Search Results for author: Amir Mosavi

Found 60 papers, 0 papers with code

A Bayesian Framework on Asymmetric Mixture of Factor Analyser

no code implementations1 Nov 2022 Hamid Reza Safaeyan, Karim Zare, Mohamad R. Mahmoudi, Amir Mosavi

In this paper, an MFA model with a rich and flexible class of skew normal (unrestricted) generalized hyperbolic (called SUNGH) distributions along with a Bayesian structure with several computational benefits have been introduced.

Performance Evaluation of Query Plan Recommendation with Apache Hadoop and Apache Spark

no code implementations17 Sep 2022 Elham Azhir, Mehdi Hosseinzadeh, Faheem Khan, Amir Mosavi

Apache Spark and Apache Hadoop frameworks are used in the present investigation to cluster different sizes of query datasets in the MapReduce-based access plan recommendation method.

Distributed Computing

A Secure Healthcare 5.0 System Based on Blockchain Technology Entangled with Federated Learning Technique

no code implementations16 Sep 2022 Abdur Rehman, Sagheer Abbas, M. A. Khan, Taher M. Ghazal, Khan Muhammad Adnan, Amir Mosavi

The purpose of this study is to construct a secure health monitoring system in healthcare 5. 0 by utilizing a blockchain technology and Intrusion Detection System (IDS) to detect any malicious activity in a healthcare network and enables physicians to monitor patients through medical sensors and take necessary measures periodically by predicting diseases.

Federated Learning Intrusion Detection

Prediction of the energy and exergy performance of F135 PW100 turbofan engine via deep learning

no code implementations24 Aug 2022 Mohammadreza Sabzehali, Amir Hossein Rabieeb, Mahdi Alibeigia, Amir Mosavi

Based on the results obtained in the first phase, to model the thermodynamic performance of the aforementioned engine cycle, Flight-Mach number and flight altitude are considered to be 2. 5 and 30, 000 m, respectively; due to the operational advantage of supersonic flying at high altitude flight conditions, and the higher thrust of hydrogen fuel.

Energy-Exergy Analysis and Optimal Design of a Hydrogen Turbofan Engine

no code implementations14 Aug 2022 Mohammadreza Sabzehali, Somayeh Davoodabadi Farahani, Amir Mosavi

In on design conditions, entropy generation rate, nitrogen oxide production rate, and TSFC for the chosen cycle based on the economic approach +18. 89 percent, +10. 01 percent, and -0. 21percent, respectively, and based on the exero-environmental approach -54. 03percent, -42. 02percent, and +21. 44percent change compared to the base engine, respectively.

Accurate Discharge Coefficient Prediction of Streamlined Weirs by Coupling Linear Regression and Deep Convolutional Gated Recurrent Unit

no code implementations12 Apr 2022 Weibin Chen, Danial Sharifrazi, Guoxi Liang, Shahab S. Band, Kwok Wing Chau, Amir Mosavi

Streamlined weirs which are a nature-inspired type of weir have gained tremendous attention among hydraulic engineers, mainly owing to their established performance with high discharge coefficients.

Integration of neural network and fuzzy logic decision making compared with bilayered neural network in the simulation of daily dew point temperature

no code implementations23 Feb 2022 Guodao Zhang, Shahab S. Band, Sina Ardabili, Kwok-wing Chau, Amir Mosavi

Whilst the ANFIS model is extremely stable for almost all numbers of membership functions, the BNN model is highly sensitive to this scale factor to predict DPT.

Decision Making

The Effect of Marketing Investment on Firm Value and Systematic Risk

no code implementations29 Apr 2021 Musaab Mousa, Saeed Nosratabadi, Judit Sagi, Amir Mosavi

Since a firm's ownership concentration is a determinant factor in firm value and systematic risk, this variable is considered a moderated variable in the relationship between marketing investment and firm value and systematic risk.


Time series forecasting of new cases and new deaths rate for COVID-19 using deep learning methods

no code implementations28 Apr 2021 Nooshin Ayoobi, Danial Sharifrazi, Roohallah Alizadehsani, Afshin Shoeibi, Juan M. Gorriz, Hossein Moosaei, Abbas Khosravi, Saeid Nahavandi, Abdoulmohammad Gholamzadeh Chofreh, Feybi Ariani Goni, Jiri Jaromir Klemes, Amir Mosavi

This study is novel as it carries out a comprehensive evaluation of the aforementioned three deep learning methods and their bidirectional extensions to perform prediction on COVID-19 new cases and new death rate time series.

