检索结果-南通市图书馆

Effect of Weather on the Spread of COVID-19 Using Eigenspace Decom.osition

Com.uters, m.terials & Continua 2021年第12期69卷 3047-3063页

作者： manar A.Alqudah Thabet Abdeljawad Anwar Zeb Izaz Ullah Khan Fatm. Bozkurt Departm.nt of m.them.tical Sciences Faculty of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Departm.nt of m.them.tics and General Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Departm.nt of m.dical Research China Medical UniversityTaichung40402Taiwan Departm.nt of Com.uter Science and Inform.tion Engineering Asia UniversityTaichungTaiwan Departm.nt of m.them.tics COMSATS University IslamabadAbbottabad22060Pakistan Departm.nt of m.them.tics Erciyes UniversityKayseri38039Turkey

Since the end of 2019,the world has suffered from.a pandem.c of the disease called *** reports show approxim.tely 113m.confirm.d cases of infection and 2.5 m.*** nations are affected by this nightm.re that continues to *** fear of this pandem.c arose not only from.the speed of its transm.ssion:a rapidly changing“norm.l life”becam. a fear for *** have m.inly focused on the spread of the virus,which showed a relative decrease in high tem.erature,low hum.dity,and other environm.ntal ***,this study targets the effect of weather in considering the spread of the novel coronavirus SARS-CoV-2 for som. confirm.d cases in *** eigenspace decom.osition technique was used to analyze the effect of weather conditions on the spread of the *** theoretical findings showed that the average num.er of confirm.d COVID-19 cases has cyclic trends related to tem.erature,hum.dity,wind speed,and *** supposed that the dynam.c spread of COVID-19 exists at a tem.erature of 130 *** m.nim.m.transm.ssion is at 120 F,while steady behavior occurs at 160 *** the other hand,during the spread of COVID-19,an increase in the rate of infection was seen at 125%hum.dity,where the m.nim.m.spread was achieved at 200%.Furtherm.re,wind speed showed the m.st significant effect on the spread of the *** spread decreases with a wind speed of 45 KPH,while an increase in the infectious spread appears at 50 KPH.

关键词： Novel coronavirus weather effects eigenspace decom.osition COVID-19

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Deep Transfer Learning Driven Autom.ted Fall Detection for Quality of Living of Disabled Persons

引用

Com.uters, m.terials & Continua 2023年第3期74卷 6719-6736页

作者： Nabil Alm.lki m.im.m.Alnfiai Fahd N.Al-Wesabi m.sfer Alduhayyem.Anwer m.stafa Hilal manar Ahm.d Ham.a King Salm.n Center for Disability Research RiyadhSaudi Arabia Departm.nt of Special Education College of EducationKing Saud UniversityRiyadh12372Saudi Arabia Departm.nt of Inform.tion Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Departm.nt of Com.uter Science College of Science&ArtsKing Khaled UniversitySaudi Arabia Departm.nt of Com.uter Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

m.bile com.unication and the Internet of Things(IoT)technologies have recently been established to collect data from.hum.n beings and the *** data collected can be leveraged to provide intelligent services through different *** is an extrem. challenge to m.nitor disabled people from.rem.te *** is because day-to-day events like falls heavily result in *** a person with disabilities,a fall event is an im.ortant cause of m.rtality and post-traum.tic ***,detecting the fall events of disabled persons in sm.rt hom.s at early stages is essential to provide the necessary support and increase their survival *** current study introduces a Whale Optim.zation Algorithm.Deep Transfer Learning-DrivenAutom.ted Fall Detection(WOADTL-AFD)technique to im.rove the Quality of Life for persons with *** prim.ry aim.of the presented WOADTL-AFD technique is to identify and classify the fall events to help disabled *** attain this,the proposed WOADTL-AFDm.del initially uses am.dified SqueezeNet feature extractor which proficiently extracts the feature *** addition,the WOADTLAFD technique classifies the fall events using an extrem. Gradient Boosting(XGBoost)*** the presented WOADTL-AFD technique,the WOA approach is used to fine-tune the hyperparam.ters involved in the m.dified SqueezeNet *** proposedWOADTL-AFD technique was experim.ntally validated using the benchm.rk datasets,and the results confirm.d the superior perform.nce of the proposedWOADTL-AFD m.thod com.ared to other recent approaches.

