检索结果-南通市图书馆

A Constraint Adaptive Multi-Tasking Differential Evolution Algorithm:Designed for Dispatch of Integrated Energy System in Coal Mine

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Tsinghua Science and technology 2024年第2期29卷 368-385页

作者： Canyun Dai Xiaoyan Sun Hejuan Hu Yong Zhang Dunwei Gong school of information and Control Engineering China University of Mining and TechnologyXuzhou 221116China school of information Science and technology Qingdao University of Science and TechnologyQingdao 266061China

The dispatch of integrated energy systems in coal mines(IES-CM)with mine-associated supplies is vital for efficient energy utilization and carbon emissions ***,IES-CM dispatch is highly challenging due to its feature as multi-objective and strong *** constrained multi-objective evolutionary algorithms often fall into locally feasible domains with poorly distributed Pareto front,which greatly deteriorates dispatch *** tackle this problem,we transform the traditional dispatch model of IES-CM into two tasks:the main task with all constraints and the helper task with constraint *** we propose a constraint adaptive multi-tasking differential evolution algorithm(CA-MTDE)to optimize these two tasks *** helper task with constraint adaptive is developed to obtain infeasible solutions near the feasible *** purpose of this infeasible solution is to transfer guiding knowledge to help the main task move away from local ***,a dynamic dual-learning strategy using DE/current-to-rand/1 and DE/current-to-best/1 is developed to maintain task diversity and ***,we comprehensively evaluate the performance of CA-MTDE by applying it to a coal mine in Shanxi Province,considering two IES-CM *** demonstrate the feasibility of CA-MTDE and its ability to generate a Pareto front with exceptional convergence,diversity,and distribution.

关键词： dispatch integrated energy system coal mine evolutionary multi-tasking constraint differential evolution

BLS-identification:A device fingerprint classification mechanism based on broad learning for Internet of Things

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Digital Communications and Networks 2024年第3期10卷 728-739页

作者： Yu Zhang Bei Gong Qian Wang Faculty of information technology Beijing University of TechnologyBeijing100124China school of information Science and technology Zhengzhou Normal UniversityHenan450044China

The popularity of the Internet of Things(IoT)has enabled a large number of vulnerable devices to connect to the Internet,bringing huge security *** a network-level security authentication method,device fingerprint based on machine learning has attracted considerable attention because it can detect vulnerable devices in complex and heterogeneous access ***,flexible and diversified IoT devices with limited resources increase dif-ficulty of the device fingerprint authentication method executed in IoT,because it needs to retrain the model network to deal with incremental features or *** address this problem,a device fingerprinting mechanism based on a Broad Learning System(BLS)is proposed in this *** mechanism firstly characterizes IoT devices by traffic analysis based on the identifiable differences of the traffic data of IoT devices,and extracts feature parameters of the traffic packets.A hierarchical hybrid sampling method is designed at the preprocessing phase to improve the imbalanced data distribution and reconstruct the fingerprint *** complexity of the dataset is reduced using Principal Component Analysis(PCA)and the device type is identified by training weights using *** experimental results show that the proposed method can achieve state-of-the-art accuracy and spend less training time than other existing methods.

关键词： Device fingerprint Traffic analysis Class imbalance Broad learning system Access authentication

Energy consumption optimization for edge computing-supported cellular networks based on optimal transport theory

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(information Sciences) 2024年第2期67卷 201-218页

作者： Xiangyu LV Xiaohu GE Yi ZHONG Qiang LI Yong XIAO school of Electronic information and Communications Huazhong University of Science and Technology

With advancements in mobile communication technologies, there have been multiple user device(UD) connections to cellular networks. Because of changes in the spatial distribution of UDs and application requirements, the traditional offloading mechanism based on the nearest distance will result in heavy loads for some base stations(BSs). Because there is a high-order relationship between the energy consumption of the BS processing tasks and the number of computing tasks, the traditional offloading mechanism will result in high energy consumption, and UD’s offloading decision must be dynamically adjusted. The offloading decision of UDs is optimized based on detailed information about various parameters associated with a network from the standpoint of distribution. This information includes details regarding the spatial distribution of UDs,application requirements, and the offloading period of computing tasks. Based on optimal transport theory,an energy consumption optimization algorithm is suggested to lower the total amount of energy consumed by the offloading process of UDs’ computing tasks by reasonably planning the offloading BSs of the UDs in the networks. The simulation results show that the proposed offloading mechanism based on energy consumption optimization reduces the total energy consumption of the offloading process by 28.09% when compared to the traditional offloading mechanism, and the traffic managed by each BS is balanced.