Time Series Forecasting

Driving Factors Behind the Social Role of Retail Centers on Recreational Activities

no code implementations6 Apr 2021 Sepideh Baghaee, Saeed Nosratabadi, Farshid Aram, Amir Mosavi

Accordingly, two hypotheses were raised illustrating that the travel time (i. e., the time it takes for a customer to reach the retail center) and the variety of shops (in a retail center) increase the percentage of people who spend their leisure time and recreational activities retail centers.

Machine Learning versus Mathematical Model to Estimate the Transverse Shear Stress Distribution in a Rectangular Channel

no code implementations6 Mar 2021 Babak Lashkar-Ara, Niloofar Kalantari, Zohreh Sheikh Khozani, Amir Mosavi

The results of the sensitivity analysis show that the most influential parameter for the SSD in a smooth rectangular channel is the dimensionless parameter B/H, Where the transverse coordinate is B, and the flow depth is H. With the parameters (b/B), (B/H) for the bed and (z/H), (B/H) for the wall as inputs, the modeling of the GP was better than the other one.

BIG-bench Machine Learning

Analyzing Uniaxial Compressive Strength of Concrete Using a Novel Satin Bowerbird Optimizer

no code implementations4 Mar 2021 Hossein Moayedi, Amir Mosavi

Surmounting the complexities in analyzing the mechanical parameters of concrete entails selecting an appropriate methodology.

Synthesizing multi-layer perceptron network with ant lion, biogeography-based dragonfly algorithm evolutionary strategy invasive weed and league champion optimization hybrid algorithms in predicting heating load in residential buildings

no code implementations13 Feb 2021 Hossein Moayedi, Amir Mosavi

The significance of heating load (HL) accurate approximation is the primary motivation of this research to distinguish the most efficient predictive model among several neural-metaheuristic models.

Hybrid Artificial Intelligence Methods for Predicting Air Demand in Dam Bottom Outlet

no code implementations13 Feb 2021 Aliakbar Narimani, Mahdi Moghimi, Amir Mosavi

In large infrastructures such as dams, which have a relatively high economic value, ensuring the proper operation of the associated hydraulic facilities in different operating conditions is of utmost importance.

Adaptive Neuro-Fuzzy Inference System and a Multilayer Perceptron Model Trained with Grey Wolf Optimizer for Predicting Solar Diffuse Fraction

no code implementations13 Sep 2020 Randall Claywell, Laszlo Nadai, Felde Imre, Amir Mosavi

The accurate prediction of the solar Diffuse Fraction (DF), sometimes called the Diffuse Ratio, is an important topic for solar energy research.

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

no code implementations12 Jul 2020 Mostafa Emadi, Ruhollah Taghizadeh-Mehrjardi, Ali Cherati, Majid Danesh, Amir Mosavi, Thomas Scholten

The SOC content was the highest in udic soil moisture regime class with mean values of 4 percent, followed by the aquic and xeric classes, respectively.

BIG-bench Machine Learning

Generation expansion planning in the presence of wind power plants using a genetic algorithm model

no code implementations7 Jul 2020 Ali Sahragard, Hamid Falaghi, Mahdi Farhadi, Amir Mosavi, Abouzar Estebsari

The purpose of GEP is to enhance construction planning and reduce the costs of installing different types of power plants.

Modeling and Uncertainty Analysis of Groundwater Level Using Six Evolutionary Optimization Algorithms Hybridized with ANFIS, SVM, and ANN

no code implementations28 Jun 2020 Akram Seifi, Mohammad Ehteram, Vijay P. Singh, Amir Mosavi

The results showed that the ANFIS-GOA was superior to the other hybrid models for predicting GWL in the first piezometer and third piezometer in the testing stage.

