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Urban electric Vehicle Charging Station Placement Optimization with Graylag Goose Optimization Voting Classifier

Computers, Materials & Continua 2024年第7期80卷 1163-1177页

作者： Amel Ali Alhussan Doaa sami.Khafaga el-Sayed M.el-kenawy Marwa M.Eid Abdelhameed Ibrahim Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and electronics Delta Higher Institute for Engineering and TechnologyMansoura35511Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

To reduce the negative effects that conventional modes of transportation have on the environment,researchers are working to increase the use of electric *** demand for environmentally friendly transportation may be hampered by obstacles such as a restricted range and extended rates of *** establishment of urban charging infrastructure that includes both fast and ultra-fast terminals is essential to address this ***,the powering of these terminals presents challenges because of the high energy requirements,whichmay influence the quality of *** the maximum hourly capacity of each station based on its geographic location is necessary to arrive at an accurate estimation of the resources required for charging *** is vital to do an analysis of specific regional traffic patterns,such as road networks,route details,junction density,and economic zones,rather than making arbitrary conclusions about traffic *** vehicle traffic is simulated using this data and other variables,it is possible to detect limits in the design of the current traffic engineering ***,the binary graylag goose optimization(bGGO)algorithm is utilized for the purpose of feature ***,the graylag goose optimization(GGO)algorithm is utilized as a voting classifier as a decision algorithm to allocate demand to charging stations while taking into consideration the cost variable of traffic *** on the results of the analysis of variance(ANOVA),a comprehensive summary of the components that contribute to the observed variability in the dataset is *** results of the Wilcoxon Signed Rank Test compare the actual median accuracy values of several different algorithms,such as the voting GGO algorithm,the voting grey wolf optimization algorithm(GWO),the voting whale optimization algorithm(WOA),the voting particle swarm optimization(PSO),the voting firefly algorithm(FA),and the voting genetic algori

关键词： electric vehicle graylag goose optimization metaheuristics optimization machine learning

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Thermoelastic rotating contact of an FGM coating with temperature-dependent and arbitrary varying properties

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Science China(Technological Sciences) 2023年第4期66卷 1038-1049页

作者： ZHOU JiaLin SHEN Fei LIU Jing el-BORGI sami.KE LiaoLiang Department of Mechanics School of Mechanical EngineeringTianjin UniversityTianjin 300350China College of Engineering Huazhong Agricultural UniversityWuhan 430070Chin Mechanical Engineering Program Engineering BuildingTexas A&M University at QatarP.O.Box 23874Qatar

This paper investigates the frictional thermoelastic contact of a rigid spherical punch and functionally graded material(FGM)coated half-space with arbitrarily varying material *** material parameters include the elastic modulus,Poisson’s ratio,heat conduction parameter,and thermal expansion *** material parameters of the FGM coating and half-space are assumed to be temperature *** spherical punch is rotated in the FGM-coated half-space at a constant angular *** generated frictional heat is related to the friction coefficient,contact radius,angular velocity,and contact pressure.A theoretical formula for the thermoelastic rotating contact problem is established and solved using the finite element *** main objective of this paper is to investigate the effects of temperature dependence,gradient index,friction coefficient,angular velocity,and gradient form on the surface temperature and stresses.

关键词： rotating punch frictional heat functionally graded materials temperature dependence arbitrary properties

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Papanicolaou smear interpretation with progestin-only hormonal birth control methods

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Journal of Reproduction and Contraception 2016年第1期27卷 25-40页

作者： Ziad sami.ABOUZEID Ahmed Samy el-AGWANY Department of Obstetrics and Gynecology Faculty of Medicine Alexandria University

Objective To define the relationship between the use of progestogen-only contracep- tion and the occurrence of abnormal cervical cytology and cervical intraepithelial lesion. Methods The present study was designed as a case-control study including 200 progestogen-only contraceptive （POC） users recruited as cases （group A） and 50 women who were non-hormonal contraceptive users as a control group （group B）. Positive Papanicolau （Pap） smear was reported in cervical cell abnormalities from atypical squamous cell of undetermined significance （ASCUS） to invasive cancer. Pap smear was evaluated according to the Bethesda system classification 2001. Cases with posi- tive Pap smears were subjected to visual inspection of the cervix with 5.0% acetic acid （VIA test） and punch biopsy. Results Statistical analysis of Pap smear results in this study showed epithelial cell abnormalities in 44 cases （22.0%） in group A and 9 cases （18.0%） in group B showing no statistically significant difference （P〉O. 05）. ASCUS abnormality was reported in 31 cases （15.5%） of group A and 6 cases of group B （12.0%）. Low-grade squamous intraepithelial lesion （LSIL） was found in 11 cases （5.5%） and 3 cases （6.0%） of group A and group B, respectively. High-grade squamous intraepithelial lesion （HSIL） was found in 2 cases （1.0%） of group A and none of group B. The incidence of abnormal Pap smears in group A did not greatly vary between different methods of POCs. Among Depo medroxyprogesterone acetate （DMPA） users, ASCUS was found in 17 cases （16.8%）, LSIL was found in 11 cases （10.8%） and HSIL was found in 2 cases （1.9%）. While in progesterone-only pills （POPs） users and Implanon~ users, ASCUS was found in 10 cases （12.8%） and 4 cases （20.0%） respectively with no higher epithelial abnormalities found. Levonorgestrel intrauterine device （LNG-IUD） was used by 1 case in group A and was not associated with Pap smear abnormality. Cases with ASCUS abnormality were followed up by repeated Pap smear after 3 mont

