期刊文献+
任意字段
题名或关键词
题名
关键词
摘要
作者
第一作者
机构
刊名
分类号
参考文献
作者简介
基金资助
栏目信息
共找到3,335篇文章
< 1 2 … 167 >
每页显示 20 50 100
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
显示方式：
AI and Deep Learning for Terahertz Ultra-Massive MIMO:From Model-Driven Approaches to Foundation Models 认领 引用 被引量：1
1
作者 Wentao Yu Hengtao He +4 位作者 Shenghui Song Jun Zhang Linglong Dai Lizhong Zheng Khaled B.Letaief 《Engineering》 SCIE EI CSCD 2026年第1期14-33,共20页
This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the ch... This study explored the transformative potential of artificial intelligence(AI)in addressing the challenges posed by terahertz ultra-massive multiple-input multiple-output(UM-MIMO)systems.It begins by outlining the characteristics of terahertz UM-MIMO systems and identifies three primary challenges for transceiver design:computational complexity,modeling difficulty,and measurement limitations.The study posits that AI provides a promising solution to these challenges.Three systematic research roadmaps are proposed for developing AI algorithms tailored to terahertz UM-MIMO systems.The first roadmap,model-driven deep learning(DL),emphasizes the importance of leveraging available domain knowledge and advocates the adoption of AI only to enhance bottleneck modules within an established signal processing or optimization framework.Four essential steps are discussed:algorithmic frameworks,basis algorithms,loss function design,and neural architecture design.The second roadmap presents channel state information(CSI)foundation models,aimed at unifying the design of different transceiver modules by focusing on their shared foundation,that is,the wireless channel.The training of a single compact foundation model is proposed to estimate the score function of wireless channels,which serve as a versatile prior for designing a wide variety of transceiver modules.Four essential steps are outlined:general frameworks,conditioning,site-specific adaptation,and the joint design of CSI foundation models and model-driven DL.The third roadmap aims to explore potential directions for applying pretrained large language models(LLMs)to terahertz UM-MIMO systems.Several application scenarios are envisioned,including LLM-based estimation,optimization,search,network management,and protocol understanding.Finally,the study highlights open problems and future research directions. 展开更多
关键词 Terahertz communications Ultra-massive multiple-input multiple-output Model-driven deep learning Foundation models Large language models
暂未订购 下载PDF
AI Large Model-Driven Adaptive Evolution of Brain-Computer Interface Chips:Technical Architecture,Challenges,and Future Directions 认领 引用
2
作者 Borui Cui 《Journal of Electronic Research and Application》 2026年第1期209-220,共12页
This paper focuses on how AI large models,such as Transformers and meta-learning can empower brain-computer interface(BCI)chips to achieve dynamic adaptation,thereby overcoming the limitations of traditional fixed dec... This paper focuses on how AI large models,such as Transformers and meta-learning can empower brain-computer interface(BCI)chips to achieve dynamic adaptation,thereby overcoming the limitations of traditional fixed decoding models that struggle to adapt to individual neural plasticity and dynamic changes in brain states.It analyzes pathways to enhance chip generalization and real-time performance across three technical dimensions:hardware architecture,algorithm optimization,and multimodal fusion.The paper also explores core challenges like data privacy and energy-efficiency tradeoffs.Building on this foundation,it proposes a neuromorphic computing design framework for next-generation chips to advance the intelligent and personalized development of BCI in medical rehabilitation and human-computer interaction. 展开更多
