Bilijipub publisherAdvances in Engineering and Intelligence Systems2821-02630010420230101Investigation of Different Components of Steel Metal utilizing Artificial Intelligence16395610.22034/aeis.2022.359530.1040ENZainab L. HQadisiyah University, science college, biotechnology departmentFatima Abd NajiBabylon University, College of Science, physics and laser departmentJournal Article20220829Due to the reality that the investigation and plan of structures are based on tried-and-error strategies and the utilize of auxiliary examination program for this reason required a huge sum of time for computing in computers, so utilizing surmised methods that have the correct accuracy can be valuable. Within the display proposal, an analysis of steel Components utilizing Artificial intelligence is explored employing a multi-layer perceptron. The success rate of diverse preparing algorithm has been studied and compared to the detailed reply and pointed to imperative focuses within the preparing of the Artificial intelligence. Subsequently, in common, it can be said that the precision of the organize in getting particular values of steel components is more influenced by this issue, and each of the training algorithms (LM), (BR), and (SCG) have the capacity to precisely reach the reply.https://aeis.bilijipub.com/article_163956_c63ce1edd1fce87aef17db37eeddcec6.pdfBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02630010420230101Cost-based modeling for optimal energy management of smart buildings with renewable energy resources and electric vehicles using a scenario-based algorithm16395910.22034/aeis.2022.366739.1045ENHanlie ChengSchool of Energy Resource, China University of Geosciences (Beijing), Beijing 434000, ChinaJournal Article20221022The growth of electricity consumption and demand for higher quality of electricity have directed the electricity industry towards using new technologies. The rising trend of privatization, competitive nature of the electricity market and transformation of large investors into smaller ones have motivated electricity industry managers to pay more attention to increasing the generated power and grid equipment with maximum energy efficiency and minimum operation costs. Simultaneous use of different infrastructures for energy transfer and generation has led to the concept of energy hubs. Herein, a novel method is proposed to bridge the research gap in simultaneous optimization of solar system capacity and household energy hub operation. The proposed method is implemented on a household energy hub including controllable and uncontrollable loads, combined heat and power unit (CHP), grid-connected hybrid electric vehicles (EVs), heating loads and solar system. Studies were conducted in different conditions to compare the proposed method with the existing methods of optimal operation of household energy hubs and the simultaneous optimization of planning and operation problems with an emphasis on the solar system to highlight the benefits of the proposed method. The results indicate the efficiency of the proposed method in reducing operating costs and increasing the efficiency of the household energy hub while maintaining the user comfort level at the highest level.https://aeis.bilijipub.com/article_163959_078355d8d54d035f2f991063b9f97126.pdfBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02630010420230101Construction of Mechanical Earth Model (MEM) to determine the goemechanical properties of reservouirs: a case study16396010.22034/aeis.2022.367650.1048ENWilliam WardRMIT Univ, Melbourne, AustraliaAnnabelle GrahamSwinburne Univ Technol, Fac Sci Engn & Technol, Melbourne, Vic 3122, AustraliaEmma ScottRMIT Univ, Melbourne, AustraliaJournal Article20221029The mechanical earth model (MEM) has recently been considered in the oil and gas industry due to its importance in predicting the safe and stable range of drilling mud, better understanding the effective parameters in wellbore instability, safe drilling and reduce exorbitant costs on the industry and understanding the geomechanical properties of the reservoir. The MEM includes a logical set of information related to geology, stress field, mechanical properties of rock (elastic modulus and rock failure properties) and pore pressure which can be employed as a tool to quickly update information for use in drilling and reservoir management. In this paper, a MEM was constructed using well logging data for a well in one of the oil-fields as a case study and calibrated using laboratory results and drilling reports. According to the results obtained from the minimum horizontal stress values and the maximum horizontal stress range, as well as the occurrence of tensile failures in the wellbore, it was found that the stress regime prevailing in the study field is a strike-slip fault regime. The results also show that shear failure occurs in the direction of minimum horizontal stress and tensile failure