Prediction Intervals Time Series

A Mobile Cloud-Based eHealth Scheme

no code implementations15 Apr 2020 Yihe Liu, Aaqif Afzaal Abbasi, Atefeh Aghaei, Almas Abbasi, Amir Mosavi, Shahab Shamshirband, Mohammed A. A. Al-qaness

Mobile cloud computing is an emerging field that is gaining popularity across borders at a rapid pace.

Dynamic Modeling and Adaptive Controlling in GPS-Intelligent Buoy (GIB) Systems Based on Neural-Fuzzy Networks

no code implementations3 Apr 2020 Dangquan Zhang, Muhammad Aqeel Ashraf, Zhenling Liu, Wan-Xi Peng, Mohammad Javad Golkar, Amir Mosavi

Given the importance of controlling the position of buoys and the construction of intelligent systems, in this paper, dynamic system modeling is applied to position marine buoys through the improved neural network with a backstepping technique.

Data Science in Economics

no code implementations19 Mar 2020 Saeed Nosratabadi, Amir Mosavi, Puhong Duan, Pedram Ghamisi

The data science advances are investigated in three individual classes of deep learning models, ensemble models, and hybrid models.


Sustainable Banking; Evaluation of the European Business Models

no code implementations18 Mar 2020 Saeed Nosratabadi, Gergo Pinter, Amir Mosavi, Sandor Semperger

The proposed business model components of this study were ranked in terms of their impact on achieving sustainability goals.

Novel Meta-Heuristic Model for Discrimination between Iron Deficiency Anemia and B-Thalassemia with CBC Indices Based on Dynamic Harmony Search

no code implementations3 Mar 2020 Sultan Noman Qasem, Amir Mosavi

In recent decades, attention has been directed at anemia classification for various medical purposes, such as thalassemia screening and predicting iron deficiency anemia (IDA).

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

no code implementations24 Feb 2020 Shahab Shamshirband, Amir Mosavi, Narjes Nabipour, Kwok-wing Chau

In this regard, EC-EARTH near surface wind outputs obtained from CORDEX-MENA simulations are used for historical and future projection of the energy.

Performance Analysis of Combine Harvester using Hybrid Model of Artificial Neural Networks Particle Swarm Optimization

no code implementations22 Feb 2020 Laszlo Nadai, Felde Imre, Sina Ardabili, Tarahom Mesri Gundoshmian, Pinter Gergo, Amir Mosavi

Novel applications of artificial intelligence for tuning the parameters of industrial machines for optimal performance are emerging at a fast pace.

BIG-bench Machine Learning

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

no code implementations14 Feb 2020 Saeed Samadianfard, Sajjad Hashemi, Katayoun Kargar, Mojtaba Izadyar, Ali Mostafaeipour, Amir Mosavi, Narjes Nabipour, Shahaboddin Shamshirband

In the current study, for predicting wind speed at target stations in the north of Iran, the combination of a multi-layer perceptron model (MLP) with the Whale Optimization Algorithm (WOA) used to build new method (MLP-WOA) with a limited set of data (2004-2014).

Prediction of Discharge Capacity of Labyrinth Weir with Gene Expression Programming

no code implementations16 Jan 2020 Hossein Bonakdari, Isa Ebtehaj, Bahram Gharabaghi, Ali Sharifi, Amir Mosavi

This paper proposes a model based on gene expression programming for predicting the discharge coefficient of triangular labyrinth weirs.

A Bayesian Monte-Carlo Uncertainty Model for Assessment of Shear Stress Entropy

no code implementations10 Jan 2020 Amin Kazemian-Kale-Kale, Azadeh Gholami, Mohammad Rezaie-Balf, Amir Mosavi, Ahmed A Sattar, Bahram Gharabaghi, Hossein Bonakdari

We present a novel method to evaluate the uncertainty of four popular entropy models, including Shannon, Shannon-Power Low (PL), Tsallis, and Renyi, in shear stress estimation in circular channels.

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

no code implementations9 Jan 2020 Narjes Nabipour, Amir Mosavi, Eva Hajnal, Laszlo Nadai, Shahab Shamshirband, Kwok-wing Chau

The near-surface wind data obtained from a regional climate model are employed to investigate climate change impacts on the wind power resources in the Caspian Sea.