关键词 Brain-computer interface Artificial intelligence Chip Large model-driven Meta-learning
暂未订购 下载PDF
Deep learning aided underwater acoustic OFDM receivers: Model-driven or data-driven? 认领 引用
3
作者 Hao Zhao Miaowen Wen +3 位作者 Fei Ji Yaokun Liang Hua Yu Cui Yang 《Digital Communications and Networks》 SCIE EI CSCD 2025年第3期866-877,共12页
The Underwater Acoustic(UWA)channel is bandwidth-constrained and experiences doubly selective fading.It is challenging to acquire perfect channel knowledge for Orthogonal Frequency Division Multiplexing(OFDM)communica... The Underwater Acoustic(UWA)channel is bandwidth-constrained and experiences doubly selective fading.It is challenging to acquire perfect channel knowledge for Orthogonal Frequency Division Multiplexing(OFDM)communications using a finite number of pilots.On the other hand,Deep Learning(DL)approaches have been very successful in wireless OFDM communications.However,whether they will work underwater is still a mystery.For the first time,this paper compares two categories of DL-based UWA OFDM receivers:the DataDriven(DD)method,which performs as an end-to-end black box,and the Model-Driven(MD)method,also known as the model-based data-driven method,which combines DL and expert OFDM receiver knowledge.The encoder-decoder framework and Convolutional Neural Network(CNN)structure are employed to establish the DD receiver.On the other hand,an unfolding-based Minimum Mean Square Error(MMSE)structure is adopted for the MD receiver.We analyze the characteristics of different receivers by Monte Carlo simulations under diverse communications conditions and propose a strategy for selecting a proper receiver under different communication scenarios.Field trials in the pool and sea are also conducted to verify the feasibility and advantages of the DL receivers.It is observed that DL receivers perform better than conventional receivers in terms of bit error rate. 展开更多
关键词 Deep learning Doubly-selective channels Data-driven Model-driven Underwater acoustic communication OFDM
暂未订购 下载PDF
4K-DMDNet:diffraction model-driven network for 4K computer-generated holography 认领 引用 被引量：33
4
作者 Kexuan Liu Jiachen Wu +1 位作者 Zehao He Liangcai Cao 《Opto-Electronic Advances》 SCIE EI CAS CSCD 2023年第5期17-29,共13页
Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training dataset... Deep learning offers a novel opportunity to achieve both high-quality and high-speed computer-generated holography(CGH).Current data-driven deep learning algorithms face the challenge that the labeled training datasets limit the training performance and generalization.The model-driven deep learning introduces the diffraction model into the neural network.It eliminates the need for the labeled training dataset and has been extensively applied to hologram generation.However,the existing model-driven deep learning algorithms face the problem of insufficient constraints.In this study,we propose a