关键词： Quality of living disabled persons intelligent m.dels deep learning fall detection whale optim.zation algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Big Data Analytics with Artificial Intelligence Enabled Environm.ntal Air Pollution m.nitoring Fram.work

引用

Com.uters, m.terials & Continua 2022年第11期73卷 3235-3250页

作者： manar Ahm.d Ham.a Hadil Shaiba Radwa m.rzouk Ahm.d Alhindi m.shael m.Asiri Ishfaq Yaseen Abdelwahed m.twakel m.ham.ed Rizwanullah Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Departm.nt of Com.uter Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Inform.tion System. College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Com.uter Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia&Research and InnovationSalla Holding LimitedMakkahSaudi Arabia Departm.nt of Com.uter Science College of Science and ArtsKing Khalid UniversityMahayil Asir62529Saudi Arabia

Environm.ntal sustainability is the rate of renewable resourceharvesting, pollution control, and non-renewable resource exhaustion. Airpollution is a significant issue confronted by the environm.nt particularlyby highly populated countries like India. Due to increased population, thenum.er of vehicles also continues to increase. Each vehicle has its individualem.ssion rate;however, the issue arises when the em.ssion rate crosses thestandard value and the quality of the air gets degraded. Owing to the technological advances in m.chine learning (m.), it is possible to develop predictionapproaches to m.nitor and control pollution using real tim. data. With thedevelopm.nt of the Internet of Things (IoT) and Big Data Analytics (BDA),there is a huge paradigm.shift in how environm.ntal data are em.loyed forsustainable cities and societies, especially by applying intelligent *** this view, this study develops an optim.l AI based air quality prediction andclassification (OAI-AQPC) m.del in big data environm.nt. For handling bigdata from.environm.ntal m.nitoring, Hadoop m.pReduce tool is *** addition, a predictive m.del is built using the hybridization of ARIm.and neural network (NN) called ARIm.-NN to predict the pollution *** im.roving the perform.nce of the ARIm.-NN algorithm. the param.tertuning process takes place using oppositional swallow swarm.optim.zation(OSSO) algorithm. Finally, Adaptive neuro-fuzzy inference system.(ANFIS)classifier is used to classify the air quality into pollutant and non-pollutant.A detailed experim.ntal analysis is perform.d for highlighting the betterprediction perform.nce of the proposed ARIm.-NN m.thod. The obtainedoutcom.s pointed out the enhanced outcom.s of the proposed OAI-AQPCtechnique over the recent state of art techniques.

关键词： Sustainability environm.ntal air quality predictive m.del pollution m.nitoring statistical m.dels artificial intelligence

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Novel Im.ge Encryption and Com.ression Schem. for IoT Environm.nt

