Semnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863120230501The Effect of Different Types of Rare Earth Magnets on The Torque of Spoke-Type Permanent Magnet Vernier Motor15880210.22075/mseee.2024.32795.1139ENAliImanifarFaculty of Electrical and Computer Engineering (ECE), Semnan University, Semnan, Iran.HamidYaghobiFaculty of Electrical and Computer Engineering (ECE), Semnan University, Semnan, Iran.Journal Article20231226The Vernier motor family is a type of electric motor that provides high torque density at low speed. In this paper, the spoke-type permanent magnet Vernier motor, which is a new type of permanent magnet Vernier motor, is discussed, and the concept of rare earth magnets is also discussed. To check the output torque of spoke-type permanent magnet Vernier motors, different rare earth magnets have been placed and the output torque value has been calculated for each and compared with ordinary magnets which are more economical and cheaper. In this comparison, it is concluded that using a certain type of magnet has the best results in the output torque, and using a magnet is more economicalhttps://mseee.semnan.ac.ir/article_8802_d68e697d608751a9f9c7f0fb4c78f07f.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863120230501Artificial Intelligence for Predictive Analytics in the Petrochemical Industry: A Scoping Review712901610.22075/mseee.2024.32344.1133ENSaraMohammadiDepartment of Economics, Razi University, Kermanshah, IranSadeghSulaimanyDepartment of Computer Engineering, University of Kurdistan, Sananadaj, IranAsoMafakheriSBNA Lab, Department of Computer Engineering, University of Kurdistan, Sananadaj, IranJournal Article20231115The petrochemical industry, particularly in countries like China, the United States, Saudi Arabia, Russia, Germany, and Iran, plays a significant role in generating value in the petroleum and gas sector. This paper aims to systematically explore the literature to identify key concepts, theories, evidence, and research gaps on the use of artificial intelligence in the petrochemical industry. To achieve this, we conducted a scoping review of eligible English journals and conferences that focus on the computational approach to prediction in petrochemical issues. Our search and investigation, carried out on Google Scholar and Scopus, led to the identification of 34 relevant papers. Our findings, from an application perspective, span categories such as energy saving, leakage, failure and error, chemical and molecular, danger and fire, production processes, price and trade, maintenance, noise, and safety and health. In terms of the computational methods utilized, we identified different versions of neural networks, optimization algorithms, and traditional machine learning algorithms, Markov processes, dimension reduction, network analysis, randomized algorithms, and mathematical modeling. For future work, this paper suggests the exploration of underutilized but promising computational techniques for research problems in the petrochemical industry.https://mseee.semnan.ac.ir/article_9016_39d47a01b41676276f1111f8f0d382c2.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863120230501Prevention of Maloperation of the REF Relays Using Artificial Intelligence and Wavelet Transform1321880410.22075/mseee.2024.33363.1148ENHosseinShabani RoshanFaculty of Electrical and Computer Engineering (ECE), Semnan University, Semnan, Iran.ZahraMoravejFaculty of Electrical and Computer Engineering (ECE), Semnan University, Semnan, Iran.Ali AkbarAbdoosFaculty Electrical and Computer Engineering, Babol noshiravani University of Technology, Babol, Iran.AlirezaJodaeiFaculty of Electrical and Computer Engineering (ECE), Semnan University, Semnan, Iran.Journal Article20240223Restricted Earth Fault (REF) Relay, a type of differential protection, is responsible for detecting single-phase-to-ground faults at the terminal of a transformer or faults in the winding to the core. This protection scheme is inherently sensitive and rapid; however, due to current transformer saturation during external fault conditions with high currents and the transient magnetizing current flowing through the transformer core, it may be susceptible to false operation. In this paper, an intelligent restricted ground fault protection scheme based on wavelet transform (WT) is presented. In the initial step, the differential current resulting from the simulation is analyzed using WT, and various features of decomposed signals are extracted as sample patterns for training intelligent classifiers. The performance of the proposed method is evaluated using data obtained from the simulation of a 230/63.5 kV power transformer in the PSCAD/EMTDC software environment. Additionally, to accurately simulate the transformer current during saturation, the valid Gill's model is employed. The results of implementing this intelligent protection scheme confirm its high reliability against false operation.https://mseee.semnan.ac.ir/article_8804_6dd9b536547d415c2ff0fee1be7643e7.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863120230501An Adaptive Neuro Fuzzy Inference System based Method for DC Fault Recognition in VSC-MTDC System2336901710.22075/mseee.2024.34270.1160ENMahimaKumariDepartment of Electrical Engineering, National Institute of Technology Raipur, Chhattisgarh, India.AnamikaYadavDepartment of Electrical Engineering, National Institute of Technology Raipur, Chhattisgarh, India.Journal Article20240528This paper presents an Adaptive Neuro Fuzzy Inference System (ANFIS) method for recognizing the fault in a Voltage Source Converter-Multiterminal HVDC (VSC-MTDC) system. A four-terminal VSC-based HVDC system is designed in MATLAB software and used for the validation of research. The proposed scheme has advanced features that overcome the limitations of a fuzzy inference system, as it does not need an expert to provide the best performance. Artificial Neural Networks (ANNs) depend only on input and output data through the training process. ANFIS is a very effective method that combines the strengths of artificial neural networks (ANN) in learning from processes and the ability of fuzzy inference systems to deal with uncertain input. In order to protect against faults, two distinct FIS models have been developed to recognize pole-to-ground and pole-to-pole faults. The results indicate a trip signal when a fault is present, hence increasing the reliability of the system. This approach provides quick outcomes without taking any feedback from the remote end of the system.https://mseee.semnan.ac.ir/article_9017_21f53ce2379989043de0d861357bd433.