Saeed Farzin
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View article: Integrating Deep Learning and Copula Models for Flood–Drought Compound Analysis in Iran
Integrating Deep Learning and Copula Models for Flood–Drought Compound Analysis in Iran Open
This study aims to forecast the combined impacts of drought and flood in the future using an integrated framework. This framework integrates U-Net++, quantile mapping (QM), Copula models, and ISIMIP3b gridded large-scale discharge data (19…
View article: A New Flood Routing Framework Based on Modified Muskingum Model and Nature‐Based Optimization Algorithms
A New Flood Routing Framework Based on Modified Muskingum Model and Nature‐Based Optimization Algorithms Open
This study presents a new flood routing method integrating the modified Muskingum (NLM7_Aqlat) method with hybrid natural optimization algorithms (hybrid of Humboldt squid optimization algorithm [HSOA] and gradient‐based optimizer [GBO] an…
View article: Comprehensive Study of Climate Change Impacts on Temperature and Precipitation in East and West of Mazandaran Province in North of Iran
Comprehensive Study of Climate Change Impacts on Temperature and Precipitation in East and West of Mazandaran Province in North of Iran Open
The consequences of climate change in recent decades include global warming and variations in precipitation patterns. In this research, the impacts of climate change on temperature and precipitation in the east and west of Mazandaran Provi…
View article: A combination approach for optimization operation of multi-objective cascade reservoir systems (Case study: Karun reservoirs)
A combination approach for optimization operation of multi-objective cascade reservoir systems (Case study: Karun reservoirs) Open
Multi-reservoir systems that have diverse and conflicting objectives are challenging to design due to their uncertainties, non-linearities, dimensions and conflicts. The operation of multi-reservoir systems is crucial to increasing hydropo…
View article: The Pine Cone Optimization Algorithm (PCOA)
The Pine Cone Optimization Algorithm (PCOA) Open
The present study introduces a novel nature-inspired optimizer called the Pine Cone Optimization algorithm (PCOA) for solving science and engineering problems. PCOA is designed based on the different mechanisms of pine tree reproduction, i…
View article: Modeling of Monthly Rainfall–Runoff Using Various Machine Learning Techniques in Wadi Ouahrane Basin, Algeria
Modeling of Monthly Rainfall–Runoff Using Various Machine Learning Techniques in Wadi Ouahrane Basin, Algeria Open
Rainfall–runoff modeling has been the core of hydrological research studies for decades. To comprehend this phenomenon, many machine learning algorithms have been widely used. Nevertheless, a thorough comparison of machine learning algorit…
View article: Predicting rainfall response to climate change and uncertainty analysis: Introducing a novel downscaling CMIP6 models technique based on the stacking ensemble machine learning
Predicting rainfall response to climate change and uncertainty analysis: Introducing a novel downscaling CMIP6 models technique based on the stacking ensemble machine learning Open
This study proposes a novel downscaling technique based on stacking ensemble machine learning (SEML) to predict rainfall under climate change. The SEML consists of two levels. Rainfall time series predicted by level 1 algorithms MLR, MNLR,…
View article: Humboldt Squid Optimization Algorithm (HSOA): A Novel Nature-Inspired Technique for Solving Optimization Problems
Humboldt Squid Optimization Algorithm (HSOA): A Novel Nature-Inspired Technique for Solving Optimization Problems Open
This study presents a new natural-based algorithm called the Humboldt Squid Optimization Algorithm (HSOA). HSOA is inspired by Humboldt squids hunting, moving, and mating behavior. The HSOA search procedure involves an attack on fish schoo…
View article: An innovative approach of GSSHA model in flood analysis of large watersheds based on accuracy of DEM, size of grids, and stream density
An innovative approach of GSSHA model in flood analysis of large watersheds based on accuracy of DEM, size of grids, and stream density Open
Distributed modeling approach may have much better performance and accuracy compared with lumped-parameter hydrologic models. The main goals of this research are: investigating the possibility of combining distributed hydrological models w…
View article: Hydrological drought analysis in response to climate change based on a novel hybrid machine learning algorithm