model-driven neural network capable of high-fidelity 4K computer-generated hologram generation,called 4K Diffraction Model-driven Network(4K-DMDNet).The constraint of the reconstructed images in the frequency domain is strengthened.And a network structure that combines the residual method and sub-pixel convolution method is built,which effectively enhances the fitting ability of the network for inverse problems.The generalization of the 4K-DMDNet is demonstrated with binary,grayscale and 3D images.High-quality full-color optical reconstructions of the 4K holograms have been achieved at the wavelengths of 450 nm,520 nm,and 638 nm. 展开更多
关键词 computer-generated holography deep learning model-driven neural network sub-pixel convolution oversampling
暂未订购 下载PDF
Assessing a Model-Driven Web-Application Engineering Approach 认领 引用 被引量：2
5
作者 Ali Fatolahi Stephane S. Some 《Journal of Software Engineering and Applications》 2014年第5期360-370,共11页
Model-Driven Engineering (MDE) by reframing software development as the transformation of high-level models, promises lots of gains to Software Engineering in terms of productivity, quality and reusability. Although a... Model-Driven Engineering (MDE) by reframing software development as the transformation of high-level models, promises lots of gains to Software Engineering in terms of productivity, quality and reusability. Although a number of empirical studies have established the reality of these gains, there are still lots of reluctances toward the adoption of MDE in practice. This resistance can be explained by several technological and social factors among which a natural scepticism toward novel approaches. In this paper we attempt to provide arguments to help alleviate this scepticism by conducting an assessment of a MDE approach. Our goal is to show that although this MDE is novel, it retains similarities with the conventional Software Engineering approach while automating aspects of it. 展开更多
关键词 Model-Driven Engineering (MDE) Software Process Assessment Web-Engineering
暂未订购 下载PDF
NDT-Suite: A Methodological Tool Solution in the Model-Driven Engineering Paradigm 认领 引用
6
作者 Julián Alberto García-García María José Escalona +1 位作者 Francisco José Domínguez-Mayo Alberto Salido 《Journal of Software Engineering and Applications》 2014年第4期206-217,共12页
Although the Model-Driven paradigm is being accepted in the research environment as a very useful and powerful option for effective software development, its real application in the enterprise context is still a chall... Although the Model-Driven paradigm is being accepted in the research environment as a very useful and powerful option for effective software development, its real application in the enterprise context is still a challenge for software engineering. Several causes can be stacked out, but one of them can be the lack of tool support for the efficient application of this paradigm. This paper presents a set of tools, grouped in a suite named NDT-Suite, which under the Model-Driven paradigm offer a suitable solution for software development. These tools explore different options that this paradigm can improve such as, development, quality assurance or requirement treatment. Besides, this paper analyses how they are being successfully applied in the industry. 展开更多
关键词 Model-Driven Web Engineering Model-Based Suite Tools Practical Experiences NDT NDT-Suite