occurs in the direction of maximum horizontal stress.https://aeis.bilijipub.com/article_163960_53468abede1cfad15ad693ac116112d4.pdfBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02630010420230101Recommended System Optimization in Social Networks based on Cooperative Filter with Deep MVR Algorithm16396210.22034/aeis.2022.368020.1049ENKim Hung PhoFaculty of Mathematics and Statistics, Ton Duc Thang University, Ho Chi Minh City, VietnamJournal Article20221101Today, social networks have become very popular due to their high usage in communicating with each other. But this popularity requires the development of a backend to communicate with each other. Hence, a topic called identifying users is created by making recommendations or propositional systems, and so on, link prediction. The most important issue is the new users' social networks so that they can offer suggestions. In this research, we tried to provide a system of recommendations for introducing new users to previous users and vice versa based on the principles of machine learning. The proposed method is that the data is entered into the program and then the keywords are extracted from them. Then a sampling between the data is performed based on the Pearson and Cronbach method. In the process of extraction operations along with diminishing dimensions, selection and finally extraction of the best features is done using the cooperative filter which is named here based on deep learning- Modified Vector Rotational (MVR) algorithm and its operators. In the following, due to the lack of probabilistic and statistical training in Deep and Reinforcement Learning with a random structure that is used to select users and also to offer users concerning the tastes of the extracted, there is an optimization algorithm for MVR to consider the best features with training. In the following, a series of evaluation criteria have been used to ensure the proposed approach, indicating the appropriate results of the proposed method.https://aeis.bilijipub.com/article_163962_30e226e3e266471fe1f055b840bcc262.pdfBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02630010420230101Estimating the Pile Settlement Using a Machine Learning Technique Optimized by Henry's Gas Solubility Optimization and Particle Swarm Optimization16396410.22034/aeis.2022.368689.1051ENSaravana KumarDepartment of Mechanical Engineering, Mount Zion College of Engineering and Technology, Pudukottai, Tamilnadu 622507, IndiaSavarimuthu RobinsonDepartment of Electronics and Communication Engineering, Mount Zion College of Engineering and Technology, Pudukkottai, 622507, Tamil Nadu, IndiaJournal Article20221106Ensuring constructional projects are safe, like stacked structures, requires consideration to immunize structures over the period. Pile settlement (PS) is an important project problem and is receiving a lot of attention to prevent failure before construction starts. Several items for estimating pile motion can help understand the project's perspective during the loading phase. Most intelligent strategies for the mathematical calculation of pile movement are used in PS simulations. Therefore, in present article, a developed framework operating support vector regression (SVR) together with Henry's Gas Solubility Optimization (HGSO) and Particle Swarm Optimization (PSO) was considered for accurate pile motion calculation. The usages of optimizers were to tune some internal settings of SVR. The Kuala Lumpur transportation network was selected to study the movement of piles based on the land rock characteristics using the developed SVR-HGSO and SVR-PSO structures. Five metrics were used to evaluate the performance of each model. The main objective of this research is to evaluate the artificial inteligent approach in form of two developed models in simulating the pile settlement rates using hybrid optimized frameworks. The R2 of modeling both were obtained similarly at 0.99 level. While the RMSE of SVR-PSO appeared more than two-fold of SVR-HGSO, 0.46 and 0.29 mm, respectively. Also, test phase results showed the better performance of SVR-HGSO with an MAE index of 0.278, which is 57.10% lower than the other one. The OBJ proved accurate modeling by SVR-HGSO calculated at 0.283mm level.https://aeis.bilijipub.com/article_163964_5d98ad10633ab3d105bf93829427ca61.pdfBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02630010420230101Scholarships Determination to Talented Students Based on Academic Characteristics with Deep Learning Approach and Particle Swarm Optimization Algorithm16396510.22034/aeis.2022.369500.1054ENDorota MozyrskaFaculty of Computer Science, Bialystok University of Technology,Wiejska 45A, 15-531, Bialystok, PolandEwa PawluszewiczFaculty of Mechanical Engineering, Bialystok University of Technology, Wiejska 45C, 15-531, Bialystok, PolandJournal Article20221112Knowledge is the most basic and important principle for students. Students can be classified