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电力建设 2001年第6期22卷 57-59,64页

作者：周林雷绍兰四川大学电力工程系成都市610065 重庆大学电气工程学院重庆市400044

静止无功补偿器 (SVC)是灵活交流输电系统中的一个重要组成部分 ,其结构简单并易于实现 ,因此被广泛应用于电力系统中。应用H∞鲁棒控制设计原理及混合灵敏度分析方法设计的SVC的H∞鲁棒控制器 ,通过仿真可以看出 ,它不仅能提供电力系... 详细信息

静止无功补偿器 (SVC)是灵活交流输电系统中的一个重要组成部分 ,其结构简单并易于实现 ,因此被广泛应用于电力系统中。应用H∞鲁棒控制设计原理及混合灵敏度分析方法设计的SVC的H∞鲁棒控制器 ,通过仿真可以看出 ,它不仅能提供电力系统正阻尼。

关键词：电力系统静止无功补偿器 H∞鲁棒控制器电压稳定性

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一种多变量时间序列的短期负荷预测方法研究

电工技术学报 2005年第4期20卷 62-67页

作者：雷绍兰孙才新周湶邓群刘凡重庆大学高电压与电工新技术教育部重点实验室

针对短期负荷影响因素多的特点提出了电力短期负荷的多变量时间序列预测方法,并根据单变量时间序列的延时重构对由历史负荷序列及其相关因素序列所构成的多变量时间序列进行了相空间重构,采用互信息法计算了各子序列的延迟时间,各子序... 详细信息

针对短期负荷影响因素多的特点提出了电力短期负荷的多变量时间序列预测方法,并根据单变量时间序列的延时重构对由历史负荷序列及其相关因素序列所构成的多变量时间序列进行了相空间重构,采用互信息法计算了各子序列的延迟时间,各子序列的嵌入维数则运用平均一步绝对误差和最小一步绝对误差进行选取,然后通过RBF神经网络的非线性映射能力进行电力短期负荷预测。研究结果表明多变量时间序列的预测效果相对于单变量序列有较大提高。

关键词：短期负荷预测混沌多变量时间序列径向基函数神经网络

基于粗糙集数据挖掘的配电网小区空间负荷预测方法研究

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电工技术学报 2005年第5期20卷 98-102页

作者：程其云张晓星周湶雷绍兰孙才新重庆大学高电压与电工新技术教育部重点实验室重庆400044 贵州省电力公司贵阳市南供电局贵阳550002

提出了一种新颖的配电网空间负荷预测方法,采用粗糙集(RS)数据挖掘方法对可能影响小区用地决策的相关属性进行约简,去除冗余属性,克服了以往方法受人为因素影响较大的弱点,得出决定小区用地类型的决策规则,从而得到每个小区适于发展各... 详细信息

提出了一种新颖的配电网空间负荷预测方法,采用粗糙集(RS)数据挖掘方法对可能影响小区用地决策的相关属性进行约简,去除冗余属性,克服了以往方法受人为因素影响较大的弱点,得出决定小区用地类型的决策规则,从而得到每个小区适于发展各类负荷的程度,再运用全局最优的土地分配算法来计算各小区内各类负荷的增长,克服了仿真法不能得到整个土地最优分配方案决策的弱点。最后用实例说明了该方法的有效性。

关键词：空间负荷预测粗糙集数据挖掘分配算法

Metarelation2vec:A Metapath-Free Scalable Representation Learning Model for Heterogeneous Networks

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Tsinghua Science and Technology 2024年第2期29卷 553-575页

作者： lei Chen Yuan Li Yong lei Xingye Deng School of Information and Electrical Engineering Hunan University of Science and TechnologyXiangtan 411201China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China

Metapaths with specific complex semantics are critical to learning diverse semantic and structural information of heterogeneous networks(HNs)for most of the existing representation learning ***,any metapaths consisting of multiple,simple metarelations must be driven by domain *** sensitive,expensive,and limited metapaths severely reduce the flexibility and scalability of the existing models.A metapath-free,scalable representation learning model,called Metarelation2vec,is proposed for HNs with biased joint learning of all metarelations in a bid to address this ***,a metarelation-aware,biased walk strategy is first designed to obtain better training samples by using autogenerating cooperation probabilities for all metarelations rather than using expert-given ***,grouped nodes by the type,a common and shallow skip-gram model is used to separately learn structural proximity for each node ***,grouped links by the type,a novel and shallow model is used to separately learn the semantic proximity for each link ***,supervised by the cooperation probabilities of all meta-words,the biased training samples are thrown into the shallow models to jointly learn the structural and semantic information in the HNs,ensuring the accuracy and scalability of the *** experimental results on three tasks and four open datasets demonstrate the advantages of our proposed model.

