Taher Rajaee

Taher Rajaee
University of Qom · Civil Engineering

Assistant Professor

About

47
Publications
11,055
Reads
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1,549
Citations
Additional affiliations
January 2015 - present
University of Qom
Position
  • Professor (Associate)

Publications

Publications (47)
Article
Full-text available
In this study the fluctuating loads of the control gate in the experimental model of the bottom outlet of a dam was evaluated. The production, transportation, and dissipation of turbulent flow eddies based on Kolmogorov theory were investigated by image processing of the flow under the control gate, time series of velocity and static pressure fluct...
Book
Full-text available
انسیس فلوئنت یک نرم افزار دینامیک سیّالات محاسباتی، بر پایه روش حجم محدود – المان محدود است که علاوه بر دقت بالا در تخمین پارامترهای جامد و سیّال مورد مطالعه، اندرکنش بین آنها را نیز محاسبه می کند. با در اختیار داشتن پردازنده سریع و به کارگیری روش پردازش موازی، می توان بر دقت و سرعت شبیه سازی ها افزود. درواقع، انسیس فلوئنت به دلیل قدرت و سرعت بالای...
Article
Full-text available
One way to mitigate the risk of consumption of contaminated water in water distribution networks is optimal placement of the quality sensors. A considerable challenge in this respect is the significance of contamination at a junction. Beside the population affected and the volume of the contaminated water consumed, importance of each junction is a...
Article
Full-text available
The inconveniences of introducing and modifying the mesh grids in mesh-based numerical methods lead the researchers to meshfree methods. In this research the steady-state numerical solution of incompressible continuity and Navier–Stokes equations, and the standard k-Ɛ turbulence model was investigated in a 2D domain. The computational domain consis...
Article
In the past decades, climate change, population growth, urbanization, changes in land-use, and outdated runoff collecting networks have affected the quantity and quality of urban runoff in many countries. In this research, a new methodology for planning green infrastructures (GI) for runoff water quality improvement in urban areas was proposed. Thi...
Article
One of the ways to reduce the risk of contaminated water consumption is to optimally locate the quality sensors. These sensors warn users in the case of contamination detection. Analyzing the actual conditions of the contamination enter to the network is faced with many uncertainties. These uncertainties include the dose of contamination, time and...
Article
The article Tracing and assessment of simultaneous dust storms in the cities of Ahvaz and Kermanshah in western Iran based on the new approach, written by Taher Rajaee, Nima Rohani, Ehsan Jabbari, Barat Mojaradi, was originally published electronically on the publisher’s internet portal (currently SpringerLink) on 12 June 2020 with open access. Wit...
Article
Full-text available
One of the most important and relatively new natural disaster compared with others is the dust-storm phenomenon in today’s world, which has been aggravated by rising drought and global warming. Studies on the phenomenon of dust have different aspects and characteristics. To study this phenomenon, the use of meteorological models such as HYSPLIT, as...
Article
Full-text available
Prediction of biochemical oxygen demand (BOD) as the main pollution indicators of organic pollution in freshwater resources is necessary. In the present work, a hybrid wavelet-genetic programming (WGP) method was implemented to improve prediction of BOD. The Shannon entropy was used to identify the optimal input combinations of WGP. In addition, an...
Article
Simulation approaches employed in sediment processes are important for watershed management and environmental impact assessment. Use of Stochastic models that based on time series observations and do not require heavy calculations and complex relationships is developing. Recent years, artificial intelligence (AI) techniques have developed to improv...
Article
The need for accurate predictions of water quality in rivers has encouraged researchers to develop new methods and to improve the predictive ability of conventional models. In recent years artificial intelligence (AI)-based methods have been recognized significantly powerful for this purpose. In this study, the performance of the various types of s...
Article
Full-text available
The complex nature of water resources and the related uncertainty cause decision making to be difficult in practice. In this study, two multi-criteria decision making (MCDM) methods, Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), were applied to determine the best scenario adapti...
Article
Full-text available
This study is a review to the special issue on artificial intelligence (AI) methods for groundwater level (GWL) modeling and forecasting, and presents a brief overview of the most popular AI techniques, along with the bibliographic reviews of the experiences of the authors over past years, and the reviewing and comparison of the obtained results. A...
Article