暂未订购 下载PDF
A comprehensive review of remaining useful life prediction methods for lithium-ion batteries:Models,trends,and engineering applications 认领 引用 被引量：1
7
作者 Yang Li Haotian Shi +5 位作者 Shunli Wang Qi Huang Chunmei Liu Shiliang Nie Xianyi Jia Tao Luo 《Journal of Energy Chemistry》 SCIE EI CAS CSCD 2026年第1期384-414,I0009,共31页
Under complex working conditions,accurate prediction of the remaining useful life(RUL)of lithium-ion batteries is of great significance to ensure the stable operation of energy storage systems,the safe driving of elec... Under complex working conditions,accurate prediction of the remaining useful life(RUL)of lithium-ion batteries is of great significance to ensure the stable operation of energy storage systems,the safe driving of electric vehicles,and the continuous power supply of electronic devices.This paper systematically describes the RUL prediction methods of lithium-ion batteries and comprehensively summarizes the development status and future trends in this field.First,the battery degradation mechanisms and lightweight data acquisition are analyzed.Secondly,a systematic classification model is constructed for the more widely used lithium battery RUL prediction methods,and the application characteristics and implementation limitations of different methods are analyzed in detail.An innovative classification framework for hybrid methods is proposed based on the depth of physical-data interaction.Then,collaborative modelling of calendar ageing and cyclic ageing is discussed,revealing their coupled effects and corresponding RUL prediction methods.Finally,the technical bottlenecks faced by the current RUL prediction of lithium batteries are identified,potential solutions are proposed,and the future development trends are outlined. 展开更多
关键词 Lithium-ion batteries Remaining useful life Model-driven approach Data-driven approach Hybrid approach
暂未订购 下载PDF
High-Performance Segmentation of Power Lines in Aerial Images Using a Wavelet-Guided Hybrid Transformer Network 认领 引用 被引量：1
8
作者 Burhan Baraklı Ahmet Küçüker 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第2期772-802,共31页
Inspections of power transmission lines(PTLs)conducted using unmanned aerial vehicles(UAVs)are complicated by the fine structure of the lines and complex backgrounds,making accurate and efficient segmentation challeng... Inspections of power transmission lines(PTLs)conducted using unmanned aerial vehicles(UAVs)are complicated by the fine structure of the lines and complex backgrounds,making accurate and efficient segmentation challenging.This study presents the Wavelet-Guided Transformer U-Net(WGT-UNet)model,a new hybrid net-work that combines Convolutional Neural Networks(CNNs),Discrete Wavelet Transform(DWT),and Transformer architectures.The model’s primary contribution is based on spatial and channel attention mechanisms derived from wavelet subbands to guide the Transformer’s self-attention structure.Thus,low and high frequency components are separated at each stage using DWT,suppressing structural noise and making linear objects more prominent.The developed design is supported by multi-component hybrid cost functions that simultaneously solve class imbalance,edge sharpness,structural integrity,and spatial regularity issues.Furthermore,high segmentation success has been achieved