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Price prediction of power transformer materials based on CEEMD and GRU

Global Energy Interconnection 2024年第2期7卷 217-227页

作者： Yan Huang Yufeng Hu Liangzheng Wu Shangyong Wen Zhengdong Wan Energy Development research Institute China Southern Power GridGuangzhou 510623P.R.China China southern Power Grid Guangzhou 510623P.R.China

The rapid growth of the Chinese economy has fueled the expansion of power grids.Power transformers are key equipment in power grid projects,and their price changes have a significant impact on cost control.However,the prices of power transformer materials manifest as nonsmooth and nonlinear sequences.Hence,estimating the acquisition costs of power grid projects is difficult,hindering the normal operation of power engineering construction.To more accurately predict the price of power transformer materials,this study proposes a method based on complementary ensemble empirical mode decomposition(CEEMD)and gated recurrent unit(GRU)network.First,the CEEMD decomposed the price series into multiple intrinsic mode functions(IMFs).Multiple IMFs were clustered to obtain several aggregated sequences based on the sample entropy of each IMF.Then,an empirical wavelet transform(EWT)was applied to the aggregation sequence with a large sample entropy,and the multiple subsequences obtained from the decomposition were predicted by the GRU model.The GRU model was used to directly predict the aggregation sequences with a small sample entropy.In this study,we used authentic historical pricing data for power transformer materials to validate the proposed approach.The empirical findings demonstrated the efficacy of our method across both datasets,with mean absolute percentage errors(MAPEs)of less than 1%and 3%.This approach holds a significant reference value for future research in the field of power transformer material price prediction.

关键词： Power transformer material Price prediction Complementary ensemble empirical mode decomposition Gated recurrent unit Empirical wavelet transform

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Novel Static Security and Stability Control of Power Systems Based on Artificial Emotional Lazy Q-Learning

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Energy Engineering 2024年第6期121卷 1713-1737页

作者： Tao Bao Xiyuan Ma Zhuohuan Li Duotong Yang Pengyu Wang Changcheng Zhou Digital Grid research Institute Southern Power GridGuangzhou510000China

The stability problem of power grids has become increasingly serious in recent years as the size of novel power systems increases.In order to improve and ensure the stable operation of the novel power system,this study proposes an artificial emotional lazy Q-learning method,which combines artificial emotion,lazy learning,and reinforcement learning for static security and stability analysis of power systems.Moreover,this study compares the analysis results of the proposed method with those of the small disturbance method for a stand-alone power system and verifies that the proposed lazy Q-learning method is able to effectively screen useful data for learning,and improve the static security stability of the new type of power system more effectively than the traditional proportional-integral-differential control and Q-learning methods.

关键词： Artificial sentiment static secure stable analysis Q-learning lazy learning data filtering

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Multimorbidity and mortality among older patients with coronary heart disease in Shenzhen,China

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Journal of Geriatric Cardiology 2024年第1期21卷 81-89页

作者： Fu-Rong LI Shuang WANG Xia LI Zhi-Yuan CHENG Cheng JIN Chun-Bao MO Jing ZHENG Feng-Chao LIANG Dong-Feng GU Shenzhen Key Laboratory of Cardiovascular Health and Precision Medicine Southern University of Science and TechnologyShenzhenGuangdongChina School of Public Health and Emergency Management Southern University of Science and TechnologyShenzhenGuangdongChina Shenzhen Health Development research and Data Management Center ShenzhenChina School of Medicine Southern University of Science and TechnologyShenzhenGuangdongChina

