Pub Date : 2023-09-30DOI: 10.1080/02533839.2023.2262759
Tao Zhang, Tianyu Zhao, Yi Qin, Sucheng Liu
ABSTRACTAI has been widely used in intelligent transportation systems, autonomous driving and automated vehicles in particular. Intelligent vehicles in the future will be a combination of Internet of things and AI, and AI is the key for intelligent vehicles. The maturer the intelligent vehicles are, the more advanced the AI techniques will be applied in intelligent vehicles. In this paper, we perform a survey on the progress of AI applications in automated vehicles, including perception, autonomous driving, and test, and then discuss challenges of intelligent vehicles and recent advances in AI and prospective applications in the future transportation ecosystem, intelligent vehicles in particular.CO EDITOR-IN-CHIEF: Yuan, Shyan-MingASSOCIATE EDITOR: Yuan, Shyan-MingKEYWORDS: Intelligent vehiclesartificial intelligenceautomated vehiclesobject detection Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by Anhui Provincial Key Laboratory of Power Electronics and Motion Control, Guangxi Key Laboratory of Trusted Software (kx202016), Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province (obdma202001), and Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis (GXIC20-03).
{"title":"Artificial intelligence in intelligent vehicles: recent advances and future directions","authors":"Tao Zhang, Tianyu Zhao, Yi Qin, Sucheng Liu","doi":"10.1080/02533839.2023.2262759","DOIUrl":"https://doi.org/10.1080/02533839.2023.2262759","url":null,"abstract":"ABSTRACTAI has been widely used in intelligent transportation systems, autonomous driving and automated vehicles in particular. Intelligent vehicles in the future will be a combination of Internet of things and AI, and AI is the key for intelligent vehicles. The maturer the intelligent vehicles are, the more advanced the AI techniques will be applied in intelligent vehicles. In this paper, we perform a survey on the progress of AI applications in automated vehicles, including perception, autonomous driving, and test, and then discuss challenges of intelligent vehicles and recent advances in AI and prospective applications in the future transportation ecosystem, intelligent vehicles in particular.CO EDITOR-IN-CHIEF: Yuan, Shyan-MingASSOCIATE EDITOR: Yuan, Shyan-MingKEYWORDS: Intelligent vehiclesartificial intelligenceautomated vehiclesobject detection Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by Anhui Provincial Key Laboratory of Power Electronics and Motion Control, Guangxi Key Laboratory of Trusted Software (kx202016), Key Laboratory of Oceanographic Big Data Mining & Application of Zhejiang Province (obdma202001), and Guangxi Key Laboratory of Hybrid Computation and IC Design Analysis (GXIC20-03).","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ABSTRACTAccording to a survey by the Ministry of the Interior (MOI) in Taiwan, around half of the 8.93 million buildings in the country, which are over 30 years old, have inadequate seismic capacity due to outdated design standards or aging materials. To evaluate seismic capacity, a preliminary seismic evaluation (PSE) system that involves site investigation and shop drawing review (if available) by professional engineers is typically used. However, given the significant financial and manpower resources required, performing PSE on all buildings in Taiwan is not practical. In order to overcome the challenge of evaluating the seismic capacity of buildings in a cost-effective and efficient manner, this study developed an enhanced PSE system called QSEBS, based on deep learning technology. By leveraging government property tax databases, QSEBS can rapidly estimate the seismic capacity of buildings, with results consistent with those of the PSERCB system. The key advantage of QSEBS is its ability to eliminate the need for human labors in PSE, saving significant amounts of money and manpower, particularly for a large number of buildings. Thus, QSEBS can serve as a valuable tool to support the government’s urban disaster-prevention strategy and can be widely implemented.CO EDITOR-IN-CHIEF: Ou, Yu-ChenASSOCIATE EDITOR: Ou, Yu-ChenKEYWORDS: Back-propagation neural network (BPNN)preliminary seismic evaluation of reinforced concrete building (PSERCB)quick seismic estimation of building structures (QSEBS)Kruskal-Wallis H testdata cleaning Nomenclature Ac2=seismic-capacity indexA2500=seismic demand for a 2500-year return period earthquakeAc2/IA2500=seismic capacity-demand ratio for seismic vulnerability assessmentC=ratio of spectral acceleration divided by ground acceleration for a specific structural period in elastic normalized response spectrum of accelerationD=diameter of the rebars and stirrupsE=convenient representation of 2μ−1E_TACW=equivalent total area of column-wallE_W/CW=equivalent width per column-wallE_D/CW=equivalent depth per column-wallH=value of Kruskal-Wallis H testH0=null hypotheses for correlation evaluationI=importance factorR=response reduction factorSa=parameter of elastic design spectral acceleration responseTn=structural periodVu, e=ultimate elastic base shear demandVy=yield base shear demandVS30=average shear wave velocity for a soil depth of 30 mW=sum of weight lumped at the ground floor’s ceiling levelμ=ductility level△u=ultimate or code-specified displacement△y=yield displacementχ2=Chi-square valueDisclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis study was supported by the National Science and Technology Center for Disaster Reduction, Taiwan [Grant No. NCDR-S-111012].