based on knowledge. This classification is based on students' abilities and activities. Since MsC students need to receive scholarships to other countries to gain more knowledge, it is essential to provide a decision management and knowledge management system. Therefore, there is a need for a data set of students' information in order to perform a data mining process in order to find those elite students based on their activities and abilities of students and recommend them scholarships. Therefore, the present research tries to present such a system which is based on Natural Language Processing (NLP), feature extraction operations with Particle Swarm Optimization (PSO) algorithm and finally offers suggestions with deep Convolutional Neural Network (CNN). The results show that the accuracy of the proposed approach is higher than previous methods.https://aeis.bilijipub.com/article_163965_d10782a360dfaa6bc717863c2e0572c5.pdfBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02630010420230101A Novel Design of MSM Photodetector and the Investigation of Two-Top Contacts Spacing Effects on Detection Speed and Transient Response16396710.22034/aeis.2022.370845.1056ENSavarimuthu RobinsonDepartment of Electronics and Communication Engineering, Mount Zion College of Engineering and Technology, Pudukkottai, 622507, Tamil Nadu, IndiaYunjian JiaCollege of Communication Engineering, Chongqing University, Chongqing, 400044, ChinaJournal Article20221119The photodetector is one of the main components of the optical communication systems that converts optical signal to electrical signal. Metal Semiconductor Metal photodetector is one type of photodetector with a high coefficient of quantum efficiency and high speed while having a simple structure. In this paper, a novel microstructure of the Metal Semiconductor Metal photodetector consisting of an absorbing layer of semiconductor and two metal electrodes which act as two back-to-back Schottky diodes is designed and simulated. Incident light is absorbed by the active area between the two top electrodes and generates electron-hole pairs which are collected by electrodes and then an electric current is generated. Therefore, by determining the transient response of the detector for the various distance between the electrodes, we can find out the effect of the distance on the detection speed and detector response. In the best case, the response rate is 57 ps and the maximum instantaneous current is 3.27 nA. The shorter the distance between the two upper detector electrodes, called the empty area, the faster the detection speed increases, and the total light current decreases due to the reduction of the light flux descending on the surface.https://aeis.bilijipub.com/article_163967_d981dc6a72ebdf48b4672e191938b01f.pdfBilijipub publisherAdvances in Engineering and Intelligence Systems2821-02630010420230101Strategic Review: The CZTS Thin-Film Using Tandem and Multi-junction Solar Cell16396810.22034/aeis.2022.374374.1058ENSaif Adnan MuhamadIraqi Ministry of Education
Qadisiyah, Dewanyah, 58001, IraqMethaq Hadi LaftaMinistry of Education, Iraqdisabled, Baghdad, IraqJournal Article20221126In this study, a strategic review of fabrication technology and the CZTS (Cu2ZnSnS4) thin film solar cell using tandem and Multijunction structures is discussed. This review is tried to cover all the contents with a simple expression and at the same time so that the reader with any scientific level of this research field can have a good understanding of the research field and the importance of solar cells. Currently, two technologies are dominant in making solar cells (first and second generation) and new technology is in the research phase (third generation). The first-generation technology is based on silicon wafers with a thickness of 300μm - 400μm. The second generation of technology or thin-film technology, based on the semiconductor coating layer on glass, metal, or polymer layers, is 1μm - 5μm thick. Third-generation solar cells are also in the research phase, which includes nanocrystalline solar cells (based on liquid crystals), polymer solar cells, organic solar cells, perovskite solar cells (lead-mineral-organic hybrids or materials based on tin halides), Color Sensitive Solar Cells, Photo Electro Chemical Solar Cells, Multijunction Cells, Quantum Well Solar Cells, and Quantum Point Solar Cells. Although research into production technologies, especially third-generation technology, has evolved rapidly, there is still no review of the structures and results of all-generation technology. Due to the content of CZTS thin cells, the density of defects is an important role in the number of photovoltaic properties of the solar cell, many of these defects reduce the efficiency of the cell, and suggestions for increasing the efficiency of CZTSxSe1-x solar cells is introduced.https://aeis.bilijipub.com/article_163968_7c6583b6d3c5f10dc00e41c4c8f35045.pdf