Hydrological drought analysis in response to climate change based on a novel hybrid machine learning algorithm Open
For the first time, a combination of metaheuristic algorithms and machine learning is used for hydrological drought analysis under climate change conditions and applications. The new framework is used by a novel hybrid machine learning mod…
View article: A novel hybrid framework based on the ANFIS, discrete wavelet transform, and optimization algorithm for the estimation of water quality parameters
A novel hybrid framework based on the ANFIS, discrete wavelet transform, and optimization algorithm for the estimation of water quality parameters Open
Improving the performance of machine learning (ML) algorithms is essential for accurately estimating water quality parameters (WQPs). For the first time, a novel hybrid framework, namely the adaptive neural fuzzy inference system–discrete …
View article: A Novel Framework Based on the Stacking Ensemble Machine Learning (SEML) Method: Application in Wind Speed Modeling
A Novel Framework Based on the Stacking Ensemble Machine Learning (SEML) Method: Application in Wind Speed Modeling Open
Wind speed (WS) is an important factor in wind power generation. Because of this, drastic changes in the WS make it challenging to analyze accurately. Therefore, this study proposed a novel framework based on the stacking ensemble machine …
View article: Prediction of groundwater table and drought analysis; a new hybridization strategy based on bi-directional long short-term model and the Harris hawk optimization algorithm
Prediction of groundwater table and drought analysis; a new hybridization strategy based on bi-directional long short-term model and the Harris hawk optimization algorithm Open
In the present study, a new hybridization strategy for predicting the groundwater table (GWT) and drought analysis is presented. Therefore, a hybrid of the bi-directional long short-term model (BLSTM) and the Harris hawk optimization (HHO)…
View article: Development of Atom Search Optimization Algorithm in the Optimal Operation of Single and Multi-Reservoir Systems (Case study: Dez Dam)
Development of Atom Search Optimization Algorithm in the Optimal Operation of Single and Multi-Reservoir Systems (Case study: Dez Dam) Open
The optimal operation of reservoirs is regarded as one of the most vital issues in water resources management, which also plays an important role in environmental processes and control of ecosystem pollution, especially in river water. The…
View article: Evaluation of Time Series Models in Simulating Different Monthly Scales of Drought Index for Improving Their Forecast Accuracy
Evaluation of Time Series Models in Simulating Different Monthly Scales of Drought Index for Improving Their Forecast Accuracy Open
Drought is regarded as one of the most intangible and creeping natural disasters, which occurs in almost all climates, and its characteristics vary from region to region. The present study aims to investigate the effect of differentiation …
View article: A New Methodology for Reference Evapotranspiration Prediction and Uncertainty Analysis under Climate Change Conditions Based on Machine Learning, Multi Criteria Decision Making and Monte Carlo Methods
A New Methodology for Reference Evapotranspiration Prediction and Uncertainty Analysis under Climate Change Conditions Based on Machine Learning, Multi Criteria Decision Making and Monte Carlo Methods Open
In the present study, a new methodology for reference evapotranspiration (ETo) prediction and uncertainty analysis under climate change and COVID-19 post-pandemic recovery scenarios for the period 2021–2050 at nine stations in the two basi…
View article: Modeling of Reference Crop Evapotranspiration in Wet and Dry Climates Using Data-Mining Methods and Empirical Equations
Modeling of Reference Crop Evapotranspiration in Wet and Dry Climates Using Data-Mining Methods and Empirical Equations Open
In the present study, performance of data-mining methods in modeling and estimating reference crop evapotranspiration (ETo) is investigated. To this end, different machine learning, including Artificial Neural Network (ANN), M5 tree, Multi…
View article: Dye Pollutant Removal from Synthetic Wastewater: A New Modeling and Predicting Approach Based on Experimental Data Analysis, Kriging Interpolation Method, and Computational Intelligence Techniques
Dye Pollutant Removal from Synthetic Wastewater: A New Modeling and Predicting Approach Based on Experimental Data Analysis, Kriging Interpolation Method, and Computational Intelligence Techniques Open