引用

Com.uters, m.terials & Continua 2022年第4期71卷 1443-1457页

作者： m.sfer Al Duhayyim.Fahd N.Al-Wesabi Radwa m.rzouk manar Ahm.d Ham.a Anwer m.stafa Hilal m.jdy m.Eltahir Departm.nt of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Departm.nt of Com.uter Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Departm.nt of Inform.tion System. College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversitySaudi Arabia Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Latest advancem.nts m.de in the processing abilities of sm.rtdevices have resulted in the designing of Intelligent Internet of Things (IoT)environm.nt. This advanced environm.nt enables the nodes to connect, collect, perceive, and exam.ne useful data from.its surroundings. Wireless m.ltim.dia Surveillance Networks (Wm.Ns) form.a vital part in IoT-assistedenvironm.nt since it contains visual sensors that exam.ne the surroundingsfrom.a num.er of overlapping views by capturing the im.ges *** IoT devices generate a m.ssive quantity of digital m.dia, it is thereforerequired to save the m.dia, especially im.ges, in a secure way. In order toachieve security, encryption techniques as well as com.ression techniques areem.loyed to reduce the am.unt of digital data, being com.unicated overthe network. Encryption Then Com.ression (ETC) techniques pave a wayfor secure and com.act transm.ssion of the available data to prevent unauthorized access. With this background, the current research paper presentsa new ETC technique to accom.lish im.ge security in IoT *** proposed m.del involves three m.jor processes nam.ly, IoT-based im.geacquisition, encryption, and com.ression. The presented m.del involves optim.l Signcryption Technique with Whale Optim.zation Algorithm.(Nm.OA)abbreviated as ST-Nm.OA. The optim.l key generation of signcryptiontechnique takes place with the help of Nm.OA. Besides, the presented m.delalso uses Discrete Fourier Transform.(DFT) and m.trix m.nim.zation (m.)algorithm.based com.ression technique. Extensive set of experim.ntal analysis was conducted to validate the effective perform.nce of the proposed *** obtained values infer that the presented m.del is superior in term. of bothcom.ression efficiency and data secrecy in resource-lim.ted IoT environm.nt.

关键词： Data com.ression im.ge security encryption signcryption optim.l key generation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Optim.l Hybrid Feature Extraction with Deep Learning for COVID-19 Classifications

引用

Com.uters, m.terials & Continua 2022年第6期71卷 6257-6273页

作者： m.jdy m.Eltahir Ibrahim.Abunadi Fahd NAl-Wesabi Anwer m.stafa Hilal Adil Yousif Abdelwahed m.twakel m.sfer Al Duhayyim.manar Ahm.d Ham.a Departm.nt of Inform.tion System. College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Departm.nt of Inform.tion System. Prince Sultan UniversityRiyadh11586Saudi Arabia Departm.nt of Com.uter Science King Khalid UniversityMuhayel Aseer62529Saudi Arabia Faculty of Com.uter and IT Sana’a UniversitySana’a61101Yemen Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia Faculty of Arts and Science Najran UniversitySharourahSaudi Arabia Departm.nt of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

Novel coronavirus 2019(COVID-19)has affected the people’s health,their lifestyle and econom.cal status across the *** application of advanced Artificial Intelligence(AI)m.thods in com.ination with radiological im.ging is useful in accurate detection of the *** also assists the physicians to take care of rem.te villages *** current research paper proposes a novel autom.tedCOVID-19 analysism.thod with the help ofOptim.l Hybrid Feature Extraction(OHFE)and Optim.l Deep Neural Network(ODNN)called OHFE-ODNN from.chest x-ray *** objective of the presented technique is for perform.ng binary and m.lti-class classification of COVID-19 analysis from.chest X-ray *** presented OHFE-ODNN m.thod includes a sequence of procedures such as m.dian Filtering(m.)-based pre-processed,feature extraction and finally,binary(COVID/Non-COVID)and m.lticlass(Norm.l,COVID,SARS)***,in OHFE-based feature extraction,Gray Level Co-occurrence m.trix(GLCm.and Histogram.of Gradients(HOG)are integrated *** presented OHFE-ODNN m.del includes Squirrel Search Algorithm.SSA)for finetuning the param.ters of *** perform.nce of the presented OHFEODNN technique is conducted using chest x-rays *** presented OHFE-ODNN m.thod classified the binary classes effectively with a m.xim.m.recision of 95.82%,accuracy of 94.01%and F-score of 96.61%.Besides,m.ltiple classes were classified proficiently by OHFE-ODNN m.del with a precision of 95.63%,accuracy of 95.60%and an F-score of 95.73%.

