World's Best Scientists 2026 revealed!
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Computer Science
Hungary
2026

D-Index & Metrics

Computer Science

D-Index
77
Citations
19180
World Ranking
1298
National Ranking
1

Research.com Recognitions

  • 2026 - Research.com Computer Science in Hungary Leader Award
  • 2025 - Research.com Computer Science in Hungary Leader Award
  • 2022 - Research.com Computer Science in Hungary Leader Award

Overview

Amir Mosavi is affiliated with Óbuda University in Hungary and has contributed extensively to research in engineering and its related subfields. Their body of work covers a wide range of topics within engineering, with a strong focus on the application of artificial intelligence across various disciplines.

Their main field of study is Engineering, with particular specialization in the following subfields:

  • Civil and Structural Engineering
  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Environmental Engineering
  • Building and Construction

Amir Mosavi's research addresses a number of key topics, including:

  • Energy Load and Power Forecasting
  • Hydrological Forecasting Using AI
  • COVID-19 diagnosis using AI
  • Hydrology and Watershed Management Studies
  • COVID-19 epidemiological studies
  • Innovative concrete reinforcement materials
  • Hydraulic flow and structures

They have published prolifically in several recognized venues, with frequent contributions to:

  • Preprints.org
  • Engineering Applications of Computational Fluid Mechanics
  • arXiv (Cornell University)
  • IEEE Access
  • SSRN Electronic Journal

Their recent papers illustrate an emphasis on machine learning and predictive analytics applied to engineering and epidemiology:

  • "Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis" (2020) published in IEEE Access
  • "COVID-19 Outbreak Prediction with Machine Learning" (2020) published in Algorithms
  • "Deep Learning for Stock Market Prediction" (2020) published in Entropy
  • "Predicting Standardized Streamflow index for hydrological drought using machine learning models" (2020) published in Engineering Applications of Computational Fluid Mechanics
  • "COVID-19 Pandemic Prediction for Hungary; A Hybrid Machine Learning Approach" (2020) published in Mathematics

Amir collaborates frequently with several co-authors whose joint work has spanned numerous publications. Among the most frequent co-authors are:

  • Shahab S. Band
  • Sina Ardabili
  • Kwok-wing Chau
  • Narjes Nabipour
  • Shahaboddin Shamshirband

Best Publications

  • Flood prediction using machine learning models: Literature review

    Amir Mosavi;Pinar Ozturk;Kwok Wing Chau

  • An ensemble prediction of flood susceptibility using multivariate discriminant analysis, classification and regression trees, and support vector machines

    Bahram Choubin;Bahram Choubin;Ehsan Moradi;Mohammad Golshan;Jan Adamowski

  • State of the Art of Machine Learning Models in Energy Systems, a Systematic Review

    Amir Mosavi;Amir Mosavi;Amir Mosavi;Mohsen Salimi;Sina Faizollahzadeh Ardabili;Timon Rabczuk

  • Sustainable Business Models: A Review

    Saeed Nosratabadi;Amir Mosavi;Shahaboddin Shamshirband;Edmundas Kazimieras Zavadskas

  • COVID-19 outbreak prediction with machine learning

    Sina F. Ardabili;Amir Mosavi;Pedram Ghamisi;Filip Ferdinand

  • Predicting and Mapping of Soil Organic Carbon Using Machine Learning Algorithms in Northern Iran

    Mostafa Emadi;Ruhollah Taghizadeh-Mehrjardi;Ali Cherati;Majid Danesh

  • Sustainable business models: A review

    Saeed Nosratabadi;Amir Mosavi;Shahaboddin Shamshirband;Edmundas Kazimieras Zavadskas

  • Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis

    Mojtaba Nabipour;Pooyan Nayyeri;Hamed Jabani;S Shahab

  • Deep Learning for Stock Market Prediction

    M. Nabipour;P. Nayyeri;H. Jabani;A. Mosavi;A. Mosavi

  • Flash-flood hazard assessment using ensembles and Bayesian-based machine learning models: Application of the simulated annealing feature selection method.