关键词： optimal transport theory edge computing energy consumption reduction dynamic voltage frequency scaling

Federated Meta Reinforcement Learning for Personalized Tasks

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Tsinghua Science and technology 2024年第3期29卷 911-926页

作者： Wentao Liu Xiaolong Xu Jintao Wu Jielin Jiang school of Computer Science Nanjing University of Information Science and TechnologyNanjing 210044China school of Software Nanjing University of Information Science and TechnologyNanjing 210044China

As an emerging privacy-preservation machine learning framework,Federated Learning(FL)facilitates different clients to train a shared model collaboratively through exchanging and aggregating model parameters while raw data are kept local and *** this learning framework is applied to Deep Reinforcement Learning(DRL),the resultant Federated Reinforcement Learning(FRL)can circumvent the heavy data sampling required in conventional DRL and benefit from diversified training data,besides privacy preservation offered by *** FRL implementations presuppose that clients have compatible tasks which a single global model can *** practice,however,clients usually have incompatible(different but still similar)personalized tasks,which we called task *** may severely hinder the implementation of FRL for practical *** this paper,we propose a Federated Meta Reinforcement Learning(FMRL)framework by integrating Model-Agnostic Meta-Learning(MAML)and ***,we innovatively utilize Proximal Policy Optimization(PPO)to fulfil multi-step local training with a single round of ***,considering the sensitivity of learning rate selection in FRL,we reconstruct the aggregation optimizer with the Federated version of Adam(Fed-Adam)on the server *** experiments demonstrate that,in different environments,FMRL outperforms other FL methods with high training efficiency brought by Fed-Adam.

关键词： federated learning reinforcement learning meta-learning personalization

A deep learning model enabled multi-event recognition for distributed optical fiber sensing

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Science China(information Sciences) 2024年第3期67卷 291-307页

作者： Yujiao LI Xiaomin CAO Wenhao NI Kuanglu YU Institute of information Science School of Computer and Information TechnologyBeijing Jiaotong University Beijing Key Laboratory of Advanced information Science and Network technology Beijing Jiaotong University

Fiber optic sensors that utilize backscattered light offer distributed real-time measurements and have been seen tremendous improvements in sensing distance and spatial resolution over the last ***, these improvements in sensor capabilities lead to a significant increase in the amount of data that needs to be processed. Traditional processing schemes are no longer adequate, so the development of novel signal processing methods is critical. Phase-sensitive optical time domain reflectometry(Φ-OTDR) is now applied in various applications for multi-event recognition, and it would usually be difficult, sometimes even unrealistic to label all the acquired samples due to its real-time and seamless monitoring nature. To fully take advantage of the information contained within the large number of unlabeled samples, which were formerly not utilized and hence wasted, we propose a semi-supervised model to boost the event classification performance of Φ-OTDR. The model extracts respectively the temporal features and the spatial bidirectional features together with a dual attention mechanism. Its classification accuracy has been improved up to 96.9%with only 1230 labeled samples. In addition, our model shows significant advantages when the number of labeled samples is reduced. Importantly, our method improves the accuracy of multi-event classification without any modification to the optical setup.

