo) using artificial intelligence methods: Offering a new approach for lagged ETo data-based modeling

S Mehdizadeh - Journal of hydrology, 2018 - Elsevier
Evapotranspiration (ET) is considered as a key factor in hydrological and climatological
studies, agricultural water management, irrigation scheduling, etc. It can be directly …

Development of boosted machine learning models for estimating daily reference evapotranspiration and comparison with empirical approaches

S Mehdizadeh, B Mohammadi, QB Pham, Z Duan - Water, 2021 - mdpi.com
Proper irrigation scheduling and agricultural water management require a precise
estimation of crop water requirement. In practice, reference evapotranspiration (ETo) is firstly …

Prediction of suspended sediment load using data-driven models

RM Adnan, Z Liang, A El-Shafie, M Zounemat-Kermani… - Water, 2019 - mdpi.com
Estimation of suspended sediments carried by natural rivers is essential for projects related
to water resource planning and management. This study proposes a dynamic evolving …