148 citations · 151 across the 10 of their papers we have counts for
11 papers
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…
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…
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…
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…
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…
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…