Full-text available
Among the various water users, the agricultural sector is the largest consumer of water in the world. Thus, the implementation of agricultural adaptation strategies is essential for an optimal allocation of water resources in a changing climate. The objective of this study is to examine the changes in management criteria for a multi-purpose reservo...
Article
Full-text available
In this research, the behavior of the morning glory crest and throat were investigated in the event of flood. Spillway structure and dam reservoir fluid were respectively simulated using the finite element method and finite volume method in ANSYS software. The morning glory structure’s behavior was performed in three scenarios: a) the static analys...
Article
Full-text available
Prediction of pH is an important issue in managing water quality in surface waters (e.g., rivers, lakes) as well as drinking water. The capacity of artificial neural network (ANN), wavelet-artificial neural network (WANN), traditional multiple linear regression (MLR), and wavelet-multiple linear regression (WMLR) models to predict daily pH levels (...
Article
Full-text available
This paper introduces a Semivariance-Transinformation (S-T) based method for designing an optimum bay water nutrients monitoring network in San Francisco bay (S.F. bay), USA. Phosphorus and nitrogen are the most important nutrients that lead to eutrophic condition. The monthly phosphate and nitrate+nitrite data recorded during September 2006 to Aug...
Article
Full-text available
The purpose of this study is to evaluate Gharanghu multipurpose reservoir system (East Azerbaijan, Iran) using efficiency indexes (EIs) affected by climate change. At first, the effects of climate change on inflow to the reservoir, as well as changes in the demand volume over a time interval of 30 years (2040–2069) are reviewed. Simulation results...
Article
The streamflows are important and effective factors in stream ecosystems and its accurate prediction is an essential and important issue in water resources and environmental engineering systems. A hybrid wavelet-linear genetic programming (WLGP) model, which includes a discrete wavelet transform (DWT) and a linear genetic programming (LGP) to predi...
Article
Simulation of groundwater level (GWL) fluctuations is an important task in management of groundwater resources. In this study, the effect of wavelet analysis on the training of the artificial neural network (ANN), multi linear regression (MLR) and support vector regression (SVR) approaches was investigated, and the ANN, MLR and SVR along with the w...
Article
Accurate estimates of air demand are critical when addressing cavitation phenomenon in bottom outlet conduits of dams. In the present study, this accuracy was evaluated for air demand estimation models using gene expression programming (GEP), classification tree methods [including boosted regression trees (BRT) and random forest (RF) algorithms], o...
Article
Full-text available
Concentration of dissolved oxygen (DO) is an indicator to evaluate environmental health in many riverine systems. In this study two hybrid models, the wavelet-based regression model (WR) and the wavelet-based artificial neural network model (WANN), are proposed for short-interval (one day ahead) and long-interval (31 days ahead) prediction of DO co...
Article
Full-text available
The paper presents an entropy-based method for designing an optimum bay water salinity monitoring network in San Francisco bay (S.F. bay) considering maximum-monitoring-information and minimum-data-lost criteria. Due to cost concerns, it is necessary to design the optimal salinity monitoring network with a minimal number of sampling stations to pro...
Article
Full-text available
Prediction of dissolved oxygen (DO) plays an important role in water resources especially in surface waters such as rivers. The oxygen affects a vast number of other water indicators. In this study, the artificial neural network (ANN) and a hybrid wavelet-ANN (WANN) models were considered to predict thirty minutes dissolved oxygen in the River Cald...
Article
River flow forecasting is important for successful water resources planning and management. The current study investigated the applicability of the artificial neural network (Ann), adaptive neuro-fuzzy inference system (Anfis), wavelet-Ann (Wann) and wavelet-Anfis (Wanfis) for daily river flow forecasting in Karaj River. Three scenarios were used....
Article
River flow forecasting is important for successful water resources planning and management. The current study investigated the applicability of the artificial neural network (Ann), adaptive neuro-fuzzy inference system (Anfis), wavelet-Ann (Wann) and wavelet-Anfis (Wanfis) for daily river flow forecasting in Karaj River. Three scenarios were used....
Article
Because of increasing worldwide contamination of coastal marine water in the last decades, the exact prediction of water quality parameters in these areas is an important factor in coastal management. In this study, the evaluation of wavelet-gene expression programing (WGEP) and wavelet-artificial neural network (WANN) hybrid model was assessed in...
