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A hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction

Energy and AI 2024年第4期18卷 368-379页

作者： Weipeng Li Yuting Chong Xin Guo Jun Liu School of Automation and Information Engineering Xi’an University of TechnologyNo.5 Jinhua South RoadXi’an710048ShaanxiChina Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing No.5 Jinhua South RoadXi’an710048ShaanxiChina

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power *** data-driven forecasting methods are regarded as an effective ***,the inherent randomness and nonlinearity of wind power systems,along with the abundance of redundant information in measurement data,present challenges to forecasting *** integration of precise and efficient techniques for data feature decomposition and extraction is essential in conjunction with advanced driven data-forecasting *** on the seasonal variation characteristics of wind energy,a hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction is *** effectiveness and superiority of the proposed method in predictive accuracy are demonstrated through comprehensive multi-model experiment comparisons.

关键词： Wind power prediction Data-driven Hybrid model Seasonal feature decomposition Gated recurrent networks Attention mechanism

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Development of a novel critical nitrogen concentration-cumulative transpiration curve for optimizing nitrogen management under varying irrigation conditions in winter wheat

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The Crop Journal 2024年第4期12卷 1242-1251页

作者： Tianyang Ye Yu Zhang Jingyan Xuan Xintian Wang Yang Li Junhao Xu Liujun Xiao Leilei Liu Liang Tang Weixing Cao Bing Liu Yan Zhu National Engineering and Technology Center for Information Agriculture Engineering Research Center of Smart AgricultureMinistry of EducationKey Laboratory for Crop System Analysis and Decision MakingMinistry of AgricultureJiangsu Key Laboratory for Information AgricultureJiangsu Collaborative Innovation Center for Modern Crop ProductionNanjing Agricultural UniversityNanjing 210095JiangsuChina Institute of Remote Sensing and Digital Agriculture Sichuan Academy of Agricultural SciencesChengdu 610066SichuanChina

Accurate nitrogen(N)nutrition diagnosis is essential for improving N use efficiency in crop *** widely used critical N(Nc)dilution curve traditionally depends solely on agronomic variables,neglecting crop water *** three-year field experiments with winter wheat,encompassing two irrigation levels(rainfed and irrigation at jointing and anthesis)and three N levels(0,180,and 270 kg ha1),this study aims to establish a novel approach for determining the Nc dilution curve based on crop cumulative transpiration(T),providing a comprehensive analysis of the interaction between N and water *** Nc curves derived from both crop dry matter(DM)and T demonstrated N concentration dilution under different conditions with different *** equation Nc=6.43T0.24 established a consistent relationship across varying irrigation *** test results indicated that the nitrogen nutrition index(NNI),calculated from this curve,effectively identifies and quantifies the two sources of N deficiency:insufficient N supply in the soil and insufficient soil water concentration leading to decreased N availability for root ***,the NNI calculated from the Nc-DM and Nc-T curves exhibited a strong negative correlation with accumulated N deficit(Nand)and a positive correlation with relative grain yield(RGY).The NNI derived from the Nc-T curve outperformed the NNI derived from the Nc-DM curve concerning its relationship with Nand and RGY,as indicated by larger R2 values and smaller *** novel Nc curve based on T serves as an effective diagnostic tool for assessing winter wheat N status,predicting grain yield,and optimizing N fertilizer management across varying irrigation *** findings would provide new insights and methods to improve the simulations of water-N interaction relationship in crop growth models.

关键词： Crop dry matter Crop cumulative transpiration Bayesian statistical model Critical nitrogen dilution curve Nitrogen nutrition index

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Analysis of the impact of long-term service of inverter devices on electromagnetic compatibility 2

Analysis of the impact of long-term service of inverter devi...

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2nd China Power Supply Society Electromagnetic Compatibility Conference, CPEMC 2024

作者： Zhang, Ruiheng Pei, Xuejun Meng, Jin Fan, Hongming Zhou, Peng Yuan, Yuzhang Power Electronics and Energy Management Key Laboratory Ministry of Education of China Huazhong University of Science and Technology Wuhan China National Key Laboratory of Science and Technology on Vessel Integrated Power System Naval University of Engineering Wuhan China

ISBN: (纸本)9798331509552

Taking the IGBT power module of the inverter device as the research object, finite element analysis technology was used to explore the influence of long-term service on the thermal characteristics and stress-strain of the IGBT module. At the same time, the influence of service aging on the electromagnetic compatibility performance of the device was studied, and the finite element simulation results were verified through accelerated aging experiments. The results showed that during the long-term operation of the IGBT module, due to the different thermal expansion coefficients of its materials, strain differences were found, ultimately leading to an increase in its ground capacitance, resulting in an increase in the amplitude of the common mode conducted noise of the device by 3dBμA in the frequency band after 20MHz. This study will provide theoretical guidance for the electromagnetic compatibility design of inverter devices for long-term service. ©2024 IEEE.