{"title":"AI-based system for quick seismic estimation of building structures on urban disaster-prevention in Taiwan","authors":"Jin-Biau Wei, Yu-Chi Sung, Chung-Min Chiu, Chia-Hsuan Li, Sheng-Wei Kuo, Zhi-Yuan Chen, Xiao-Qin Liu, Siao-Syun Ke, Chih-Hao Hsu","doi":"10.1080/02533839.2023.2261987","DOIUrl":"https://doi.org/10.1080/02533839.2023.2261987","url":null,"abstract":"ABSTRACTAccording to a survey by the Ministry of the Interior (MOI) in Taiwan, around half of the 8.93 million buildings in the country, which are over 30 years old, have inadequate seismic capacity due to outdated design standards or aging materials. To evaluate seismic capacity, a preliminary seismic evaluation (PSE) system that involves site investigation and shop drawing review (if available) by professional engineers is typically used. However, given the significant financial and manpower resources required, performing PSE on all buildings in Taiwan is not practical. In order to overcome the challenge of evaluating the seismic capacity of buildings in a cost-effective and efficient manner, this study developed an enhanced PSE system called QSEBS, based on deep learning technology. By leveraging government property tax databases, QSEBS can rapidly estimate the seismic capacity of buildings, with results consistent with those of the PSERCB system. The key advantage of QSEBS is its ability to eliminate the need for human labors in PSE, saving significant amounts of money and manpower, particularly for a large number of buildings. Thus, QSEBS can serve as a valuable tool to support the government’s urban disaster-prevention strategy and can be widely implemented.CO EDITOR-IN-CHIEF: Ou, Yu-ChenASSOCIATE EDITOR: Ou, Yu-ChenKEYWORDS: Back-propagation neural network (BPNN)preliminary seismic evaluation of reinforced concrete building (PSERCB)quick seismic estimation of building structures (QSEBS)Kruskal-Wallis H testdata cleaning Nomenclature Ac2=seismic-capacity indexA2500=seismic demand for a 2500-year return period earthquakeAc2/IA2500=seismic capacity-demand ratio for seismic vulnerability assessmentC=ratio of spectral acceleration divided by ground acceleration for a specific structural period in elastic normalized response spectrum of accelerationD=diameter of the rebars and stirrupsE=convenient representation of 2μ−1E_TACW=equivalent total area of column-wallE_W/CW=equivalent width per column-wallE_D/CW=equivalent depth per column-wallH=value of Kruskal-Wallis H testH0=null hypotheses for correlation evaluationI=importance factorR=response reduction factorSa=parameter of elastic design spectral acceleration responseTn=structural periodVu, e=ultimate elastic base shear demandVy=yield base shear demandVS30=average shear wave velocity for a soil depth of 30 mW=sum of weight lumped at the ground floor’s ceiling levelμ=ductility level△u=ultimate or code-specified displacement△y=yield displacementχ2=Chi-square valueDisclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis study was supported by the National Science and Technology Center for Disaster Reduction, Taiwan [Grant No. NCDR-S-111012].","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136279950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1080/02533839.2023.2238396
Atmanli A. Chan, H. C. Chang
{"title":"2022 successful reviewers","authors":"Atmanli A. Chan, H. C. Chang","doi":"10.1080/02533839.2023.2238396","DOIUrl":"https://doi.org/10.1080/02533839.2023.2238396","url":null,"abstract":"","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"25 1","pages":"i - i"},"PeriodicalIF":1.1,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74783245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-10DOI: 10.1080/02533839.2023.2238397