Article
Full-text available
Wastewater reuse is considered as a solution to better management of the water resources that presents a viable method to solve water shortage problems, especially in regions where available water resources are limited. Selection of wastewater reuse application for different uses is a multidimensional process which involves multiple criteria and mu...
Article
Full-text available
The prediction of water quality parameters plays an important role in water resources and environmental systems. The use of electrical conductivity (EC) as a water quality indicator is one of the important parameters for estimating the amount of mineralization. This study describes the application of artificial neural network (ANN) and wavelet–neur...
Conference Paper
Full-text available
This study describes the application of Artificial Neural Network (ANN) and Wavelet-Artificial Neural Network (WANN) models for the prediction of Chloride (Cl-) content of Beshar River at Yasuj, Iran. Both models used 10 years (2002-2012) monthly variations of Shah Mokhtar Gauging Station’s water quality variables (E.C., K+ and Na+) as input parame...
Article
This study investigated the effects of upstream stations' flow records on the performance of artificial neural network (ANN) models for predicting daily watershed runoff. As a comparison, a multiple linear regression (MLR) analysis was also examined using various statistical indices. Five streamflow measuring stations on the Cahaba River, Alabama,...
Article
Accurate suspended sediment prediction is an integral component of sustainable water resources and environmental systems. This study considered artificial neural network (ANN), wavelet analysis and ANN combination (WANN), multilinear regression (MLR), and sediment rating curve (SRC) models for daily suspended sediment load (S) modeling in the Iowa...
Article
In this research, a new wavelet artificial neural network (WANN) model was proposed for daily suspended sediment load (SSL) prediction in rivers. In the developed model, wavelet analysis was linked to an artificial neural network (ANN). For this purpose, daily observed time series of river discharge (Q) and SSL in Yadkin River at Yadkin College, NC...
Article
Full-text available
This study investigated the prediction of suspended sediment load in a gauging station in the USA by neuro-fuzzy, conjunction of wavelet analysis and neuro-fuzzy as well as conventional sediment rating curve models. In the proposed wavelet analysis and neuro-fuzzy model, observed time series of river discharge and suspended sediment load were decom...
Article
The study of sediment load is important for its implications to the environment and water resources engineering. Four models were considered in the study of suspended sediment concentration prediction: artificial neural networks (ANNs), neuro-fuzzy model (NF), conjunction of wavelet analysis and neuro-fuzzy (WNF) model, and the conventional sedimen...
Article
Simulation approaches employed in suspended sediment processes are important in the areas of water resources and environmental engineering. In the current study, neuro-fuzzy (NF), a combination of wavelet transform and neuro-fuzzy (WNF), multi linear regression (MLR), and the conventional sediment rating curve (SRC) models were considered for suspe...
Article
This study investigated the prediction of suspended sediment load in a gauging station in the USA by neuro-fuzzy, conjunction of wavelet analysis and neuro-fuzzy as well as conventional sediment rating curve models. In the proposed wavelet analysis and neuro-fuzzy model, observed time series of river discharge and suspended sediment load were decom...
Article
In the present study, artificial neural networks (ANNs), neuro-fuzzy (NF), multi linear regression (MLR) and conventional sediment rating curve (SRC) models are considered for time series modeling of suspended sediment concentration (SSC) in rivers. As for the artificial intelligence systems, feed forward back propagation (FFBP) method and Sugeno i...
Article
Full-text available
Selenium transport and transformation were simulated in a soil column. A one-dimensional dynamic mathematical and computer model is formulated to simulate, selenate, selenite, selenomethionine, organic selenium, and gaseous selenium. This computer model is based on the mass balance equation, including convective transport, dispersive transport, sur...
Article
A 2D finite element model for the solution of wave equations is developed. The fluid is considered as incompressible and irrotational. This is a difficult mathematical problem to solve numerically as well as analytically because the condition of the dynamic boundary (Bernoulli's equation) on the free surface is not fixed and varies with time. The f...

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Projects (2)
Project
The main aim of the project developing heuristic data-driven methods for improving hydrological time series (river flow, ground water level, lake level etc.) forecasting.