关键词： Insulated gate bipolar transistors (IGBT)

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Improving atmospheric pressure vertical correction model using Gaussian function

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Geodesy and Geodynamics 2025年第1期16卷 67-74页

作者： Baoshuang Zhang Junyu Li Lilong Liu Yibin Yao Liangke Huang Chao Ren Hongchang He Tengxu Zhang Yuxin Wang College of Geomatics and Geoinformation Guilin University of TechnologyGuilin 541004China Guangxi Key Laboratory of Spatial Information and Geomatics Guilin 541004China School of Geodesy and Geomatics Wuhan UniversityWuhan 430079China Schoolof Resources and Environmental Science and Engineering Hubei University of Science and TechnologyXianning 437100China

The Zenith Hydrostatic Delay(ZHD)is essential for high-precision Global Navigation Satellite system(GNSS)and Very Long Baseline Interferometry(VLBI)data *** estimation of ZHD relies on in situ atmospheric pressure,which is primarily variable in the vertical *** atmospheric pressure is either site-specific or has limited spatial coverage,necessitating vertical corrections for broader *** study introduces a model that uses a Gaussian function for the vertical correction of atmospheric pressure when in situ meteorological observations are *** with the fifth-generation European Centre for Medium-Range Weather Forecasts reanalysis(ERA5)reveals an average Bias and RMS for the new model of 0.31 h Pa and 2.96 h Pa,*** corresponds to improvements of 37.5%and 80.3%in terms of RMS compared to two commonly used models(T0and Tvmodels)that require in situ meteorological observations,*** validation with radiosonde data shows an average Bias and RMS of 1.85 h Pa and 4.87 h Pa,corresponding to the improvement of 42.8%and 71.1%in RMS compared with T0and Tv models,*** accuracies are sufficient for calculating ZHD to an accuracy of 1 mm by performing atmospheric pressure vertical *** new model can correct atmospheric pressure from meteorological stations or numerical weather forecasts to different heights of the troposphere.

关键词： Atmospheric pressure Vertical correction Zenith hydrostatic delay(ZHD) Gauss function ERA5

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Microstructure and Mechanical Properties of B-Bearing Austenitic Stainless Steel Fabricated by Laser Metal Deposition In-Situ Alloying

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Acta Metallurgica Sinica(English Letters) 2022年第3期35卷 453-465页

作者： Sheng Huang Xiaoyu Zhang Dichen Li Qingyu Li State Key Laboratory for Manufacturing Systems Engineering Xian Jiaotong UniversityXian 710049China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of ChinaChengdu 610213China

In the field repair application of laser metal deposition(LMD),the kinds of powder materials that can be used are limited,while the equipment components are made of various *** many components have to be repaired with heterogeneous ***,it is difficult to match the mechanical properties between the repaired layer and the substrate due to the diff erent *** on the high flexibility of raw materials and processes in LMD,an in-situ alloying method is proposed herein for tailoring the mechanical properties of LMDed *** diff erent mixing ratios of Fe314 and 316 L stainless steel powders as the control parameter,the microstructure and mechanical properties of B-bearing austenitic stainless steel fabricated by LMD in-situ alloying with diff erent proportions of Fe314 and 316 L particles were *** the increase in the concentration of 316 L steel,the volume fraction of the eutectic phase in deposited B-bearing austenitic stainless steel reduced,the size of the austenite dendrite increased,the yield strength and ultimate tensile strength decreased monotonically,while the elongation increased ***,the fracture mode changed from quasi-cleavage fracture to ductile *** adding 316 L powder,the yield strength,tensile strength,and elongation of deposited B-bearing austenitic stainless steel could be adjusted within the range of 712 MPa–257 MPa,1325 MPa–509 MPa,and 8.7%–59.3%,***,this work provides a new method and idea for solving the performance matching problem of equipment components in the field repair.

关键词： Additive manufacturing Laser metal deposition In-situ alloying B-bearing austenitic stainless steel Mechanical properties

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Measurement-based Path Loss Prediction and Analysis in Water Scenarios

Measurement-based Path Loss Prediction and Analysis in Water...