"List of Reviewers for 2022." Journal of the Chinese Institute of Engineers, 46(7), pp. ii–iii
“2022年的评审名单。”中国工程师学会学报,46(7),pp. ii-iii
{"title":"List of Reviewers for 2022","authors":"","doi":"10.1080/02533839.2023.2238397","DOIUrl":"https://doi.org/10.1080/02533839.2023.2238397","url":null,"abstract":"\"List of Reviewers for 2022.\" Journal of the Chinese Institute of Engineers, 46(7), pp. ii–iii","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135493719","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-07DOI: 10.1080/02533839.2023.2238771
Reshma R. Devale, Amit M. Katariya, Y. S. Mahajan
ABSTRACT Recovery of trifluoroacetic acid (TFA) by distillation is difficult due to the existence of a high boiling azeotrope. Esterification of TFA to ethyl trifluoroacetate was performed in this work in order to recover the acid from its dilute aqueous mixture. The reaction was carried out in a batch reactor. Parameter estimation was done to obtain a kinetic model by using the experimental data. Reactive distillation studies were performed to explore its feasibility and process intensification. Methodology to obtain almost pure ethyl trifluoroacetate from dilute aqueous reaction mixture was devised.
{"title":"Ethyl trifluoroacetate formation as a means to recover trifluoroacetic acid from dilute aqueous mixture: reaction, separation and purification","authors":"Reshma R. Devale, Amit M. Katariya, Y. S. Mahajan","doi":"10.1080/02533839.2023.2238771","DOIUrl":"https://doi.org/10.1080/02533839.2023.2238771","url":null,"abstract":"ABSTRACT Recovery of trifluoroacetic acid (TFA) by distillation is difficult due to the existence of a high boiling azeotrope. Esterification of TFA to ethyl trifluoroacetate was performed in this work in order to recover the acid from its dilute aqueous mixture. The reaction was carried out in a batch reactor. Parameter estimation was done to obtain a kinetic model by using the experimental data. Reactive distillation studies were performed to explore its feasibility and process intensification. Methodology to obtain almost pure ethyl trifluoroacetate from dilute aqueous reaction mixture was devised.","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"56 1","pages":"781 - 794"},"PeriodicalIF":1.1,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89223361","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-04DOI: 10.1080/02533839.2023.2238778
Aysu Kayalıoğlu
ABSTRACT Fertilizers are very sensitive to climatic conditions due to their hygroscopic nature. They tend to absorb moisture, weaken and accordingly lose their free-flowing property depending on the ambient conditions. In this study, the influence of storage conditions on a commercial grade calcium ammonium nitrate (CAN/26) fertilizer was investigated using methods that included simulation of storage and handling. The mechanical properties of CAN/26 fertilizer were observed by friability and crushing strength tests. Granule structure begins to weaken especially above a temperature of 40°C and a pressure of 0.33 kg/cm2. Sudden changes in ambient temperature enhance the caking propensity by 4.8%. Fertilizers above 65% relative humidity start to absorb moisture and degrade at very high temperatures. The phase transition of ammonium nitrate between crystalline forms plays an important role in the caking of CAN/26, as its tendency to agglomerate at about 32°C is greatly reduced. The results show that the granule degradation in CAN/26 fertilizer increases almost linearly with increasing temperature, humidity, and pressure but there is a sharp limit for each parameter for degradation to start. With these limits, it may be possible to carry out the protection and control of the good quality of fertilizers in the sector.