关键词： progesterone cancer cervix Papanicolau (Pap) smear

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Novel Optimized Feature Selection Using Metaheuristics Applied to Physical Benchmark Datasets

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Computers, Materials & Continua 2023年第2期74卷 4027-4041页

作者： Doaa sami.Khafaga el-Sayed M.el-kenawy Fadwa Alrowais Sunil Kumar Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt School of Computer Science University of Petroleum and Energy StudiesDehradun248001India Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

In data mining and machine learning,feature selection is a critical part of the process of selecting the optimal subset of features based on the target *** are 2n potential feature subsets for every n features in a dataset,making it difficult to pick the best set of features using standard ***,in this research,a new metaheuristics-based feature selection technique based on an adaptive squirrel search optimization algorithm(ASSOA)has been *** using metaheuristics to pick features,it is common for the selection of features to vary across runs,which can lead to *** of this,we used the adaptive squirrel search to balance exploration and exploitation duties more evenly in the optimization *** the selection of the best subset of features,we recommend using the binary ASSOA search strategy we developed *** to the suggested approach,the number of features picked is reduced while maximizing classification accuracy.A ten-feature dataset from the University of California,Irvine(UCI)repository was used to test the proposed method’s performance *** other state-of-the-art approaches,including binary grey wolf optimization(bGWO),binary hybrid grey wolf and particle swarm optimization(bGWO-PSO),bPSO,binary stochastic fractal search(bSFS),binary whale optimization algorithm(bWOA),binary modified grey wolf optimization(bMGWO),binary multiverse optimization(bMVO),binary bowerbird optimization(bSBO),binary hybrid GWO and genetic algorithm 4028 CMC,2023,vol.74,no.2(bGWO-GA),binary firefly algorithm(bFA),and *** results confirm the superiority and effectiveness of the proposed algorithm for solving the problem of feature selection.

关键词： Metaheuristics adaptive squirrel search algorithm optimization methods binary optimizer

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Dipper Throated Optimization for Detecting Black-Hole Attacks inMANETs

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Computers, Materials & Continua 2023年第1期74卷 1905-1921页

作者： Reem Alkanhel el-Sayed M.el-kenawy Abdelaziz A.Abdelhamid Abdelhameed Ibrahim Mostafa Abotaleb Doaa sami.Khafaga Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of System Programming South Ural State UniversityChelyabinsk454080Russia Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia

In terms of security and privacy,mobile ad-hoc network(MANET)continues to be in demand for additional debate and *** more MANET applications become data-oriented,implementing a secure and reliable data transfer protocol becomes a major concern in the ***,MANET’s lack of infrastructure,unpredictable topology,and restricted resources,as well as the lack of a previously permitted trust relationship among connected nodes,contribute to the attack detection burden.A novel detection approach is presented in this paper to classify passive and active black-hole *** proposed approach is based on the dipper throated optimization(DTO)algorithm,which presents a plausible path out of multiple paths for statistics transmission to boost MANETs’quality of service.A group of selected packet features will then be weighed by the DTO-based multi-layer perceptron(DTO-MLP),and these features are collected from nodes using the Low Energy Adaptive Clustering Hierarchical(LEACH)clustering *** is a powerful classifier and the DTO weight optimization method has a significant impact on improving the classification process by strengthening the weights of key features while suppressing the weights ofminor *** hybridmethod is primarily designed to combat active black-hole *** the LEACH clustering phase,however,can also detect passive black-hole *** effect of mobility variation on detection error and routing overhead is explored and evaluated using the suggested *** diverse mobility situations,the results demonstrate up to 97%detection accuracy and faster execution ***,the suggested approach uses an adjustable threshold value to make a correct conclusion regarding whether a node is malicious or benign.