in producing sharp boundaries and continuous line structures with the DWT-guided attention mechanism.Experiments conducted on the TTPLA dataset reveal that the version using the ConvNeXt backbone outperforms the current state-of-the-art approaches with an F1-Score of 79.33%and an Intersection over Union(IoU)value of 68.38%.The models and visual outputs of the developed method and all compared models can be accessed at http://gffzz188fe103f8f1460askbo0nu599uqq66b6.ffgz.tsg.suse.edu.cn/burhanbarakli/WGT-UNET. 展开更多
关键词 Salient object detection superpixel segmentation transformers attention mechanism multi-level fusion edge-preserving refinement model-driven
暂未订购 下载PDF
Superpixel-Aware Transformer with Attention-Guided Boundary Refinement for Salient Object Detection 认领 引用
9
作者 Burhan Baraklı Can Yüzkollar +1 位作者 Tugrul Ta¸sçı Ibrahim Yıldırım 《Computer Modeling in Engineering & Sciences》 SCIE EI 2026年第1期1092-1129,共38页
Salient object detection(SOD)models struggle to simultaneously preserve global structure,maintain sharp object boundaries,and sustain computational efficiency in complex scenes.In this study,we propose SPSALNet,a task... Salient object detection(SOD)models struggle to simultaneously preserve global structure,maintain sharp object boundaries,and sustain computational efficiency in complex scenes.In this study,we propose SPSALNet,a task-driven two-stage(macro–micro)architecture that restructures the SOD process around superpixel representations.In the proposed approach,a“split-and-enhance”principle,introduced to our knowledge for the first time in the SOD literature,hierarchically classifies superpixels and then applies targeted refinement only to ambiguous or error-prone regions.At the macro stage,the image is partitioned into content-adaptive superpixel regions,and each superpixel is represented by a high-dimensional region-level feature vector.These representations define a regional decomposition problem in which superpixels are assigned to three classes:background,object interior,and transition regions.Superpixel tokens interact with a global feature vector from a deep network backbone through a cross-attention module and are projected into an enriched embedding space that jointly encodes local topology and global context.At the micro stage,the model employs a U-Net-based refinement process that allocates computational resources only to ambiguous transition regions.The image and distance–similarity maps derived from superpixels are processed through a dual-encoder pathway.Subsequently,channel-aware fusion blocks adaptively combine information from these two sources,producing sharper and more stable object boundaries.Experimental results show that SPSALNet achieves high accuracy with lower computational cost compared to recent competing methods.On the PASCAL-S and DUT-OMRON datasets,SPSALNet exhibits a clear performance advantage across all key metrics,and it ranks first on accuracy-oriented measures on HKU-IS.On the challenging DUT-OMRON benchmark,SPSALNet reaches a MAE of 0.034.Across all datasets,it preserves object boundaries and regional structure in a stable and competitive manner. 展开更多
关键词 Salient object detection superpixel segmentation transformers attention mechanism multi-level fusion edge-preserving refinement model-driven
暂未订购 下载PDF
厄尔尼诺-南方涛动研究的海气耦合模式:物理驱动与数据驱动模型的融合建模及示范案例 认领 引用 被引量：2