In the present study, a new approach by coupling the interpolation method with computation-based technique (data-mining algorithms and an optimization algorithm) is introduced for modeling and optimization removal of Reactive Orange 7 (RO7…
View article: Development of Dam-Break Model Considering Real Case Studies with Asymmetric Reservoirs
Development of Dam-Break Model Considering Real Case Studies with Asymmetric Reservoirs Open
Dam-break flow is known as one of the most horrible phenomena. Some hypothetical reservoir geometries were evaluated in literature, but in nature, each reservoir has a unique geometry. In the present research, dam-break flow was studied ba…
View article: A Novel LSSVM Model Integrated with GBO Algorithm to Assessment of Water Quality Parameters
A Novel LSSVM Model Integrated with GBO Algorithm to Assessment of Water Quality Parameters Open
In this study, a novel least square support vector machine (LSSVM) model integrated with gradient-based optimizer (GBO) algorithm is introduced for assessment of water quality parameters. For this purpose, three stations including Ahvaz, A…
View article: Modeling and predicting suspended sediment load under climate change conditions: a new hybridization strategy
Modeling and predicting suspended sediment load under climate change conditions: a new hybridization strategy Open
In the present study, for the first time, a new strategy based on a combination of the hybrid least-squares support-vector machine (LS-SVM) and flower pollination algorithm (FPA), average 24 general circulation model (GCM) output, and delt…
View article: Forecasting Daily and Monthly Reference Evapotranspiration in the Aidoghmoush Basin Using Multilayer Perceptron Coupled with Water Wave Optimization
Forecasting Daily and Monthly Reference Evapotranspiration in the Aidoghmoush Basin Using Multilayer Perceptron Coupled with Water Wave Optimization Open
The aim of this study is to evaluate the ability of soft computing models including multilayer perceptron‐ (MLP‐) water wave optimization (MLP‐WWO), MLP‐particle swarm optimization (MLP‐PSO), and MLP‐genetic algorithm (MLP‐GA), to simulate…
View article: Shape Optimization of Gravity Dams Using a Nature-Inspired Approach
Shape Optimization of Gravity Dams Using a Nature-Inspired Approach Open
In water infrastructures design problems, small changes in their geometries lead to a major variation in the construction time and costs. Dams are such important water infrastructures, which have different types regarding their materials a…
View article: Optimization of dam's spillway design under climate change conditions
Optimization of dam's spillway design under climate change conditions Open
The present research introduces a model to find the best shape of a dam's spillway under climate change impacts, considering a benchmark problem (i.e., Ute Dam's labyrinth spillway in the Canadian River watershed, New Mexico, USA). A spill…
View article: Modeling of qualitative parameters (Electrical conductivity and total dissolved solids) of Karun river at Mollasani, Ahvaz and Farsiat stations using data mining methods
Modeling of qualitative parameters (Electrical conductivity and total dissolved solids) of Karun river at Mollasani, Ahvaz and Farsiat stations using data mining methods Open
Background and Objective: In the present study, EC and TDS quality parameters of Karun River were modeled using data-mining algorithms including LSSVM, ANFIS, and ANN, at Mollasani, Ahvaz and Farsiat hydrometric stations. Material and Meth…
View article: Effect of MDF-Cover for Water Reservoir Evaporation Reduction, Experimental, and Soft Computing Approaches
Effect of MDF-Cover for Water Reservoir Evaporation Reduction, Experimental, and Soft Computing Approaches Open
In the civil engineering designs and water resources management projects, various methods have been proposed to prevent the evaporation of water storage tanks and pools, including the use of physical materials. The use of MDF sheets is an …
View article: Investigating the Chaotic Nature of Flow the Upstream and Downstream of Zayandehrud-Dam Reservoir Using Chaotic Systems’ Criteria
Investigating the Chaotic Nature of Flow the Upstream and Downstream of Zayandehrud-Dam Reservoir Using Chaotic Systems’ Criteria Open
River discharge is among the influential factors on the operation of water resources systems and the design of hydraulic structures, such as dams; so the study of it is of great importance. Several effective factors on this non-linear phen…