{"title":"Alternative solutions for the physicochemical evaluation and improvement of the caking properties of calcium ammonium nitrate fertilizer as a quality problem under atmospheric conditions","authors":"Aysu Kayalıoğlu","doi":"10.1080/02533839.2023.2238778","DOIUrl":"https://doi.org/10.1080/02533839.2023.2238778","url":null,"abstract":"ABSTRACT Fertilizers are very sensitive to climatic conditions due to their hygroscopic nature. They tend to absorb moisture, weaken and accordingly lose their free-flowing property depending on the ambient conditions. In this study, the influence of storage conditions on a commercial grade calcium ammonium nitrate (CAN/26) fertilizer was investigated using methods that included simulation of storage and handling. The mechanical properties of CAN/26 fertilizer were observed by friability and crushing strength tests. Granule structure begins to weaken especially above a temperature of 40°C and a pressure of 0.33 kg/cm2. Sudden changes in ambient temperature enhance the caking propensity by 4.8%. Fertilizers above 65% relative humidity start to absorb moisture and degrade at very high temperatures. The phase transition of ammonium nitrate between crystalline forms plays an important role in the caking of CAN/26, as its tendency to agglomerate at about 32°C is greatly reduced. The results show that the granule degradation in CAN/26 fertilizer increases almost linearly with increasing temperature, humidity, and pressure but there is a sharp limit for each parameter for degradation to start. With these limits, it may be possible to carry out the protection and control of the good quality of fertilizers in the sector.","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"24 1","pages":"795 - 804"},"PeriodicalIF":1.1,"publicationDate":"2023-08-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83836724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-02DOI: 10.1080/02533839.2023.2238768
Jeng-Tzong Chen, Chia-Ying Yang, Y. Chou, Chi-Ning Tsang
ABSTRACT In this paper, the animations for the 2D cycloid and the 3D spiral curves are done. The trajectories of instantaneous rotation center and the corresponding radius of curvature are given. We prove that the trajectory of the instantaneous center of rotation is also a cycloid. For a 3D spiral curve, the two radii and the two instantaneous centers of rotation for the spiral curve are also given. It is interesting to find that the two parameters in the Frenet equation have the same meaning of radius of curvature but in different planes. In a similar way of the 2D experience, we also confirm that the trajectory of the instantaneous center of rotation for a spiral curve is also a spiral curve. An example is also given to discuss the Puyuma express incident, a major accident in 2018. The curve of rail is interpolated and the radius of curvature is determined. Discussions on the radius of rail curve and the speed of train for the failure are done. Finally, the animation is implemented by using the MATLAB and the Mathematica software. Not only theoretical derivation for the curvature of a curve but also its real application to rail engineering is proposed.