关键词： COVID-19 classification deep learning radiological im.ges

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Artificial Intelligence Enabled Apple Leaf Disease Classification for Precision Agriculture

引用

Com.uters, m.terials & Continua 2022年第3期70卷 6223-6238页

作者： Fahd N.Al-Wesabi Am.ni Abdulrahm.n Albraikan Anwer m.stafa Hilal m.jdy m.Eltahir manar Ahm.d Ham.a Abu Sarwar Zam.ni Departm.nt of Com.uter Science King Khalid UniversityMuhayel AseerSaudi Arabia Faculty of Com.uter and IT Sana’a UniversityYemen Departm.nt of Inform.tion System. College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversitySaudi Arabia Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlkharjSaudi Arabia

Precision agriculture enables the recent technological advancem.nts in farm.ng sector to observe,m.asure,and analyze the requirem.nts of individual fields and *** recent developm.nts of com.uter vision and artificial intelligence(AI)techniques find a way for effective detection of plants,diseases,weeds,pests,*** the other hand,the detection of plant diseases,particularly apple leaf diseases using AI techniques can im.rove productivity and reduce crop ***,earlier and precise apple leaf disease detection can m.nim.ze the spread of the *** works m.ke use of traditional im.ge processing techniques which cannot assure high detection rate on apple leaf *** this m.tivation,this paper introduces a novel AI enabled apple leaf disease classification(AIE-ALDC)technique for precision *** proposed AIE-ALDC technique involves orientation based data augm.ntation and Gaussian filtering based noise rem.val *** addition,the AIE-ALDC technique includes a Capsule Network(CapsNet)based feature extractor to generate a helpful set of feature ***,water wave optim.zation(WWO)technique is em.loyed as a hyperparam.ter optim.zer of the CapsNet ***,bidirectional long short term.m.m.ry(BiLSTm.m.del is used as a classifier to determ.ne the appropriate class labels of the apple leaf *** design of AIE-ALDC technique incorporating theWWO based CapsNetm.del with BiLSTm.classifier shows the novelty of the *** range of experim.nts was perform.d to showcase the suprem.cy of the AIE-ALDC *** experim.ntal results dem.nstrate the prom.sing perform.nce of the AIEALDC technique over the recent state of art m.thods.

关键词： Artificial intelligence apple leaf plant disease precision agriculture deep learning data augm.ntation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

IoT-Driven Optim.l Lightweight RetinaNet-Based Object Detection for Visually Im.aired People

引用

Com.uter System. Science & Engineering 2023年第7期46卷 475-489页

作者： m.sfer Alduhayyem.m.im.m.Alnfiai Nabil Alm.lki Fahd N.Al-Wesabi Anwer m.stafa Hilal manar Ahm.d Ham.a Departm.nt of Com.uter Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia King Salm.n Center for Disability Research RiyadhAl-Hayātim 16273Saudi Arabia Departm.nt of Inform.tion Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Departm.nt of Special Education College of EducationKing Saud UniversityRiyadh12372Saudi Arabia Departm.nt of Com.uter Science College of Science&ArtsKing Khaled UniversityAr-Riyad 12372Saudi Arabia Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Visual im.airm.nt is one of the m.jor problem. am.ng people of all age groups across the *** Im.aired Persons(VIPs)require help from.others to carry out their day-to-day *** they experience several problem. in their daily lives,technical intervention can help them.resolve the *** this background,an autom.tic object detection tool is the need of the hour to em.ower VIPs with safe *** recent advances in the Internet of Things(IoT)and Deep Learning(DL)techniques m.ke it *** current study proposes IoT-assisted Transient Search Optim.zation with a Lightweight RetinaNetbased object detection(TSOLWR-ODVIP)m.del to help *** prim.ry aim.of the presented TSOLWR-ODVIP technique is to identify different objects surrounding VIPs and to convey the inform.tion via audio m.ssage to *** data acquisition,IoT devices are used in this ***,the Lightweight RetinaNet(LWR)m.del is applied to detect objects ***,the TSO algorithm.is em.loyed for fine-tuning the hyperparam.ters involved in the LWR ***,the Long Short-Term.m.m.ry(LSTm.m.del is exploited for classifying *** perform.nce of the proposed TSOLWR-ODVIP technique was evaluated using a set of objects,and the results were exam.ned under distinct *** com.arison study outcom.s confirm.d that the TSOLWR-ODVIP m.del could effectually detect and classify the objects,enhancing the quality of life of VIPs.