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

no code implementations31 Dec 2019 Narjes Nabipour, Amir Mosavi, Alireza Baghban, Shahaboddin Shamshirband, Imre Felde

Calculating hydrocarbon components solubility of natural gases is known as one of the important issues for operational works in petroleum and chemical engineering.

Simulation of Turbulent Flow around a Generic High-Speed Train using Hybrid Models of RANS Numerical Method with Machine Learning

no code implementations25 Dec 2019 Alireza Hajipour, Arash Mirabdolah Lavasani, Mohammad Eftekhari Yazdi, Amir Mosavi, Shahaboddin Shamshirband, Kwok-wing Chau

So, drag, lift, and side forces and also minimum and a maximum of pressure coefficients for mentioned wind directions and velocity are predicted and compared using statistical parameters.


Shear Stress Distribution Prediction in Symmetric Compound Channels Using Data Mining and Machine Learning Models

no code implementations20 Dec 2019 Zohreh Sheikh Khozani, Khabat Khosravi, Mohammadamin Torabi, Amir Mosavi, Bahram Rezaei, Timon Rabczuk

Finally, the most powerful data mining method which studied in this research (RF) compared with two well-known analytical models of Shiono and Knight Method (SKM) and Shannon method to acquire the proposed model functioning in predicting the shear stress distribution.

BIG-bench Machine Learning

Applying ANN, ANFIS, and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO$_2$

no code implementations21 Nov 2019 Amin Bemani, Alireza Baghban, Shahaboddin Shamshirband, Amir Mosavi, Peter Csiba, Annamaria R. Varkonyi-Koczy

In the present work, a novel and the robust computational investigation is carried out to estimate solubility of different acids in supercritical carbon dioxide.

Developing an ANFIS PSO Model to Estimate Mercury Emission in Combustion Flue Gases

no code implementations16 Sep 2019 Shahaboddin Shamshirband, Masoud Hadipoor, Alireza Baghban, Amir Mosavi, Jozsef Bukor, Annamaria Varkonyi Koczy

Accurate prediction of mercury content emitted from fossil fueled power stations is of utmost important for environmental pollution assessment and hazard mitigation.


Deep Learning for Detecting Building Defects Using Convolutional Neural Networks

no code implementations6 Aug 2019 Husein Perez, Joseph H. M. Tah, Amir Mosavi

Clients are increasingly looking for fast and effective means to quickly and frequently survey and communicate the condition of their buildings so that essential repairs and maintenance work can be done in a proactive and timely manner before it becomes too dangerous and expensive.

Multi-label Classification for Fault Diagnosis of Rotating Electrical Machines

no code implementations2 Aug 2019 Adrienn Dineva, Amir Mosavi, Mate Gyimesi, Istvan Vajda

The contribution of this work is to propose a novel methodology using multi-label classification method for simultaneously diagnosing multiple faults and evaluating the fault severity under noisy conditions.

Classification Fault Detection +2

Modeling Daily Pan Evaporation in Humid Climates Using Gaussian Process Regression

no code implementations1 Aug 2019 Sevda Shabani, Saeed Samadianfard, Mohammad Taghi Sattari, Shahab Shamshirband, Amir Mosavi, Tibor Kmet, Annamaria R. Varkonyi-Koczy

Evaporation is one of the main processes in the hydrological cycle, and it is one of the most critical factors in agricultural, hydrological, and meteorological studies.

GPR regression

Sensitivity study of ANFIS model parameters to predict the pressure gradient with combined input and outputs hydrodynamics parameters in the bubble column reactor

no code implementations19 Jul 2019 Shahaboddin Shamshirband, Amir Mosavi, Kwok-wing Chau

This new process of mapping inputs and outputs data provides a framework to fully understand the flow in the fluid domain in a short time of fuzzy structure calculation.

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

no code implementations26 May 2019 Danial Mohammadzadeh, Seyed-Farzan Kazemi, Amir Mosavi, Ehsan Nasseralshariati, Joseph H. M. Tah

In construction projects, estimation of the settlement of fine-grained soils is of critical importance, and yet is a challenging task.

Particle swarm optimization model to predict scour depth around bridge pier

no code implementations26 May 2019 Shahaboddin Shamshirband, Amir Mosavi, Timon Rabczuk

To improve the efficiency of the proposed model, individual equations are derived for laboratory and field data.


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