Robust drought forecasting in Eastern Canada: Leveraging EMD-TVF and ensemble deep RVFL for SPEI index forecasting

Multi‑step ahead forecasting of electrical conductivity in rivers by using a hybrid Convolutional Neural Network‑Long Short‑Term Memory (CNN‑LSTM) model enhanced by Boruta‑XGBoost feature selection algorithm

Experimental Study of Hydraulic Properties of Flow over Vertical Shaft Spillway with Different Shape of Inlet

Thermo-physical properties estimation of an oil-based hybrid nanofluid: application of a new hybrid neurocomputing approach

Developing Extended and Unscented Kalman Filter‑Based Neural Networks to Predict Cluster‑Induced Roughness in Gravel Bed Rivers

Experimental study and gradient-based ensemble intelligent computing to investigate effect of ultrasound on rheological behavior of bio-based phase change materials

New achievements on daily reference evapotranspiration forecasting: Potential assessment of multivariate signal decomposition schemes

Designing a decomposition-based multi-phase pre-processing strategy coupled with EDBi-LSTM deep learning approach for sediment load forecasting

A novel global solar exposure forecasting model based on air temperature: Designing a new multi-processing ensemble deep learning paradigm

Multi-step ahead hourly forecasting of air quality indices in Australia: Application of an optimal time-varying decomposition-based ensemble deep learning algorithm

Surface water electrical conductivity and bicarbonate ion determination using a smart hybridization of optimal Boruta package with Elman recurrent neural network

A comprehensive investigation of wetting distribution pattern on sloping lands under drip irrigation: A new gradient boosting multi-filtering-based deep learning approach

Design data decomposition-based reference evapotranspiration forecasting model: A soft feature filter based deep learning driven approach

A Comprehensive Experimental and Computational Investigation on Estimation of Scour Depth at Bridge Abutment: Emerging Ensemble Intelligent Systems

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

A high dimensional features-based cascaded forward neural network coupled with MVMD and Boruta-GBDT for multi-step ahead forecasting of surface soil moisture

Development of a TVF-EMD-based multi-decomposition technique integrated with Encoder-Decoder-Bidirectional-LSTM for monthly rainfall forecasting

Development of wavelet-based Kalman Online Sequential Extreme Learning Machine optimized with Boruta-Random Forest for drought index forecasting

Developing a novel hybrid Auto Encoder Decoder Bidirectional Gated Recurrent Unit model enhanced with empirical wavelet transform and Boruta-Catboost to forecast significant wave height

Experimental investigation of synthesized Al2O3 Ionanofluid's energy storage properties: Model-prediction using gene expression programming

Designing a Multi-Stage Expert System for daily ocean wave energy forecasting: A multivariate data decomposition-based approach

Air quality monitoring based on chemical and meteorological drivers: Application of a novel data filtering-based hybridized deep learning model

Experimental and computational assessment of wetting pattern for two-layered soil profiles in pulse drip irrigation: Designing a novel optimized Bidirectional deep learning paradigm

Multi-step daily forecasting of reference evapotranspiration for different climates of India: A modern multivariate complementary technique reinforced with ridge regression feature selection

Development of a new explicit soft computing model to predict the blast-induced ground vibration

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

Forecasting weekly reference evapotranspiration using Auto Encoder Decoder Bidirectional LSTM model hybridized with a Boruta-CatBoost input optimizer

Experimental exploration of rheological behavior of polyethylene glycol-carbon dot nanofluid: Introducing a robust artificial intelligence paradigm optimized with unscented Kalman filter technique

Predicting Rock Brittleness Using a Robust Evolutionary Programming Paradigm and Regression-Based Feature Selection Model

Long-term multi-step ahead forecasting of root zone soil moisture in different climates: Novel ensemble-based complementary data-intelligent paradigms

The entropy generation analysis of the influence of using fins with tip clearance on the thermal management of the batteries with phase change material: Application a new gradient-based ensemble machine learning approach

Investigation on two-phase fluid mixture flow, heat transfer and entropy generation of a non-Newtonian water-CMC/CuO nanofluid inside a twisted tube with variable twist pitch: Numerical and evolutionary machine learning simulation

Computational assessment of groundwater salinity distribution within coastal multi‑aquifers of Bangladesh

A parametric assessing and intelligent forecasting of the energy and exergy performances of a dish concentrating photovoltaic/thermal collector considering six different nanofluids and applying two meticulous soft computing paradigms