10
作者 张荣华 李殷楠 +10 位作者 杜双盈 高川 周路 朱聿超 于洋 陶灵江 智海 冯立成 陈林 徐邦琪 陆波 《大气科学学报》 CSCD 北大核心 2026年第1期1-19,共19页
厄尔尼诺-南方涛动(El Nino-Southern Oscillation,ENSO)作为地球气候系统中最强的年际变率模态,其演变对全球气候及社会经济具有深远影响,实现ENSO的精确模拟与预测一直是气候科学的核心挑战。目前ENSO模拟与预测主要依赖两类模型:一... 厄尔尼诺-南方涛动(El Nino-Southern Oscillation,ENSO)作为地球气候系统中最强的年际变率模态,其演变对全球气候及社会经济具有深远影响,实现ENSO的精确模拟与预测一直是气候科学的核心挑战。目前ENSO模拟与预测主要依赖两类模型:一类是基于物理驱动的海洋-大气动力模式,它们能够显式描述与ENSO相关的海气耦合过程,但受参数化方案和分辨率等限制,在模拟和预测精度、计算效率及实时预报方面仍存在较大误差与不确定性,且在构建过程中未充分利用历史观测数据。另一类为基于人工智能(artificial intelligence,AI)的数据驱动模型,如卷积神经网络(convolutional neural network,CNN)、U-Net及物理信息神经网络(physics-informed neural network,PINN)等,该类模型善于从历史数据中挖掘海气变量间复杂的非线性时空关系,在提升预测技巧方面优势显著,但也存在物理约束缺失、泛化能力弱等问题。近年来,物理驱动与数据驱动相结合的融合建模方法逐渐成为研究热点。其融合方式主要包括两种:一是在物理模式中引入AI技术以优化物理过程的表征等;二是在AI架构中嵌入物理约束以增强过程和机制的一致性,从而在保持物理合理性的同时,提升对ENSO非线性特征的刻画能力,有效整合了两类方法的优势。本文重点回顾作者团队在利用AI技术开展海洋-大气相互作用融合建模方面的近期研究,结合具体案例阐述融合方法实现路径与应用成效,包括:基于观测数据与PINN构建了改进的上层海洋垂向扩散参数化方案;利用U-Net构建了热带太平洋海表风应力模型及与不同复杂程度的海洋动力模式的耦合,率先实现了AI大气模型与动力海洋模式的融合建模。文中进一步分析了当前融合建模面临的关键问题与挑战,展望了其在海气相互作用过程表征与模拟方面的发展前景。本研究展示了海气相互作用融合建模的新范式与创新路径,旨在为海气耦合融合建模领域未来发展提供科学依据,推动其在实际ENSO和气候模拟及预测中的更深入应用。 展开更多
关键词 海气耦合 ENSO 物理驱动模式 数据驱动模型 融合建模 示范案例
暂未订购 下载PDF
大模型驱动政府数智治理的“技术—制度—能力”协同机制研究——基于深圳市DeepSeek应用的实证分析 认领 引用 被引量：8
11
作者 龙志奇 安小米 《情报理论与实践》 CSSCI 北大核心 2026年第3期69-76,共8页
[目的/意义]在人工智能迈向通用智能的背景下,大模型驱动政府数智治理已成为治理现代化的重要议题。构建一个整合性的分析框架,系统揭示大模型赋能政府数智治理的运行逻辑,剖析实践中的核心张力,为我国政府数智治理优化提供理论指导与... [目的/意义]在人工智能迈向通用智能的背景下,大模型驱动政府数智治理已成为治理现代化的重要议题。构建一个整合性的分析框架,系统揭示大模型赋能政府数智治理的运行逻辑,剖析实践中的核心张力,为我国政府数智治理优化提供理论指导与实践范式。[方法/过程]基于“技术—制度—能力”协同分析框架,选取深圳市DeepSeek应用作为典型案例,采用深度案例研究方法,结合文献分析、政策文本分析、系统日志检视与多轮访谈,系统剖析大模型驱动政府数智治理的机制逻辑与实践路径。[结果/结论]大模型驱动治理的协同机制表现为技术赋能、制度适配与能力提升三者间的动态耦合。然而,当前实践仍面临技术黑箱与隐私风险、制度滞后与责任模糊、算力失衡与人才短缺三重张力。据此,提出构建“技术治理—制度创新—能力建设”三维协同的螺旋上升模型,以推动治理体系的可持续优化。研究结果为理解大模型时代的数智治理提供了整合性视角,填补了这个前沿领域本土化实证研究的缺口,为各级政府部署和应用大模型提供了可复制、可推广的决策参考。 展开更多
关键词 数智治理 大模型驱动 技术—制度—能力 协同机制 DeepSeek应用
暂未订购 下载PDF
航空发动机高温结构损伤检测研究与应用进展 认领 引用 被引量：1
12
作者 周运来 温生林 +4 位作者 董鑫宇 刘威 路亮 张晓明 杨强 《西安交通大学学报》 EI CAS CSCD 北大核心 2026年第6期86-96,共11页
航空发动机作为航空装备的“动力心脏”,其高温结构(如涡轮叶片、燃烧室)在高温、高压、强振动等极端环境下的损伤失效直接威胁着航空装备安全,是制约航空装备向隐身化、超音速化、长寿命化发展的核心瓶颈之一。首先,从航空发动机高温... 航空发动机作为航空装备的“动力心脏”,其高温结构(如涡轮叶片、燃烧室)在高温、高压、强振动等极端环境下的损伤失效直接威胁着航空装备安全,是制约航空装备向隐身化、超音速化、长寿命化发展的核心瓶颈之一。首先,从航空发动机高温结构损伤智能感知、检测评估、先进测试等层面出发,综述了航空发动机高温结构损伤检测领域的研究与应用进展。接着,针对航空发动机高温结构损伤检测,分别总结了基于航空发动机定期检测和基于飞参总线数据判读两方面的研究进展,介绍了新型检测方法在航空发动机高温结构中的创新应用实践,并总结了现有的采用数据驱动方式实现损伤早期识别和趋势预测的应用研究。然后,在模型驱动方面,阐述了集成物理机理模型和采用智能算法提升预测性能的可靠性,以及机器学习与深度学习算法同步处理多源数据,从而实现航空发动机高温结构损伤快速检测的研究现状。最后,梳理了相关检测技术和判读技术发展历程,并结合航空装备应用需求展望了未来发展趋势。 展开更多
关键词 航空发动机 高温结构 损伤检测 数据驱动 模型驱动 智能算法
暂未订购 下载PDF
知识-数据-模型驱动的低空动目标轨迹融合预测方法 认领 引用 被引量：1
13
作者 周同乐 刘子仪 陈谋 《自动化学报》 EI CAS CSCD 北大核心 2026年第2期296-308,共13页
针对低空环境下动目标轨迹预测问题,提出一种知识-数据-模型驱动的动目标轨迹融合预测框架.基于低空飞行器运动特征构建飞行知识混合专家模型,通过将多源传感器数据输入至各飞行知识专家模块,实现目标机动模态的精细化识别,并使用Mamba... 针对低空环境下动目标轨迹预测问题,提出一种知识-数据-模型驱动的动目标轨迹融合预测框架.基于低空飞行器运动特征构建飞行知识混合专家模型,通过将多源传感器数据输入至各飞行知识专家模块,实现目标机动模态的精细化识别,并使用Mamba模型提取时空关联特征;设计权值自适应调节机制,利用注意力机制动态融合多源感知数据,解决传感器时空异步问题;采用门控循环单元建模长期时序依赖关系,根据目标历史飞行数据生成初步预测轨迹;基于低空目标运动学方程构建物理信息神经网络,通过动态权衡数据驱动损失与物理约束损失,矫正数据驱动偏差,确保预测轨迹满足运动学约束并有效抑制多步预测误差累积.数值仿真及实验验证结果表明,所提出的知识-数据-模型驱动的动目标轨迹融合预测方法,能够有效预测低空目标飞行轨迹. 展开更多
关键词 低空环境 知识-数据-模型驱动 动目标 数据融合 轨迹预测
暂未订购 下载PDF
AI大模型驱动背景下国内外图书馆智能咨询服务效能研究 认领 引用 被引量：1
14
作者 宋玲玲 张杏辉 《农业图书情报学报》 2026年第4期99-111,共13页
