most citedCoronary Artery Disease Diagnosis; Ranking the Significant Features Using Random Trees Model

148 citations · 152 across the 11 of their papers we have counts for

collaborators

11 papers

cs.LG2020

Extreme learning machine-based model for Solubility estimation of hydrocarbon gases in electrolyte solutions

Narjes Nabipour, Amir Mosavi, Alireza Baghban +2

Calculating hydrocarbon components solubility of natural gases is known as one of the important issues for operational works in petroleum and chemical engineering. In this work, a…

cs.CR2020

A Secure and Improved Multi Server Authentication Protocol Using Fuzzy Commitment

Hafeez Ur Rehman, Anwar Ghani, Shehzad Ashraf Chaudhry +2

Very recently, Barman et al. proposed a multi-server authentication protocol using fuzzy commitment. The authors claimed that their protocol provides anonymity while resisting all…

physics.ao-ph2020★ 3 cited

Application of ERA5 and MENA simulations to predict offshore wind energy potential

Shahab Shamshirband, Amir Mosavi, Narjes Nabipour +1

This study explores wind energy resources in different locations through the Gulf of Oman and also their future variability due climate change impacts. In this regard, EC-EARTH nea…

cond-mat.soft2020★ 1 cited

Comparative analysis of machine learning models for Ammonia Capture of Ionic Liquids

Shahaboddin Shamshirband, Narjes Nabipour, Masoud Hadipoor +2

Industry uses various solvents in the processes of refrigeration and ventilation. Among them, the Ionic liquids (ILs) as the relatively new solvents, are known for their proven eco…

cs.LG2020

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

Saeed Samadianfard, Sajjad Hashemi, Katayoun Kargar +5

Wind power as a renewable source of energy, has numerous economic, environmental and social benefits. In order to enhance and control renewable wind power, it is vital to utilize m…

eess.SP2020

Intelligent Road Inspection with Advanced Machine Learning; Hybrid Prediction Models for Smart Mobility and Transportation Maintenance Systems

Nader Karballaeezadeh, Farah Zaremotekhases, Shahaboddin Shamshirband +4

Prediction models in mobility and transportation maintenance systems have been dramatically improved through using machine learning methods. This paper proposes novel machine learn…

physics.med-ph2020★ 148 cited

Coronary Artery Disease Diagnosis; Ranking the Significant Features Using Random Trees Model

Javad Hassannataj Joloudari, Edris Hassannataj Joloudari, Hamid Saadatfar +6

Heart disease is one of the most common diseases in middle-aged citizens. Among the vast number of heart diseases, the coronary artery disease (CAD) is considered as a common cardi…

physics.ao-ph2020

Spatial Analysis of Seasonal Precipitation over Iran: Co-Variation with Climate Indices

Majid Dehghani, Somayeh Salehi, Amir Mosavi +3

Temporary changes in precipitation may lead to sustained and severe drought or massive floods in different parts of the world. Knowing variation in precipitation can effectively he…

physics.ao-ph2020

Modeling Climate Change Impact on Wind Power Resources Using Adaptive Neuro-Fuzzy Inference System

Narjes Nabipour, Amir Mosavi, Eva Hajnal +3

Climate change impacts and adaptations are the subjects to ongoing issues that attract the attention of many researchers. Insight into the wind power potential in an area and its p…

cs.LG2020

Prediction of flow characteristics in the bubble column reactor by the artificial pheromone-based communication of biological ants

Shahab Shamshirband, Meisam Babanezhad, Amir Mosavi +4

In order to perceive the behavior presented by the multiphase chemical reactors, the ant colony optimization algorithm was combined with computational fluid dynamics (CFD) data. Th…

eess.IV2019

Hybrid Machine Learning Model of Extreme Learning Machine Radial basis function for Breast Cancer Detection and Diagnosis; a Multilayer Fuzzy Expert System

Sanaz Mojrian, Gergo Pinter, Javad Hassannataj Joloudari +4

Mammography is often used as the most common laboratory method for the detection of breast cancer, yet associated with the high cost and many side effects. Machine learning predict…