关键词： Visually im.aired people deep learning object detection com.uter vision long short-term.m.m.ry transient search optim.zation

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Deep Learning Driven Arabic Text to Speech Synthesizer for Visually Challenged People

引用

Intelligent Autom.tion & Soft Com.uting 2023年第6期36卷 2639-2652页

作者： m.im.m.Alnfiai Nabil Alm.lki Fahd N.Al-Wesabi m.sfer Alduhayyem.Anwer m.stafa Hilal manar Ahm.d Ham.a King Salm.n Center for Disability Research Riyadh13369Saudi Arabia Departm.nt of Inform.tion Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Departm.nt of Special Education College of EducationKing Saud UniversityRiyadh12372Saudi Arabia Departm.nt of Com.uter Science College of Science&Arts at MuhayelKing Khaled UniversityAbha62217Saudi Arabia Departm.nt of Com.uter Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversityAl-Aflaj16733Saudi Arabia Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16242Saudi Arabia

Text-To-Speech(TTS)is a speech processing tool that is highly helpful for visually-challenged *** TTS tool is applied to transform.the texts into hum.n-like ***,it is highly challenging to accom.lish the TTS out-com.s for the non-diacritized text of the Arabic language since it has m.ltiple unique features and *** special characters like gem.nation and diacritic signs that correspondingly indicate consonant doubling and short vowels greatly im.act the precise pronunciation of the Arabic ***,such signs are not frequently used in the texts written in the Arabic language since its speakers and readers can guess them.from.the context *** this background,the current research article introduces an Optim.l Deep Learning-driven Arab Text-to-Speech Synthesizer(ODLD-ATSS)m.del to help the visually-challenged people in the Kingdom.of Saudi *** prim. aim.of the presented ODLD-ATSS m.del is to convert the text into speech signals for visually-challenged *** attain this,the presented ODLD-ATSS m.del initially designs a Gated Recurrent Unit(GRU)-based prediction m.del for diacritic and gem.nation ***,the Buckwalter code is utilized to capture,store and display the Arabic *** im.rove the TSS perform.nce of the GRU m.thod,the Aquila Optim.zation Algorithm.AOA)is used,which shows the novelty of the *** illustrate the enhanced perform.nce of the proposed ODLD-ATSS m.del,further experi-m.ntal analyses were *** proposed m.del achieved a m.xim.m.accu-racy of 96.35%,and the experim.ntal outcom.s infer the im.roved perform.nce of the proposed ODLD-ATSS m.del over other DL-based TSS m.dels.

关键词： Saudi Arabia visually challenged people deep learning Aquila optim.zer gated recurrent unit

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Cuckoo Optim.zed Convolution Support Vector m.chine for Big Health Data Processing

引用

Com.uters, m.terials & Continua 2022年第11期73卷 3039-3055页

作者： Eatedal Alabdulkreem.Jaber S.Alzahrani m.jdy m.Eltahir Abdullah m.ham.d manar Ahm.d Ham.a Abdelwahed m.twakel m.ham.d I.Eldesouki m.ham.ed Rizwanullah Departm.nt of Com.uter Sciences College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Departm.nt of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversityMecca24382Saudi Arabia Departm.nt of Inform.tion System. College of Science&Art at MahayilKing Khalid UniversityAbha 62529Saudi Arabia Research Centre Future University in EgyptNew Cairo11845Egypt Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam Bin Abdulaziz UniversityAlKharj16278Saudi Arabia Departm.nt of Inform.tion System College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAlKharj16278Saudi Arabia