关键词： Black-hole attack mobile ad-hoc network optimization dipper throated optimization

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Optimized Weighted Ensemble Using Dipper Throated Optimization Algorithm in Metamaterial Antenna

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Computers, Materials & Continua 2022年第12期73卷 5771-5788页

作者： Doaa sami.Khafaga el-Sayed M.el-kenawy Faten Khalid karim Sameer Alshetewi Abdelhameed Ibrahim Abdelaziz AAbdelhamid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt General Information Technology Department Ministry of DefenseThe Executive AffairsExcellence Services DirectorateRiyadh11564Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia

Metamaterial Antennas are a type of antenna that uses metamaterial to enhance *** bandwidth restriction associated with small antennas can be solved using metamaterial *** learning is gaining popularity as a way to improve solutions in a range of *** learning approaches are currently a big part of current research,and they’re likely to be huge in the *** model utilized determines the accuracy of the prediction in large *** goal of this paper is to develop an optimized ensemble model for forecasting the metamaterial antenna’s bandwidth and *** basic models employed in the developed ensemble are Support Vector Regression(SVR),K-NearestRegression(KNR),Multi-Layer Perceptron(MLP),Decision Trees(DT),and Random Forest(RF).The percentages of contribution of these models in the ensemble model are weighted and optimized using the dipper throated optimization(DTO)*** choose the best features from the dataset,the binary(bDTO)algorithm is *** proposed ensemble model is compared to the base models and results are recorded and analyzed *** addition,two other ensembles are incorporated in the conducted experiments for *** ensembles are average ensemble and K-nearest neighbors(KNN)-based *** comparison is performed in terms of eleven evaluation *** evaluation results confirmed the superiority of the proposed model when compared with the basic models and the other ensemble models.

关键词： Metamaterial antenna dipper throated optimization feature selection parameters prediction

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用于隧道位移监测的菱形布设新方法

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爆破 2024年第1期41卷 178-185,195页

作者：李文彪石义虎刘伟浩高云龙张聪瑞豆海涛 sami.kakar 张忠伦中铁第四勘察设计院集团有限公司武汉430063 武汉理工大学资源与环境工程学院武汉430070 武汉理工大学矿物资源加工与环境湖北省重点实验室武汉430070 中建材科创新技术研究院(山东)有限公司枣庄277100

提出了一种基于弱光栅传感器特性的监测方法,用于长期监测运营期盾构地铁隧道中存在的不均匀沉降和管片水平错动位移。将缆状弱光栅传感器经过预拉伸后,呈菱形固定在盾构隧道的壁面,通过监测弱光栅传感器的形变量,可以判别隧道结构变形... 详细信息

提出了一种基于弱光栅传感器特性的监测方法,用于长期监测运营期盾构地铁隧道中存在的不均匀沉降和管片水平错动位移。将缆状弱光栅传感器经过预拉伸后,呈菱形固定在盾构隧道的壁面,通过监测弱光栅传感器的形变量,可以判别隧道结构变形的不同模式并计算出隧道变形量,满足工程所需的实时性和精度要求。依据相似比原则,设计制造了1∶5的隧道位移模型,模拟隧道管片的局部伸缩、沉降、水平位移,将光栅传感器固定在壁面上,开展了弱光栅监测灵敏度试验、不同菱形布设角度下弱光栅监测结果对比试验和竖直沉降与水平位移试验,对比监测结果与实际位移量。研究结果表明:(1)在相同沉降情况下,弱光栅菱形布设时的光栅应变量要大于直线型布设时光栅的应变量,菱形布设方法对沉降量的变化敏感度优于传统直线型布设;(2)10°~20°为弱光栅菱形布设较优的倾斜角度区间,监测结果误差较低;(3)以光缆布设倾角为15°的试验数据为基础,建立了弱光栅波长变化与管片位移的反演方程。

关键词：盾构管片位移变形弱光栅传感器菱形布设地铁运营期

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Optimization Ensemble Weights Model for Wind Forecasting System

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Computers, Materials & Continua 2022年第11期73卷 2619-2635页

作者： Amel Ali Alhussan el-Sayed M.el-kenawy Hussah Nasser AlEisa M.el-SAID Sayed A.Ward Doaa sami.Khafaga Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Communications and electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt electrical Engineering Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Delta Higher Institute of Engineering and Technology(DHIET) Mansoura35111Egypt Department of electrical Engineering Faculty of Engineering at ShoubraBenha UniversityCairo11629Egypt Faculty of Engineering Delta University for Science and TechnologyGamasaMansoura11152Egypt

