Biography

Haitham Afan is a civil engineer specializing in water resources management, hydrological parameter modeling, and the application of Artificial Intelligence (AI) techniques in the field of civil and environmental engineering. He received his B.Sc. from the University of Anbar in 2010, and his M.Sc. and Ph.D. from Universiti Kebangsaan Malaysia in 2014 and 2017, respectively. Dr. Afan worked as a researcher at Ton Duc Thang University in Vietnam and as a post-doctoral researcher at the University of Malaya in Malaysia. He was a senior lecturer at Al-Maarif University College from 2019 to 2023. He currently works as a researcher at the Upper Euphrates developing center at the University of Anbar, where he continues to conduct cutting-edge research and contribute to the advancement of the field.

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Hayy al Muhandisin, Al Anbar, Iraq

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Harmonize input selection for sediment transport prediction
Improving the Muskingum flood routing method using a hybrid of particle swarm optimization and bat algorithm
Improving dam and reservoir operation rules using stochastic dynamic programming and artificial neural network integration model
Adaptive Fast Orthogonal Search (FOS) algorithm for forecasting streamflow
Application of artificial intelligence (AI) techniques in water quality index prediction: a case study in tropical region, Malaysia
Water quality prediction model based support vector machine model for ungauged river catchment under dual scenarios
Modeling the fluctuations of groundwater level by employing ensemble deep learning techniques
Investigating the influence of meteorological parameters on the accuracy of sea-level prediction models in Sabah, Malaysia
A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
Optimised neural network model for river-nitrogen prediction utilizing a new training approach
Delineating the Crop-Land Dynamic due to Extreme Environment Using Landsat Datasets: A Case Study
Complex extreme sea levels prediction analysis: Karachi coast case study
Pipeline scour rates prediction-based model utilizing a multilayer perceptron-colliding body algorithm
Influence of bed deposit in the prediction of incipient sediment motion in sewers using artificial neural networks
Accuracy enhancement for zone mapping of a solar radiation forecasting based multi-objective model for better management of the generation of renewable energy
Reservoir evaporation prediction modeling based on artificial intelligence methods
Artificial intelligence -driven insights into bisphenol A removal using synthesized carbon nanotubes
Linear and stratified sampling-based deep learning models for improving the river streamflow forecasting to mitigate flooding disaster
Heavy metal monitoring, analysis and prediction in lakes and rivers: state of the art
State-of-the art-powerhouse, dam structure, and turbine operation and vibrations
Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm
Investigation on the potential to integrate different artificial intelligence models with metaheuristic algorithms for improving river suspended sediment predictions
Sediment Incipient Motion in Sewer with a Bed Deposit
Input attributes optimization using the feasibility of genetic nature inspired algorithm: Application of river flow forecasting
LSTM Model Integrated Remote Sensing Data for Drought Prediction: A Study on Climate Change Impacts on Water Availability in the Arid Region
Numerical Modeling of Flow Pattern with Different Spillway Locations
Machine learning methods for better water quality prediction
Toward bridging future irrigation deficits utilizing the shark algorithm integrated with a climate change model
Assessing the predictability of an improved ANFIS model for monthly streamflow using lagged climate indices as predictors
Review of nitrogen compounds prediction in water bodies using artificial neural networks and other models
RBFNN versus FFNN for daily river flow forecasting at Johor River, Malaysia
Thermal and Hydraulic Performances of Carbon and Metallic Oxides-Based Nanomaterials
Artificial intelligence and geo-statistical models for stream-flow forecasting in ungauged stations: state of the art
Artificial intelligence models for methylene blue removal using functionalized carbon nanotubes
RBFNN versus GRNN modeling approach for sub-surface evaporation rate prediction in arid region
Energy analysis using carbon and metallic oxides-based nanomaterials inside a solar collector
Development of a novel hybrid optimization algorithm for minimizing irrigation deficiencies
Boosted artificial intelligence model using improved alpha-guided grey wolf optimizer for groundwater level prediction: Comparative study and insight for federated learning technology
Experimental and numerical analysis for earth-fill dam seepage
Modeling the Nonlinearity of Sea Level Oscillations in the Malaysian Coastal Areas Using Machine Learning Algorithms
RBFNN-based model for heavy metal prediction for different climatic and pollution conditions
Data-driven water quality prediction for wastewater treatment plants
Efficient river water quality index prediction considering minimal number of inputs variables
Beam-column joint shear prediction using hybridized deep learning neural network with genetic algorithm
An intelligent evolutionary extreme gradient boosting algorithm development for modeling scour depths under submerged weir
A Multi-Functional Genetic Algorithm-Neural Network Model for Predicting Suspended Sediment Loads
Towards a time and cost effective approach to water quality index class prediction
Hybrid model to improve the river streamflow forecasting utilizing multi-layer perceptron-based intelligent water drop optimization algorithm
ANN Based Sediment Prediction Model Utilizing Different Input Scenarios
Integrated support vector regression and an improved particle swarm optimization-based model for solar radiation prediction
Past, present and prospect of an Artificial Intelligence (AI) based model for sediment transport prediction
Feedforward artificial neural network-based model for predicting the removal of phenolic compounds from water by using deep eutectic solvent-functionalized CNTs
An improved model based on the support vector machine and cuckoo algorithm for simulating reference evapotranspiration
Precipitation forecasting using multilayer neuralNetwork and support vector machine optimization based on flow regime algorithm taking intoAccount uncertainties of soft computing models
Optimized River Stream-Flow Forecasting Model Utilizing High-Order Response Surface Method
Geneticizing input selection based advanced neural network model for sediment prediction in different climate zone
Optimizing height and spacing of check dam systems for better grassed channel infiltration capacity
Application of non-parametric approaches to identify trend in streamflow during 1976–2007 (Naula watershed)
Data-driven models for predicting water quality index: A case study of Klang and Langat rivers, Malaysia
Changes in climatic water availability and crop water demand for Iraq region
Study of Behaviour of Short Concrete Columns Confined with PVC Tube under Uniaxial Load
A novel hybrid evolutionary data-intelligence algorithm for irrigation and power production management: Application to multi-purpose reservoir systems
A novel Master–Slave optimization algorithm for generating an optimal release policy in case of reservoir operation
New evolutionary algorithm for optimizing hydropower generation considering multireservoir systems
Artificial intelligence based models for stream-flow forecasting: 2000-2015
The Impact of the Project (The University of Anbar is a Green Oasis) on Improving Vegetation Cover

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Hayy al Muhandisin, Al Anbar, Iraq

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Dr Haitham Afan (University of Anbar) Iraq

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