[目的/意义]为探索人工智能大模型如何推动图书馆智能咨询服务发展,研究通过分析国内外实践案例,旨在为构建适应本土文化的智慧服务模式提供参考。[方法/过程]选取30所应用AI大模型的国内外图书馆,通过网络调研梳理其服务内容与技术特点... [目的/意义]为探索人工智能大模型如何推动图书馆智能咨询服务发展,研究通过分析国内外实践案例,旨在为构建适应本土文化的智慧服务模式提供参考。[方法/过程]选取30所应用AI大模型的国内外图书馆,通过网络调研梳理其服务内容与技术特点,比较技术应用、功能设计及服务模式的差异,并从服务响应、资源组织、用户改进与模式创新等维度分析其服务效能。[结果/结论]AI大模型有效提升了图书馆咨询服务的效率与知识组织能力,并在用户体验与服务创新上展现出潜力。基于案例对比,从技术融合、服务优化与本土适配等方面提出发展建议,以支持智慧图书馆建设。 展开更多
关键词 智能咨询服务 AI大模型驱动 图书馆 效能研究
暂未订购 下载PDF
A Model-Driven Deep Learning Network for Quantized GFDM Receiver 认领 引用 被引量：3
15
作者 Mengjiao Zhang Chaokai Wen +1 位作者 Shi Jin Fuchun Zheng 《Journal of Communications and Information Networks》 CSCD 2019年第3期53-59,共7页
Low-resolution analog-to-digital converter(ADC)is a promising solution to reduce hardware cost and power consumption in generalized frequency division multiplexing(GFDM)systems.The severe nonlinear distortion of ADCs ... Low-resolution analog-to-digital converter(ADC)is a promising solution to reduce hardware cost and power consumption in generalized frequency division multiplexing(GFDM)systems.The severe nonlinear distortion of ADCs and the non-orthogonality of GFDM make receiver design a great challenge.In this paper,we propose a novel model-driven receiver architecture for GFDM with low-resolution ADCs.Orthogonal approximate message passing(OAMP)framework is combined with the classical linear estimator in this work to create a robust iterative receiver for GFDM systems with low-precision ADCs.The corresponding model-driven network is organized based on the proposed novel iterative algorithm according to the procedures of the receiver.The network of OAMP can reduce the gap between the approximate algorithm and the Bayesian optimal result due to the information loss of ADCs.The signal flow of the neural network is designed by unfolding the iterative algorithms for channel estimation and data detection.Numerical results are provided to show that the proposed OAMP-based receiver algorithm outperforms traditional receivers and the model-driven network can further improve the system performance on the basis of the corresponding novel algorithm. 展开更多
关键词 deep learning GFDM low-resolution receiver model-driven message passing
模型-数据可信集成的低惯量电力系统频率预测及主动减载方法 认领 引用 被引量：1
16
作者 王翔宇 张庚午 +2 位作者 陈武晖 郭小龙 刘德福 《电工技术学报》 EI CSCD 北大核心 2026年第2期541-557,共17页
低惯量电力系统面临大量有功冲击时,虽备用容量充裕,但调节存在滞后性,而现有低频减载方案缺乏“预见性”,导致减载时刻较晚,存在过切负荷问题。该文提出一种模型-数据可信集成的低惯量电力系统暂态频率预测及主动减载方法。首先,构建... 低惯量电力系统面临大量有功冲击时,虽备用容量充裕,但调节存在滞后性,而现有低频减载方案缺乏“预见性”,导致减载时刻较晚,存在过切负荷问题。该文提出一种模型-数据可信集成的低惯量电力系统暂态频率预测及主动减载方法。首先,构建集成系统频率响应模型和双注意力一维卷积神经网络(1DCNN-DA)的暂态频率可信预测框架,通过可信度评估输出现场运行人员可以信赖的最低点频率预测结果。然后,基于暂态频率预测结果,构建主动减载控制策略,通过提前减载降低减载成本,使用预先训练好的最优减载预测器在线预测满足频率安全约束的最小减载量。最后,在IEEE 10机39母线系统和某省大电网上验证了所提模型-数据可信集成的暂态频率预测和主动减载策略的性能。 展开更多
关键词 低频减载 频率预测 可信度评估 模型-数据驱动 低惯量电力系统
暂未订购 下载PDF
SCADE平台下机载综合处理设备二余度切换逻辑设计方法 认领 引用 被引量：1
17
作者 郭玉洁 李昊昱 +2 位作者 马浩 周斌 汪利建 《西安邮电大学学报》 2026年第3期119-128,共10页
为满足机载综合处理设备对高安全性、高可靠性及低成本的需求,提出一种基于模型驱动开发的机载航电综合处理设备整机二余度-模块多余度切换逻辑设计方法。从二余度系统架构与安全性需求出发,基于SCADE工具链设计了涵盖健康状态监控、切... 为满足机载综合处理设备对高安全性、高可靠性及低成本的需求,提出一种基于模型驱动开发的机载航电综合处理设备整机二余度-模块多余度切换逻辑设计方法。从二余度系统架构与安全性需求出发,基于SCADE工具链设计了涵盖健康状态监控、切换逻辑及数据输出的完整逻辑模型,并利用SCADE Design Verifier对模型进行形式化验证,证明其满足无死锁、无不可达状态及主从互斥等关键安全属性。通过模型驱动开发可减少约40%的编码与单元测试工作量,提升了开发与DO-178C认证效率,所设计的切换逻辑有效提升了系统的正确性与可靠性,为同类低成本高安全系统开发提供了可复用的工程实践参考。 展开更多
关键词 机载综合处理设备 二余度架构 切换逻辑 模型驱动开发 安全性设计
暂未订购 下载PDF
基于极限场景法的燃气掺氢综合能源系统两阶段低碳经济调度 认领 引用 被引量：3
18
作者 胡俊杰 吴俊 刘雪涛 《电力系统自动化》 EI CSCD 北大核心 2026年第7期118-128,共11页