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2024 IEEE International Conference on Computational Electromagnetics, ICCEM 2024

作者： Li, Hanpeng Chen, Xiaomin Li, Hangang Ma, Jian Ye, Xuchao Song, Lixin Zhang, Taotao Zhong, Weizhi Zhu, Qiuming Nanjing University of Aeronautics and Astronautics College of Electronic and Information Engineering Nanjing211106 China Aviation Key Laboratory of Science and Technology On Aero Electromechanical System Integration Nanjing211106 China State Key Lab. of Complex Electromagnetic Environment Effects On Electronics and Information System Luoyang471003 China

ISBN: (纸本)9798350383317

Unmanned aerial vehicles (UAVs) have enabled the unmanned management of water areas. Path loss (PL) serves as a critical factor that affects the UAV communication quality. In this work, a PL model for UAV channel in water scenarios is proposed, aiming to explore the multidimensional relationship between transceiver distance, carrier frequency, UAV height, and PL by constructing an Artificial Neural Network (ANN). Moreover, channel measurements are conducted in a river area, and the obtained data are analyzed using the proposed ANN model as well as the close-in (CI) model. The analysis results demonstrates that the PL increases initially and then declines as the UAV height increases. The proposed ANN model has higher prediction accuracy than the classic empirical model, and can achieve precise prediction of the PL in water scenarios. © 2024 IEEE.

关键词： Neural networks

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Deep learning enhanced quantum holography with undetected photons

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PhotoniX 2024年第1期5卷 54-66页

作者： Weiru Fan Gewei Qian Yutong Wang Chen-Ran Xu Ziyang Chen Xun Liu Wei Li Xu Liu Feng Liu Xingqi Xu Da-Wei Wang Vladislav V.Yakovlev Zhejiang Province Key Laboratory of Quantum Technology and Device School of Physicsand State Key Laboratory for Extreme Photonics and InstrumentationZhejiang UniversityHangzhou 310027Zhejiang ProvinceChina College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310027Zhejiang ProvinceChina College of Information Science and Engineering Fujian Key Laboratory of Light Propagation and TransformationHuaqiao UniversityXiamen 361021Fujian ProvinceChina Beijing Institute of Space and Electricity China Academy of Space TechnologyBeijing 100094China College of Optical Science and Engineering Zhejiang UniversityHangzhou 310027Zhejiang ProvinceChina Hefei National Laboratory Hefei 230088Anhui provinceChina Department of Biomedical Engineering Texas A&M UniversityCollege Station 77843TXUSA

Holography is an essential technique of generating three-dimensional ***,quantum holography with undetected photons(QHUP)has emerged as a groundbreaking method capable of capturing complex amplitude *** its potential,the practical application of QHUP has been limited by susceptibility to phase disturbances,low interference visibility,and limited spatial *** learning,recognized for its ability in processing complex data,holds significant promise in addressing these *** this report,we present an ample advancement in QHUP achieved by harnessing the power of deep learning to extract images from single-shot holograms,resulting in vastly reduced noise and distortion,alongside a notable enhancement in spatial *** proposed and demonstrated deep learning QHUP(DL-QHUP)methodology offers a transformative solution by delivering high-speed imaging,improved spatial resolution,and superior noise resilience,making it suitable for diverse applications across an array of research fields stretching from biomedical imaging to remote ***-QHUP signifies a crucial leap forward in the realm of holography,demonstrating its immense potential to revolutionize imaging capabilities and pave the way for advancements in various scientific *** integration of DL-QHUP promises to unlock new possibilities in imaging applications,transcending existing limitations and offering unparalleled performance in challenging environments.

关键词： Quantum holography Computational imaging Undetected photons Deep learning

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Incorporating metapath interaction on heterogeneous information network for social recommendation

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Frontiers of Computer science 2024年第1期18卷 33-48页

作者： Yanbin JIANG Huifang MA Xiaohui ZHANG Zhixin LI Liang CHANG College of Computer Science and Engineering Northwest Normal UniversityLanzhou 730070China Guangxi Key Lab of Multi-source Information Mining and Security Guangxi Normal UniversityGuilin 541001China Guangxi Key Laboratory of Trusted Software Guilin University of Electronic TechnologyGuilin 541004China

Heterogeneous information network(HIN)has recently been widely adopted to describe complex graph structure in recommendation systems,proving its effectiveness in modeling complex graph *** existing HIN-based recommendation studies have achieved great success by performing message propagation between connected nodes on the defined metapaths,they have the following major *** works mainly convert heterogeneous graphs into homogeneous graphs via defining metapaths,which are not expressive enough to capture more complicated dependency relationships involved on the ***,the heterogeneous information is more likely to be provided by item attributes while social relations between users are not adequately *** tackle these limitations,we propose a novel social recommendation model MPISR,which models MetaPath Interaction for Social Recommendation on heterogeneous information ***,our model first learns the initial node representation through a pretraining module,and then identifies potential social friends and item relations based on their similarity to construct a unified *** then develop the two-way encoder module with similarity encoder and instance encoder to capture the similarity collaborative signals and relational dependency on different *** experiments on five real datasets demonstrate the effectiveness of our method.