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863120230501Investigating Factors Affecting the Cost of Money in Iranian Banks Based on Artificial Intelligence and Using Data Mining3745901810.22075/mseee.2024.33162.1144ENAliHaghi NojehdehDepartment of Management, Hamedan Branch, Islamic Azad University, Hamedan, Iran.MansourEsmaeilpourDepartment of Computer Engineering, Hamedan Branch, Islamic Azad University, Hamedan, Iran.0000-0002-2475-518XBehroozBayatDepartment of Knowledge and Information Science, Islamic Azad University, Hamadan Branch, Hamadan, Iran.AlirezaIsfandyari MoghaddamDepartment of Knowledge and Information Science, Islamic Azad University, Hamadan Branch, Hamadan, Iran.Journal Article20240202One of the potential goals of companies, including banks, is to earn profit and cover current expenses. Iranian banks have also been affected. Calculating and understanding the cost of money is very important because, by calculating and analyzing it, you can estimate and implement the amount and price of paying bank facilities as well as interest on deposits. Considering that the cost of money represents the correct management of the resources and costs of a bank, the investigation of ways to reduce the cost of money in state-owned banks can be an indicator of the efficiency of managers and the performance of a bank.The best way to calculate the optimal cost is to use data mining techniques. In this research, decision tree models, Bayesian rule, neural networks, and the RoughSet model have been analyzed using data mining methods through Weka, Rosetta, and Excel software.The accuracy criterion was using decision tree J48 (0.919), Bayesian theory (0.843), neural networks (0.274), and rough set model (0.0952), which was in the form of a law by genetic algorithm, Johnson, Holt was presented. These rules enable bank managers to adopt policies based on the discovered models to better understand their resources and costs and to balance finances in their branches to achieve better value for money.https://mseee.semnan.ac.ir/article_9018_739ae8d82d7281f96b10822d8bb0b8fa.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863120230501High-Efficiency Slot Array Antenna Fed by a Microstrip Line to ESIW Transition for X-band Applications4752880610.22075/mseee.2024.33391.1150ENAhmadParsaElectrical and Computer Engineering Faculty, Semnan University, Semnan, Iran.PejmanRezaeiElectrical and Computer Engineering Faculty, Semnan University, Semnan, Iran.AliAmne ElahiElectrical and Computer Engineering Faculty, Semnan University, Semnan, Iran.ZahraMousaviraziInstitut National de la Recherche Scientifique, University of Quebec, Montreal, QC, Canada.Journal Article20240227In this manuscript, a planar slot array antenna with an innovative method is designed at a 10 GHz centrecentre frequency. The designed antenna is manufactured on PCB. In this antenna, the input power enters the microstrip line, then this power enters the empty SIW (ESIW) structure via transition and then this structure fed the eight radiation slots on the antenna. The geometry of the ESIW structure is designed as a tapered substrate, which eliminates the interference effects of higher-order modes with the dominant mode, thus providing extreme antenna radiation power. The techniques used in feeding the radiation elements have acceptable effects on the impedance bandwidth and radiation efficiency. The designed antenna feeding bandwidth is 2 GHz, also the antenna fractional bandwidth is 7.5%. All simulations were performed using CST Studio Suite software. The antenna radiation gains and efficiency are 13.8 dB and about 92% at 10 GHz, respectively. The configured antenna dimension is 222.75 × 40 × 4.4 mm<sup>3</sup>.https://mseee.semnan.ac.ir/article_8806_9a509035cc518a95fb5c7f58a3e08875.pdfSemnan University PressJournal of Modeling and Simulation in Electrical and Electronics Engineering2821-07863120230501Scientometric Analysis of Green Vehicular Communications: A Comparative Study Based on Scopus and Web of Science5361905010.22075/mseee.2024.34260.1159ENPedramHajipourSatellite Communication Group, Faculty of Communications Technology, ICT Research Institute, Tehran, Iran.HosseinEftekhariScience and Technology Observation Inc, Tehran, Iran.0009-0003-9454-0461HassanYeganehFaculty of Communications Technology, ICT Research Institute, Tehran, Iran.HoumanZarrabiFaculty of Communications Technology, ICT Research Institute, Tehran, Iran.Journal Article20240527In this article, the status of published scientific literature in the field of "trends in green vehicular communications" is investigated using scientometric analysis. For this purpose, two reliable scientific citation databases, Scopus and Web of Science, were used for analysis, comparison, and evaluation from 2007 to 2023. The results indicate that there are a total of 3,150 published research works, with 2414 and 736 documents belonging to the Scopus and Web of Science databases, respectively. Tools such as Bibexcel and VOSviewer are employed for scientific evaluation and analysis. According to the statistical results obtained from the Scopus and WoS databases, China, the United States and India are the most active countries in this field of study. Additionally, topics such as vehicular communications, energy efficiency, energy utilization, VANETs, and connected cars are among the most commonly researched subjects. The Beijing University of Posts and Telecommunications and Chongqing University are recognized as leading institutions in this field with the highest number of publications. An exponential increase in scientific output in the Scopus database has been observed since 2014, whereas an upward trend began in the WoS in 2007. In both the Scopus and Web of Science databases, the field of engineering plays a major role in this research area, accounting for 33% and 30% of scientific production, respectively. IEEE Access and IEEE Transactions on Intelligent Transportation Systems are the leading journals with the highest number of related publications. SUMO and NS-2 are the most commonly used simulators in this field.https://mseee.semnan.ac.ir/article_9050_5a24069824ec1c9823031524e7ff5415.pdf