{"title":"Animation of cycloid and spiral curves in companion with instantaneous center of rotation and radius of curvature","authors":"Jeng-Tzong Chen, Chia-Ying Yang, Y. Chou, Chi-Ning Tsang","doi":"10.1080/02533839.2023.2238768","DOIUrl":"https://doi.org/10.1080/02533839.2023.2238768","url":null,"abstract":"ABSTRACT In this paper, the animations for the 2D cycloid and the 3D spiral curves are done. The trajectories of instantaneous rotation center and the corresponding radius of curvature are given. We prove that the trajectory of the instantaneous center of rotation is also a cycloid. For a 3D spiral curve, the two radii and the two instantaneous centers of rotation for the spiral curve are also given. It is interesting to find that the two parameters in the Frenet equation have the same meaning of radius of curvature but in different planes. In a similar way of the 2D experience, we also confirm that the trajectory of the instantaneous center of rotation for a spiral curve is also a spiral curve. An example is also given to discuss the Puyuma express incident, a major accident in 2018. The curve of rail is interpolated and the radius of curvature is determined. Discussions on the radius of rail curve and the speed of train for the failure are done. Finally, the animation is implemented by using the MATLAB and the Mathematica software. Not only theoretical derivation for the curvature of a curve but also its real application to rail engineering is proposed.","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"104 1","pages":"693 - 702"},"PeriodicalIF":1.1,"publicationDate":"2023-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86199849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1080/02533839.2023.2238777
Priyadharshini Ramu, S. Gangatharan
ABSTRACT The increasing energy demand has significantly improved solar photovoltaic (SPV) systems as a distributed energy source. Real-time control of SPV performance is vital for accurate solar power (SP) prediction. The article proposes an ensemble Machine Learning Approach (MLA) called Random Forest Algorithm-Based Regression Model (RFARM) for hourly forecasting of SP. The approach selectively analyzes meteorological and solar irradiance data (SI) to enhance short-term solar panel prediction. It focuses on employing a correlation-based approach using an RFA with regression to achieve improved SP prediction accuracy. The study compares the PV power generated at Thiagarajar College of Engineering (TCE), Madurai, using four prediction techniques: Artificial Neural Networks (ANN), Random Forest (RF), K-Nearest Neighbours (KNN), and Support Vector Machine (SVM) along with a proposed RFARM for different meteorological weather conditions over a 24-hour time horizon. The proposed RFARM method achieves high prediction accuracy by selecting significant parameters, avoiding artificial filtering, and minimizing errors, particularly in predicting solar output during cloud shading. The RFARM model outperforms conventional methods in predicting the daily curve of solar power performance. It achieves an RMSE of 1.52, MAE of 14, and R-squared of 98%. Feature selection further improves accuracy, reducing RMSE by 12.5% and MAE by 17.2% respectively.
{"title":"An ensemble machine learning-based solar power prediction of meteorological variability conditions to improve accuracy in forecasting","authors":"Priyadharshini Ramu, S. Gangatharan","doi":"10.1080/02533839.2023.2238777","DOIUrl":"https://doi.org/10.1080/02533839.2023.2238777","url":null,"abstract":"ABSTRACT The increasing energy demand has significantly improved solar photovoltaic (SPV) systems as a distributed energy source. Real-time control of SPV performance is vital for accurate solar power (SP) prediction. The article proposes an ensemble Machine Learning Approach (MLA) called Random Forest Algorithm-Based Regression Model (RFARM) for hourly forecasting of SP. The approach selectively analyzes meteorological and solar irradiance data (SI) to enhance short-term solar panel prediction. It focuses on employing a correlation-based approach using an RFA with regression to achieve improved SP prediction accuracy. The study compares the PV power generated at Thiagarajar College of Engineering (TCE), Madurai, using four prediction techniques: Artificial Neural Networks (ANN), Random Forest (RF), K-Nearest Neighbours (KNN), and Support Vector Machine (SVM) along with a proposed RFARM for different meteorological weather conditions over a 24-hour time horizon. The proposed RFARM method achieves high prediction accuracy by selecting significant parameters, avoiding artificial filtering, and minimizing errors, particularly in predicting solar output during cloud shading. The RFARM model outperforms conventional methods in predicting the daily curve of solar power performance. It achieves an RMSE of 1.52, MAE of 14, and R-squared of 98%. Feature selection further improves accuracy, reducing RMSE by 12.5% and MAE by 17.2% respectively.","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"5 1","pages":"737 - 753"},"PeriodicalIF":1.1,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75628757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-01DOI: 10.1080/02533839.2023.2238759
Mehmet Akpamukcu, Abdullah Ateş, Ozan Akdağ
ABSTRACT Electromagnetic Field Optimization (EFO) and Harris Hawk Optimization (HHO) algorithms are combined with the optimization to optimization (OtoO) approach, and the EFO-HHO algorithm pair is presented in this study. EFO method was used as the essential algorithm and HHO method was used as the auxiliary algorithm according to the OtoO structure. The constant parameters (R_rate, Ps_rate, P_field, N_field) of the EFO algorithm that affect the optimization performance are optimized with the HHO optimization algorithm for the related optimization problem. The proposed method was tested on 10 different benchmark functions according to different dimensional (30, 50100). The EFO-HHO algorithm pair can produce better results than the existing literature, especially in cases of increased dimension with the proposed approach. In addition to these, the OPF problem was tested on the IEEE 30 test bus system for the engineering application of the proposed method. The results are compared with the existing literature results. As it can be seen from the results, it has been shown on the real engineering problem that the optimization performance can be increased with the OtoO approach without changing the basic philosophy of the EFO algorithm.