关键词： metarelation random walk heterogeneous network metapath representation learning

Two-Stage Online Debiased Lasso Estimation and Inference for High-Dimensional Quantile Regression with Streaming Data

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Journal of Systems Science & Complexity 2024年第3期37卷 1251-1270页

作者： PENG Yanjin WANG lei School of Statistics and Data Science KLMDASRLEBPS and LPMCNankai UniversityTianjin 300071China

In this paper,the authors propose a two-stage online debiased lasso estimation and statistical inference method for high-dimensional quantile regression(QR)models in the presence of streaming *** the first stage,the authors modify the QR score function based on kernel smoothing and obtain the online lasso smoothed QR estimator through iterative *** estimation process only involves the current data batch and specific historical summary statistics,which perfectly accommodates to the special structure of streaming *** the second stage,an online debiasing procedure is carried out to eliminate biases caused by the lasso penalty as well as the accumulative approximation error so that the asymptotic normality of the resulting estimator can be *** authors conduct extensive numerical experiments to evaluate the performance of the proposed *** experiments demonstrate the effectiveness of the proposed method and support the theoretical *** application to the Beijing PM2.5 Dataset is also presented.

关键词： Adaptive tuning asymptotic normality debiased lasso online updating quantile regres-sion

Structural energy storage composites based on modified carbon fiber electrode with metal-organic frame enhancing layered double hydroxide

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Nano Research 2024年第3期17卷 1552-1563页

作者： Jinrui Ye Zhongbao Wang Qin lei lei Sun Jinfeng Gu School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Tangshan Research Institute Beijing Institute of TechnologyTangshan 063000China School of Materials Science and Engineering Shenyang Jianzhu UniversityShenyang 110168China Department of Stomatology PLA Strategic Support Force Characteristic Medical CenterBeijing 100101China Beijing Electromechanical Engineering Research Institute Beijing 100074China

Structural energy storage composites present advantages in simultaneously achieving structural strength and electrochemical *** of carbon fiber electrodes and resin structural electrolytes in energy storage composite poses challenges in maintaining good mechanical and electrochemical properties at reasonable cost and ***,we report a simple method to fabricate structural supercapacitor using carbon fiber electrodes(modified by Ni-layered double hydroxide(Ni-LDH)and in-situ growth of Co-metal-organic framework(Co-MOF)in a two-step process denoted as Co-MOF/Ni-LDH@CF)and bicontinuous-phase epoxy resin-based structural ***-MOF/Ni-LDH@CF as electrode material exhibits improved specific capacity(42.45 F·g^(-1))and cycle performance(93.3%capacity retention after 1000 cycles)in a three-electrode *** bicontinuous-phase epoxy resin-based structural electrolyte exhibits an ionic conductivity of 3.27×10^(-4) S·cm^(-1).The fabricated Co-MOF/Ni-LDH@CF/SPE-50 structural supercapacitor has an energy density of 3.21 Wh·kg^(-1) at a power density of 42.25 W·kg^(-1),whilst maintaining tensile strength and modulus of 334.6 MPa and 25.2 *** results show practical potential of employing modified commercial carbon fiber electrodes and epoxy resin-based structural electrolytes in structural energy storage applications.

关键词： carbon fiber electrode structural electrolyte structural energy storage composites supercapacitor

DCVAE-adv:A Universal Adversarial Example Generation Method for White and Black Box Attacks

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Tsinghua Science and Technology 2024年第2期29卷 430-446页

作者： lei Xu Junhai Zhai College of Mathematics and Information Science Hebei UniversityBaoding 071002China

Deep neural network(DNN)has strong representation learning ability,but it is vulnerable and easy to be fooled by adversarial *** order to handle the vulnerability of DNN,many methods have been *** general idea of existing methods is to reduce the chance of DNN models being fooled by observing some designed adversarial examples,which are generated by adding perturbations to the original *** this paper,we propose a novel adversarial example generation method,called *** from the existing methods,DCVAE-adv constructs adversarial examples by mixing both explicit and implicit perturbations without using original ***,the proposed method can be applied to both white box and black box *** addition,in the inference stage,the adversarial examples can be generated without loading the original images into memory,which greatly reduces the memory *** compared DCVAE-adv with three most advanced adversarial attack algorithms:FGSM,AdvGAN,and AdvGAN++.The experimental results demonstrate that DCVAE-adv is superior to these state-of-the-art methods in terms of attack success rate and transfer ability for targeted *** code is available at https://***/xzforeverlove/DCVAE-adv.