Big health data collection and storing for further analysis is a challenging task because this knowledge is big and has m.ny *** cloud-based IoT health providers have been described in the literature ***,there are a num.er of issues related to tim. consum.d and overall network perform.nce when it com.s to big data *** the existing m.thod,less perform.d optim.zation algorithm. were used for optim.zing the *** the proposed m.thod,the Chaotic Cuckoo Optim.zation algorithm.was used for feature selection,and Convolutional Support Vector m.chine(CSVm.was *** research presents a m.thod for analyzing healthcare inform.tion that uses in future *** m.jor goal is to take a variety of data while im.roving efficiency and m.nim.zing process *** suggested m.thod em.loys a hybrid m.thod that is divided into two *** the first stage,it reduces the features by using the Chaotic Cuckoo Optim.zation algorithm.with Levy flight,opposition-based learning,and distributor *** the second stage,CSVm.is used which com.ines the benefits of convolutional neural network(CNN)and *** CSVm.m.difies CNN’s convolution product to learn hidden deep inside data *** im.roved econom.c flexibility,greater protection,greater analytics with confidentiality,and lower operating cost,the suggested approach is built on fog *** results of the experim.nts show that the suggested m.thod can m.nim.ze the num.er of features in the datasets,enhances the accuracy by 82%,and decrease the tim. of the process.

关键词： Healthcare convolutional support vector m.chine feature selection chaotic cuckoo optim.zation accuracy processing tim. convolutional neural network

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Blockchain Driven m.taheuristic Route Planning in Secure Vehicular Adhoc Networks

引用

Com.uters, m.terials & Continua 2022年第12期73卷 6461-6477页

作者： Siwar Ben Haj Hassine Saud SAlotaibi Hadeel Alsolai Reem.Alshahrani Lilia Kechiche m.im.m.Alnfiai Am.ra Sayed A.Aziz manar Ahm.d Ham.a Departm.nt of Com.uter Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Departm.nt of Inform.tion System. College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Departm.nt of Inform.tion System. College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Departm.nt of Com.uter Science College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Departm.nt of Sciences and Technology Taif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Departm.nt of Inform.tion Technology College of Computers and Information TechnologyTaif UniversityTaif P.O.Box 11099Taif21944Saudi Arabia Departm.nt of Digital m.dia Faculty of Computers and Information TechnologyFuture University in EgyptNew Cairo11835Egypt Departm.nt of Com.uter and Self Developm.nt Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

Nowadays,vehicular ad hoc networks(VANET)turn out to be a core portion of intelligent transportation system.(ITSs),that m.inly focus on achieving continual Internet connectivity am.ngst vehicles on the *** VANET was utilized to enhance driving safety and build an ITS in m.dern *** safety is a m.in portion of VANET,the privacy and security of these m.ssages should be *** this aspect,this article presents a blockchain with sunflower optim.zation enabled route planning schem.(BCSFO-RPS)for secure *** presented BCSFO-RPSm.del focuses on the identification of routes in such a way that vehicular com.unication is *** addition,the BCSFO-RPS m.del em.loys SFO algorithm.with a fitness function for effectual identification of ***,the proposed BCSFO-RPS m.del derives an intrusion detection system.IDS)encom.assing two processes nam.ly feature selection and *** detect intrusions,correlation based feature selection(CFS)and kernel extrem. m.chine learning(KELm.classifier is *** perform.nce of the BCSFO-RPS m.del is tested using a series of experim.nts and the results reported the enhancem.nts of the BCSFO-RPS m.del over other approaches with m.xim.m.accuracy of 98.70%.

关键词： VANET sunflower optim.zation m.chine learning blockchain intrusion detection

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：