Predicting daily soil temperature at multiple depths using hybrid machine learning models for a semi-arid region in Punjab, India

Application of a modern multi-level ensemble approach for the estimation of critical shear stress in cohesive sediment mixture

Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection

Experimental Study of Hydraulic Properties of Flow over Vertical Shaft Spillway with Bow-Tied Shape Inlet

Estimating daily global solar radiation in hot semi-arid climate using an efficient hybrid intelligent system

Assessment of scouring around spur dike in cohesive sediment mixtures: A comparative study on three rigorous machine learning models

Combined Terrestrial Evapotranspiration Index prediction using a hybrid artificial intelligence paradigm integrated with relief algorithm-based feature selection

Application of Gaussian process regression to forecast multi-step ahead SPEI drought index

Estimating the density of hybrid nanofluids for thermal energy application: Application of non-parametric and evolutionary polynomial regression data-intelligent techniques

Experimental evaluation and development of predictive models for rheological behavior of aqueous Fe3O4 ferrofluid in the presence of an external magnetic field by introducing a novel grid optimization based-Kernel ridge regression supported by sensitivity analysis

The assessment of emerging data-intelligence technologies for modeling Mg+2 and SO4−2 surface water quality

Development of a new wavelet‑based hybrid model to forecast multi‑scalar SPEI drought index (case study: Zanjan city, Iran)

Toward the accurate estimation of elliptical side orifice discharge coefficient applying two rigorous kernel-based data-intelligence paradigms

Monitoring and Zoning of Drought in Southern Alborz

Prediction of flyrock induced by mine blasting using a novel kernel-based extreme learning machine

Application of Combined Artificial Neural Network Model and meta-heuristic Optimization Algorithms in Predicting SPEI12 Drought Index

Prediction of Maximum Scour Depth near Spur Dikes in Uniform Bed Sediment Using Stacked Generalization Ensemble Tree-Based Frameworks

Specific heat capacity of molten salt-based nanofluids in solar thermal applications: A paradigm of two modern ensemble machine learning methods

Comparison of the Performance of Artificial Neural Networks and Gene Expression Programming in Estimating the Forest Soil Water Characteristic Curve

On the Thermal Conductivity Assessment of Oil-Based Hybrid Nanofluids using Extended Kalman Filter integrated with feed-forward neural network

On the specific heat capacity estimation of metal oxide-based nanofluid for energy perspective – A comprehensive assessment of data analysis techniques

A novel boosting ensemble committee-based model for local scour depth around non-uniformly spaced pile groups

Simulation of Seepage Flow through Embankment Dam by using a novel Extended Kalman Filter based neural network Paradigm: Case Study of Fontaine Gazelles Dam, Algeria

On the assessment of specific heat capacity of nanofluids for solar energy applications: Application of Gaussian process regression (GPR) approach

Effective Geometrical parameters on discharge coefficient of gated piano key weir

Application of Gaussian Process Regression Model to Predict Discharge Coefficient of Gated Piano Key Weir

Comparison of wavelet-MLP and wavelet-GMDH models in forecasting EC and SAR at Zayandeh-Rood River

Compartion performance of adaptive neuro-fuzzy inference system (ANFIS) and gene expression programming (GEP) to estimate water distribution uniformity coefficient in classic sprinkle irrigation systems.

Prediction of sand rivers bed form using decision trees

Development of a novel soft-computing framework for the simulation aims: a case study

Experimental investigation of the effect of different cluster shapes on resistance coefficient

Developing GPR model for forecasting the rock fragmentation in surface mines

Forecasting of Multi-Step Ahead Reference Evapotranspiration Using Wavelet- Gaussian Process Regression Model

Experimental Study on the effect of Percent of Bentonite on the Scour hole rate in downstream of gate

Estimation of crop actual evapotranspiration using SEBAL algorithm (Case study: Khoramdareh region at Zanjan province)

GEP to Predict Characteristics of a Hydraulic Jump Over a Rough Bed

Estimation of classical hydraulic jump length using teaching–learning based optimization algorithm

Forecasting of Reference Evapotranspiration using MLP, RBF, and SVM Neural Networks

aboratory study of discharge coefficient of spindle-shaped weirs

Numerical modeling of gated piano key weir

Numerical investigation of triangular sharp crested weir

Predicting of SDI Hydrological drought Using by GRNN Neural Networks and GPR Model in Liqvan-Chay River Basin