关键词： $\Phi$-OTDR event recognition semi-supervised learning mean teacher MT-ACNN-SA-BiLSTM

同方期刊数据库

Effect of Deposition Temperature on Optical Properties of Porous Amorphous SiC Film

在线全文

学校读者我要写书评

暂无评论

Journal of Wuhan university of technology(Materials Science) 2024年第4期39卷 839-844页

作者：徐吉祥 TAO Weijie LIU Canhui XU Haoyao LI Lixuan 贺振华 school of information Engineering Wuhan University of TechnologyWuhan 430070China

To study the effect of different deposition temperatures on the optical properties of porous SiC films,single crystal Si was used as the substrate,a layer of anodic aluminum oxide(AAO)film was transferred on the Si substrate by chemical method,and then a layer of SiC was deposited on anodic aluminum oxide(AAO)template to prepare porous fluorescent SiC film by magnetron *** deposition temperature was ranged from 373 to 873 *** thickness of the porous SiC film coated on the AAO surface was around 283 *** is found that the porous SiC with the deposition temperature of 873 K has the strongest photoluminescence(PL)intensity excited by 375 nm *** time-resolved PL spectra prove that the PL is mainly from intrinsic light emitting of *** the optimized process,porous amorphous SiC film may have potential applications in the field of warm white LEDs.

关键词： porous SiC film fluorescent SiC anodic aluminum oxide magnetron sputtering time-resolved spectrum

维普期刊数据库

Protein acetylation sites with complex-valued polynomial model

在线全文

学校读者我要写书评

暂无评论

Frontiers of Computer Science 2024年第3期18卷 217-226页

作者： Wenzheng BAO Bin YANG school of information Engineering Xuzhou University of TechnologyXuzhou 221018China school of information Science and Engineering Zaozhuang UniversityZaozhuang 277160China

Protein acetylation refers to a process of adding acetyl groups(CH3CO-)to lysine residues on protein *** one of the most commonly used protein post-translational modifications,lysine acetylation plays an important role in different *** our study,we developed a humanspecific method which uses a cascade classifier of complexvalued polynomial model(CVPM),combined with sequence and structural feature descriptors to solve the problem of imbalance between positive and negative *** gene expression programming and differential evolution are utilized to search the optimal CVPM *** also made a systematic and comprehensive analysis of the acetylation data and the prediction *** performances of our proposed method are 79.15%in Sp,78.17%in Sn,78.66%in ACC 78.76%in F1,and 0.5733 in MCC,which performs better than other state-of-the-art methods.

关键词： protein acetylation complex-valued polynomial model machine learning

General multi-attack detection for continuous-variable quantum key distribution with local local oscillator

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Chinese Physics B 2024年第5期33卷 255-262页

作者：康茁刘维琪齐锦贺晨 school of information Science and technology Northwest UniversityXi'an 710127China

Continuous-variable quantum key distribution with a local local oscillator(LLO CVQKD)has been extensively researched due to its simplicity and *** practical security of an LLO CVQKD system,there are two main attack modes referred to as reference pulse attack and polarization attack ***,there is currently no general defense strategy against such attacks,and the security of the system needs further ***,we employ a deep learning framework called generative adversarial networks(GANs)to detect both *** first analyze the data in different cases,derive a feature vector as input to a GAN model,and then show the training and testing process of the GAN model for attack *** proposed model has two parts,a discriminator and a generator,both of which employ a convolutional neural network(CNN)to improve *** results show that the proposed scheme can detect and classify attacks without reducing the secret key rate and the maximum transmission *** only establishes a detection model by monitoring features of the pulse without adding additional devices.

关键词： CVQKD generative adversarial network attack classification

维普期刊数据库

Detection accuracy of target accelerations based on vortex electromagnetic wave in keyhole space

在线全文

学校读者我要写书评

暂无评论

Chinese Physics B 2024年第2期33卷 283-290页

作者：郭凯雷爽雷艺周红平郭忠义 school of Computer and information Hefei University of TechnologyHefei 230009China

The influence of the longitudinal acceleration and the angular acceleration of detecting target based on vortex electromagnetic waves in keyhole space are *** spectrum spreads of different orbital angular momentum(OAM)modes in different non-line-of-sight situations are *** errors of target accelerations in detection are calculated and compared based on the OAM spectra spreading by using two combinations of composite OAM modes in the keyhole *** to the research,the effects about spectrum spreads of higher OAM modes are more *** error in detection is mainly affected by OAM spectrum spreading,which can be reduced by reasonably using different combinations of OAM modes in different practical *** above results provide a reference idea for investigating keyhole effect when vortex electromagnetic wave is used to detect accelerations.

关键词： vortex electromagnetic waves detect accelerations keyhole space spectrum spread

维普期刊数据库