Effective technology for wind direction forecasting can be realized using the recent advances in machine ***,the stability and safety of power systems are expected to be significantly ***,the unstable and unpredictable qualities of the wind predict the wind direction a challenging *** paper proposes a practical forecasting approach based on the weighted ensemble of machine learning *** weighted ensemble is optimized using a whale optimization algorithm guided by particle swarm optimization(PSO-Guided WOA).The proposed optimized weighted ensemble predicts the wind direction given a set of input *** conducted experiments employed the wind power forecasting dataset,freely available on kaggle and developed to predict the regular power generation at seven wind farms over forty-eight *** recorded results of the conducted experiments emphasize the effectiveness of the proposed ensemble in achieving accurate predictions of the wind *** addition,a comparison is established between the proposed optimized ensemble and other competing optimized ensembles to prove its ***,statistical analysis using one-way analysis of variance(ANOVA)and Wilcoxon’s rank-sum are provided based on the recorded results to confirm the excellent accuracy achieved by the proposed optimized weighted ensemble.

关键词： Guided Whale Optimization Algorithm(Guided WOA) forecasting machine learning weighted ensemble model wind direction

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Forecasting Energy Consumption Using a Novel Hybrid Dipper Throated Optimization and Stochastic Fractal Search Algorithm

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Intelligent Automation & Soft Computing 2023年第8期37卷 2117-2132页

作者： Doaa sami.Khafaga el-Sayed M.el-kenawy Amel Ali Alhussan Marwa M.Eid Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Communications and electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansouraEgypt

The accurate prediction of energy consumption has effective role in decision making and risk management for individuals and ***,the accurate prediction can be realized using the recent advances in machine learning and predictive *** research proposes a novel approach for energy consumption forecasting based on a new optimization algorithm and a new forecasting model consisting of a set of long short-term memory(LSTM)*** proposed optimization algorithm is used to optimize the parameters of the LSTM-based model to boost its forecasting *** optimization algorithm is based on the recently emerged dipper-throated optimization(DTO)and stochastic fractal search(SFS)algo-rithm and is referred to as dynamic *** prove the effectiveness and superiority of the proposed approach,five standard benchmark algorithms,namely,stochastic fractal search(SFS),dipper throated optimization(DTO),whale optimization algorithm(WOA),particle swarm optimization(PSO),and grey wolf optimization(GWO),are used to optimize the parameters of the LSTM-based model,and the results are compared with that of the proposed *** results show that the proposed DDTOSFS+LSTM can accurately forecast the energy consumption with root mean square error RMSE of 0.00013,which is the best among the recorded results of the other *** addition,statistical experiments are conducted to prove the statistical difference of the proposed *** results of these tests confirmed the expected outcomes.

关键词： Stochastic fractal search dipper throated optimization energy consumption long short-term memory prediction models

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Effect of Recycling Cycles on the Mechanical and Damping Properties of Flax Fibre Reinforced elium Composite:Experimental and Numerical Studies

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Journal of Renewable Materials 2021年第4期9卷 695-721页

作者： sami.Allagui Abderrahim el Mahi Jean-Luc Rebiere Moez Beyaoui Anas Bouguecha Mohamed Haddar Acoustics Laboratory of Le Mans University Le Mans UniversityLe Mans72085France Laboratory of Mechanics Modelling and Production National School of Engineering of SfaxSfax3038Tunisia

This manuscript deals with the effects of recycling on the static and dynamic properties of flax fibers reinforced thermoplastic *** corresponding thermoplastic used in this work is elium ***’s the first liquid thermoplastic resin that allows the production of recycled composite parts with promising mechanical *** appeared on the resin market in *** until now,no studies were available concerning how it can be recycled and *** this study,a thermocompression recycling process was investigated and applied to elium *** fiber-reinforced elium composites were produced using a resin infusion process and were subjected to different thermomechanical recycling *** each material,five recycling operations were carried out on the raw material.A total of 10 different materials were investigated and tested by means of tensile and free vibration tests to evaluate the effect of recycling on their *** addition,a finite element model of the dynamic problem was developed to evaluate the loss factor and natural frequencies regarding different *** results obtained show that the failure tensile properties of elium resin as well as flax fiber reinforced composites decrease during recycling ***,recycling induces a rise in the elastic ***,improvement in the dynamic stiffness was observed with recycling *** repeated recycling appeared to have negligible effects on the loss factor of the recycled *** results obtained from the experiment and the numerical analyses were in close agreement.

关键词： Recycling thermoplastic bio-composites thermocompression process tensile properties vibration loss factor

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