关键词： deep neural network adversarial examples white box attack black box attack robustness

Dynamic multifunctional metasurfaces:an inverse design deep learning approach

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Photonics Research 2024年第1期12卷 123-133页

作者： ZHI-DAN lei YI-DUO XU CHENG lei YAN ZHAO DU WANG The Institute of Technological Sciences Wuhan UniversityWuhan 430072China College of Materials Science and Engineering Sichuan UniversityChengdu 610065China

Optical metasurfaces(OMs)offer unprecedented control over electromagnetic waves,enabling advanced optical *** emergence of deep learning has opened new avenues for designing ***,existing deep learning methods for OMs primarily focus on forward design,which limits their design capabilities,lacks global optimization,and relies on prior ***,most OMs are static,with fixed functionalities once *** overcome these limitations,we propose an inverse design deep learning method for dynamic *** approach comprises a forward prediction network and an inverse retrieval *** forward prediction network establishes a mapping between meta-unit structure parameters and reflectance *** inverse retrieval network generates a library of meta-unit structure parameters based on target requirements,enabling end-to-end design of *** incorporating the dynamic tunability of the phase change material Sb2Te3with inverse design deep learning,we achieve the design and verification of dynamic multifunctional *** results demonstrate OMs with multiple information channels and encryption capabilities that can realize multiple physical field optical modulation *** Sb2Te3is in the amorphous state,near-field nano-printing based on meta-unit amplitude modulation is achieved for X-polarized incident light,while holographic imaging based on meta-unit phase modulation is realized for circularly polarized *** the crystalline state,the encrypted information remains secure even with the correct polarization input,achieving double *** research points towards ultra-compact,high-capacity,and highly secure information storage approaches.

关键词： polarization inverse approach

Extended finite element-based cohesive zone method for modeling simultaneous hydraulic fracture height growth in layered reservoirs

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Journal of Rock Mechanics and Geotechnical Engineering 2024年第8期16卷 2960-2981页

作者： lei Yang Baixi Chen Hopkins Extreme Materials Institute Johns Hopkins UniversityBaltimoreMD21218USA School of Civil Engineering The University of SydneyNSW2006Australia Department of Mechanical Engineering University of Wisconsin-Madison1513 University AvenueMadisonWI53706-1572USA Department of Civil and Environmental Engineering The Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina

In this study,a fully coupled hydromechanical model within the extended finite element method(XFEM)-based cohesive zone method(CZM)is employed to investigate the simultaneous height growth behavior of multi-cluster hydraulic fractures in layered porous reservoirs with modulus *** coupled hydromechanical model is first verified against an analytical solution and a laboratory ***,the fracture geometry(***,aperture,and area)and fluid pressure evolutions of multiple hydraulic fractures placed in a porous reservoir interbedded with alternating stiff and soft layers are investigated using the *** stress and pore pressure distributions within the layered reservoir during fluid injection are also *** simulation results reveal that stress umbrellas are easily to form among multiple hydraulic fractures’tips when propagating in soft layers,which impedes the simultaneous height *** is also observed that the impediment effect of soft layer is much more significant in the fractures suppressed by the preferential growth of adjoining *** that,the combined effect of in situ stress ratio and fracturing spacing on the multi-fracture height growth is presented,and the results elucidate the influence of in situ stress ratio on the height growth behavior depending on the fracture ***,it is found that the inclusion of soft layers changes the aperture distribution of outmost and interior hydraulic *** results obtained from this study may provide some insights on the understanding of hydraulic fracture height containment observed in filed.

关键词： Hydraulic fracturing Layered reservoir Simultaneous height growth In situ stress Fracture spacing Extended finite element method(XFEM) Cohesive zone method(CZM)