{"title":"Combination of electromagnetic field and harris hawks optimization algorithms with optimization to optimization structure and its application for optimum power flow","authors":"Mehmet Akpamukcu, Abdullah Ateş, Ozan Akdağ","doi":"10.1080/02533839.2023.2238759","DOIUrl":"https://doi.org/10.1080/02533839.2023.2238759","url":null,"abstract":"ABSTRACT Electromagnetic Field Optimization (EFO) and Harris Hawk Optimization (HHO) algorithms are combined with the optimization to optimization (OtoO) approach, and the EFO-HHO algorithm pair is presented in this study. EFO method was used as the essential algorithm and HHO method was used as the auxiliary algorithm according to the OtoO structure. The constant parameters (R_rate, Ps_rate, P_field, N_field) of the EFO algorithm that affect the optimization performance are optimized with the HHO optimization algorithm for the related optimization problem. The proposed method was tested on 10 different benchmark functions according to different dimensional (30, 50100). The EFO-HHO algorithm pair can produce better results than the existing literature, especially in cases of increased dimension with the proposed approach. In addition to these, the OPF problem was tested on the IEEE 30 test bus system for the engineering application of the proposed method. The results are compared with the existing literature results. As it can be seen from the results, it has been shown on the real engineering problem that the optimization performance can be increased with the OtoO approach without changing the basic philosophy of the EFO algorithm.","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"2667 1","pages":"754 - 765"},"PeriodicalIF":1.1,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88219314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-07-30DOI: 10.1080/02533839.2023.2238786
A. Arab
ABSTRACT This paper analyzes the trust problem in computer wireless sensor networks, WSNs. This study presents a reliable routing method in WSNs. Trust is an essential question although endeavors to prevent attacks on the networks have been made, the problem has not been satisfactorily resolved. The novelties of this paper are its improvement of the FETRP protocol in WSNs while considering recent advancements in related technologies like the Internet of Things (IoT) and its applicability in micro and macro-scale systems. Some malicious nodes deceive systems with incompatible behaviors, but this protocol detects them. This paper introduces fuzzy energy and a reliable routing protocol, FETRP, to solve problems. The protocol is upon fuzzy cluster development and has been designed to manage reliable routing of information transmission.
{"title":"The advanced wireless sensor networks’ routing protocol to detect malicious nodes and behavior","authors":"A. Arab","doi":"10.1080/02533839.2023.2238786","DOIUrl":"https://doi.org/10.1080/02533839.2023.2238786","url":null,"abstract":"ABSTRACT This paper analyzes the trust problem in computer wireless sensor networks, WSNs. This study presents a reliable routing method in WSNs. Trust is an essential question although endeavors to prevent attacks on the networks have been made, the problem has not been satisfactorily resolved. The novelties of this paper are its improvement of the FETRP protocol in WSNs while considering recent advancements in related technologies like the Internet of Things (IoT) and its applicability in micro and macro-scale systems. Some malicious nodes deceive systems with incompatible behaviors, but this protocol detects them. This paper introduces fuzzy energy and a reliable routing protocol, FETRP, to solve problems. The protocol is upon fuzzy cluster development and has been designed to manage reliable routing of information transmission.","PeriodicalId":17313,"journal":{"name":"Journal of the Chinese Institute of Engineers","volume":"28 1","pages":"805 - 812"},"PeriodicalIF":1.1,"publicationDate":"2023-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76217950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}