关键词： heterogeneous information network social reco-mmender system metapath interaction attention mechanism

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Optimization of optical convolution kernel of optoelectronic hybrid convolution neural network

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Optoelectronics Letters 2022年第3期18卷 181-186页

作者： XU Xiaofeng ZHU Lianqing ZHUANG Wei ZHANG Dongliang LU Lidan YUAN Pei School of Electro-Optical Engineering Changchun University of Science and TechnologyJilin 130022China Key Laboratory of the Ministry of Education for Optoelectronic Measurement Technology and Instrument Beijing Information Science and Technology UniversityBeijing 100192China Beijing Laboratory of Optical Fiber Sensing and System Beijing Information Science and Technology UniversityBeijing 100016China

To enhance the optical computation’s utilization efficiency, we develop an optimization method for optical convolution kernel in the optoelectronic hybrid convolution neural network(OHCNN). To comply with the actual calculation process, the convolution kernel is expanded from single-channel to two-channel, containing positive and negative weights. The Fashion-MNIST dataset is used to test the network architecture’s accuracy, and the accuracy is improved by 7.5% with the optimized optical convolution kernel. The energy efficiency ratio(EER) of two-channel network is 46.7% higher than that of the single-channel network, and it is 2.53 times of that of traditional electronic products.

关键词： convolution kernel weights

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Realizing Plain Optimization of the Thermoelectric Properties in BiCuSeO Oxide via Self-Substitution-Induced Lattice Dislocations

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Research 2023年第4期2023卷 755-764页

作者： Rui Xu Zhiwei Chen Qizhu Li Xiaoyu Yang Han Wan Mengruizhe Kong Wei Bai Nengyuan Zhu Ruohan Wang Jiming Song Zhou Li Chong Xiao Binghui Ge Information Materials and Intelligent Sensing Laboratory of Anhui Province Key Laboratory of Structure and Functional Regulation of Hybrid Materials of Ministry of EducationInstitutes of Physical Science and Information Technology and School of Materials Science and EngineeringAnhui UniversityHefei 230601China Institute of Energy Hefei Comprehensive National Science CenterHefei 230031China School of Materials Science and Engineering Tongji UniversityShanghai 201804China Hefei National Laboratory for Physical Sciences at the Microscale CAS Center for Excellence in NanoscienceUniversity of Science and Technology of ChinaHefei 230026China

Seeking new strategies to tune the intrinsic defect and optimize the thermoelectric performance via no or less use of external doped elements(i.e.,plain optimization)is an important method to realize the sustainable development of thermoelectric ***,creating dislocation defects in oxide systems is quite challenging because the rigid and stiff ionic/covalent bonds can hardly tolerate the large strain energy associated with ***,taking BiCuSe_(O) oxide as an example,the present work reports a successful construction of dense lattice dislocations in BiCuSe_(O) by self-doping of Se at the O site(i.e.,Se_(O) self-substitution),and achieves plain optimization of the thermoelectric properties with only external Pb *** to the self-substitution-induced large lattice distortion and the potential reinforcement effect by Pb doping,high-density(about 3.0×10^(14 )m^(−2))dislocations form in the grains,which enhances the scattering strength of mid-frequency phonon and results in a substantial low lattice thermal conductivity of 0.38 W m^(−1) K^(−1) at 823 K in Pb-doped BiCuSe_(O).Meanwhile,PbBi doping and Cu vacancy markedly improve the electrical conductivity while maintaining a competitively high Seebeck coefficient,thereby contributing to a highest power factor of 942μW m^(−1) K^(−2).Finally,a remarkably enhanced zT value of 1.32 is obtained at 823 K in Bi_(0.94)Pb_(0.06)Cu_(0.97)Se_(1.05)O_(0.95) with almost compositional *** high-density dislocation structure reported in this work will also provide a good inspiration for the design and construction of dislocations in other oxide systems.

关键词： plain doping dislocation

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