氢能具有能量密度高、清洁性高的特点,将其引入综合能源系统对于促进能源结构转型具有重要意义。为充分发挥氢能在降低碳排放和促进系统经济运行方面的优势,提出了基于极限场景法的燃气掺氢综合能源系统两阶段低碳经济调度模型。首先,... 氢能具有能量密度高、清洁性高的特点,将其引入综合能源系统对于促进能源结构转型具有重要意义。为充分发挥氢能在降低碳排放和促进系统经济运行方面的优势,提出了基于极限场景法的燃气掺氢综合能源系统两阶段低碳经济调度模型。首先,分析电转气(P2G)与气转电(G2P)两个过程的能源转化形式与设备的耦合特性,建立了电解槽变效率动态运行模型以及细致考虑能量转换过程的掺氢燃气轮机精细化混合燃烧出力模型。其次,结合极限场景法构建数据驱动的风光出力不确定集,提出日前-日内两阶段综合能源系统低碳经济调度模型。其中,日前阶段的计划方案最小化机组成本、备用容量成本、购能成本以及弃风弃光成本;日内阶段则以系统的各设备运行成本、碳交易成本以及调整成本最低为目标对日前计划进行实时修正,并采用滚动优化的方式求解。最后,通过仿真算例证明了所提模型在促进系统低碳经济运行与改进模型求解速率上具有积极作用。 展开更多
关键词 综合能源系统 氢能 燃气掺氢 低碳经济调度 能源转化 极限场景法 精细化建模 数据驱动
暂未订购 下载PDF
基于数据-模型混合驱动方法的多类型移动应急资源优化调度策略 认领 引用 被引量：2
19
作者 江昌旭 周龙灿 +3 位作者 庄鹏威 许浩 林俊杰 邵振国 《电网技术》 EI CSCD 北大核心 2026年第2期858-868,I0136-I0146,共11页
为有效提升配电网韧性,提出了一种基于数据-模型混合驱动的多类型移动应急资源优化调度方法。首先,考虑到交通道路状态动态变化对移动储能车(mobile energy storage system,MESS)和应急抢修队(repair crew,RC)策略的影响,构建了以电力-... 为有效提升配电网韧性,提出了一种基于数据-模型混合驱动的多类型移动应急资源优化调度方法。首先,考虑到交通道路状态动态变化对移动储能车(mobile energy storage system,MESS)和应急抢修队(repair crew,RC)策略的影响,构建了以电力-交通耦合网总损失成本最小为目标的多类型移动应急资源随机优化调度模型。然后,为了实时准确地求解MESS和RC最优路由和调度策略,提出了一种数据-模型混合驱动方法对所构建的复杂非线性随机优化模型进行求解。在数据驱动部分提出一种图注意力网络多智能体强化学习算法,以求解考虑交通网道路修复时间和移动应急资源邻接关系动态变化等不确定因素的MESS和RC最优路由策略。所提算法有效结合多种改进策略和优先经验回放策略以提高算法的采样效率和训练效果。在模型驱动部分采用二阶锥松弛和大M法将多类型移动应急资源优化调度问题构建为混合整数二阶锥规划模型以求解可再生能源出力和配电网负荷变化影响下MESS和RC最优调度策略。最后,在2个不同规模的电力-交通耦合网中验证所提方法的有效性、泛化能力和可拓展能力。 展开更多
关键词 移动应急资源 配电网韧性 路由和调度策略 数据-模型混合驱动方法 图注意力网络多智能体强化学习
暂未订购 下载PDF
A survey of model-driven techniques and tools for cyber-physical systems 认领 引用 被引量：1
20
作者 Bo LIU Yuan-rui ZHANG +3 位作者 Xue-lian CAO Yu LIU Bin GU Tie-xin WANG 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2020年第11期1567-1590,共24页
Cyber-physical systems(CPSs)have emerged as a potential enabling technology to handle the challenges in social and economic sustainable development.Since it was proposed in 2006,intensive research has been conducted,s... Cyber-physical systems(CPSs)have emerged as a potential enabling technology to handle the challenges in social and economic sustainable development.Since it was proposed in 2006,intensive research has been conducted,showing that the construction of a CPS is a hard and complex engineering process due to the nature of integrating a large number of heterogeneous subsystems.Among other approaches to dealing with the complex design issues,model-driven design of CPSs has shown its advantages.In this review paper,we present a survey of research on model-driven development of CPSs.We are concerned mainly with the widely used methods,techniques,and tools,and discuss how these are applied to CPSs.We also present comparative analyses on the surveyed techniques and tools from various perspectives,including their modeling languages,functionalities,and the challenges which they address in CPS design.With our understanding of the surveyed methods,we believe that model-driven approaches are an inevitable choice in building CPSs and further research effort is needed in the development of model-driven theories,techniques,and tools.We also argue that a unified modeling platform is needed.Such a platform would benefit research in the academic community and practical development in industry,and improve the collaboration between these two communities. 展开更多
关键词 Cyber-physical systems Model-driven approach System modeling Software engineering
暂未订购 下载PDF
已选0条
引用分析
参考文献
引证文献
 统计分析
检索结果
已选文献
上一页 1 2 … 167 下一页 到第 页
在线咨询 使用帮助 返回顶部 意见反馈