    Farzaneh Sajedi Hosseini;Bahram Choubin;Amir Mosavi;Narjes Nabipour

  • COVID-19 pandemic prediction for Hungary; A hybrid machine learning approach

    Gergo Pinter;Imre Felde;Amir Mosavi;Pedram Ghamisi

  • Deep Learning for Detecting Building Defects Using Convolutional Neural Networks

    Husein Perez;Joseph H. M. Tah;Amir Mosavi

  • Predicting Standardized Streamflow index for hydrological drought using machine learning models

    Shahabbodin Shamshirband;Sajjad Hashemi;Hana Salimi;Saeed Samadianfard

  • Evaluating urban flood risk using hybrid method of TOPSIS and machine learning

    Elham Rafiei-Sardooi;Ali Azareh;Bahram Choubin;Amir H. Mosavi;Amir H. Mosavi

  • Integrated machine learning methods with resampling algorithms for flood susceptibility prediction.

    Esmaeel Dodangeh;Bahram Choubin;Ahmad Najafi Eigdir;Narjes Nabipour

  • Flash Flood Susceptibility Modeling Using New Approaches of Hybrid and Ensemble Tree-Based Machine Learning Algorithms

    Shahab S. Band;Saeid Janizadeh;Subodh Chandra Pal;Asish Saha

  • Wind speed prediction using a hybrid model of the multi-layer perceptron and whale optimization algorithm

    Saeed Samadianfard;Sajjad Hashemi;Katayoun Kargar;Mojtaba Izadyar

  • Advances in Machine Learning Modeling Reviewing Hybrid and Ensemble Methods

    Sina Ardabili;Amir Mosavi;Amir Mosavi;Annamária R. Várkonyi-Kóczy

  • Prediction of Hydropower Generation Using Grey Wolf Optimization Adaptive Neuro-Fuzzy Inference System

    Majid Dehghani;Hossein Riahi-Madvar;Farhad Hooshyaripor;Amir Mosavi;Amir Mosavi

  • Modeling Pan Evaporation Using Gaussian Process Regression K-Nearest Neighbors Random Forest and Support Vector Machines; Comparative Analysis

    Sevda Shabani;Saeed Samadianfard;Mohammad Taghi Sattari;Amir Mosavi

  • Ensemble Boosting and Bagging Based Machine Learning Models for Groundwater Potential Prediction

    Amirhosein Mosavi;Farzaneh Sajedi Hosseini;Bahram Choubin;Massoud Goodarzi

  • Ensemble models with uncertainty analysis for multi-day ahead forecasting of chlorophyll a concentration in coastal waters

    Shahaboddin Shamshirband;Ehsan Jafari Nodoushan;Jason E. Adolf;Azizah Abdul Manaf

  • Prediction of Compression Index of Fine-Grained Soils Using a Gene Expression Programming Model

    Danial Mohammadzadeh;Seyed-Farzan Kazemi;Amir Mosavi;Ehsan Nasseralshariati

  • A New Online Learned Interval Type-3 Fuzzy Control System for Solar Energy Management Systems

    Zhi Liu;Ardashir Mohammadzadeh;Hamza Turabieh;Majdi Mafarja

  • Snow avalanche hazard prediction using machine learning methods

    Bahram Choubin;Moslem Borji;Amir Mosavi;Amir Mosavi;Farzaneh Sajedi-Hosseini

Frequent Co-Authors

Shahab S. Band
Shahab S. Band National Yunlin University of Science and Technology
Kwok-wing Chau
Kwok-wing Chau Hong Kong Polytechnic University
Pedram Ghamisi
Pedram Ghamisi Helmholtz-Zentrum Dresden-Rossendorf
Alireza Baghban
Alireza Baghban Amirkabir University of Technology
Hossein Moayedi
Hossein Moayedi Duy Tan University
Hossein Bonakdari
Hossein Bonakdari University of Ottawa
Edmundas Kazimieras Zavadskas
Edmundas Kazimieras Zavadskas Vilnius Gediminas Technical University
Roohallah Alizadehsani
Roohallah Alizadehsani Deakin University
Bahram Gharabaghi
Bahram Gharabaghi University of Guelph
Isa Ebtehaj
Isa Ebtehaj Université Laval

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