BACKGROUND The current understanding of the magnitude and consequences of multimorbidity in Chinese older adults with coronary heart disease(CHD)is insufficient.We aimed to assess the association and population-attributable fractions(PAFs)between multimorbidity and mortality among hospitalized older patients who were diagnosed with CHD in Shenzhen,China.METHODS We conducted a retrospective cohort study of older Chinese patients(aged≥65 years)who were diagnosed with CHD.Cox proportional hazards models were used to estimate the associations between multimorbidity and all-cause and cardiovascular disease(CVD)mortality.We also calculated the PAFs.RESULTS The study comprised 76,455 older hospitalized patients who were diagnosed with CHD between January 1,2016,and August 31,2022.Among them,70,217(91.9%)had multimorbidity,defined as the presence of at least one of the predefined 14 chronic conditions.Those with cancer,hemorrhagic stroke and chronic liver disease had the worst overall death risk,with adjusted HRs(95%CIs)of 4.05(3.77,4.38),2.22(1.94,2.53),and 1.85(1.63,2.11),respectively.For CVD mortality,the highest risk was observed for hemorrhagic stroke,ischemic stroke,and chronic kidney disease;the corresponding adjusted HRs(95%CIs)were 3.24(2.77,3.79),1.91(1.79,2.04),and 1.81(1.64,1.99),respectively.All-cause mortality was mostly attributable to cancer,heart failure and ischemic stroke,with PAFs of 11.8,10.2,and 9.1,respectively.As for CVD mortality,the leading PAFs were heart failure,ischemic stroke and diabetes;the corresponding PAFs were 18.0,15.7,and 6.1,respectively.CONCLUSIONS Multimorbidity was common and had a significant impact on mortality among older patients with CHD in Shenzhen,China.Cancer,heart failure,ischemic stroke and diabetes are the primary contributors to PAFs.Therefore,prioritizing improved treatment and management of these comorbidities is essential for the survival prognosis of CHD patients from a holistic public health perspective.

关键词： patients morbidity mortality

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Reducing idleness in financial cloud services via multi-objective evolutionary reinforcement learning based load balancer

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Science China(Information Sciences) 2024年第2期67卷 20-40页

作者： Peng YANG Laoming ZHANG Haifeng LIU Guiying LI Department of Statistics and Data Science Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and EngineeringSouthern University of Science and Technology Academy for Advanced Interdisciplinary Studies Southern University of Science and Technology Guangdong OPPO Mobile Telecommunications Corp. Ltd research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology

In recent years, various companies have started to shift their data services from traditional data centers to the cloud. One of the major motivations is to save on operational costs with the aid of cloud elasticity. This paper discusses an emerging need from financial services to reduce the incidence of idle servers retaining very few user connections, without disconnecting them from the server side. This paper considers this need as a bi-objective online load balancing problem. A neural network based scalable policy is designed to route user requests to varied numbers of servers for the required elasticity. An evolutionary multi-objective training framework is proposed to optimize the weights of the policy. Not only is the new objective of idleness reduced by over 130% more than traditional industrial solutions, but the original load balancing objective itself is also slightly improved. Extensive simulations with both synthetic and real-world data help reveal the detailed applicability of the proposed method to the emergent problem of reducing idleness in financial services.

关键词： evolutionary reinforcement learning evolutionary multi-objective optimization load balance cloud computing

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Cognitive function among military veterans with STEM occupations

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Military Medical research 2024年第2期11卷 308-310页

作者： Justin T.McDaniel Kevin N.Hascup Erin R.Hascup Ugochukwu G.Ezigbo Amanda M.Weidhuner Harvey Henson David L.Albright Dale and Deborah Smith Center for Alzheimer's research and trEatment(CARE) Southern Illinois University School of MedicineSpringfieldIL 62794USA STEM Education research Center Southern Illinois UniversityCarbondaleIL 62901USA Department of Political Science The University of AlabamaTuscaloosaAL 35487USA

Dear Editor,There is limited research on the relationship between science,technology,engineering,and mathematics(STEM)occupational history and cognitive function in later life,especially among military veterans,who may be at greater risk for later-life cognitive decline.This study examines a nationally representative sample of military veterans to address this gap in knowledge.

关键词： Alzheimer's disease Veterans Science technology engineering and mathematics(STEM) Animal fluency test Dementia

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Understanding intrarenal backflow: Intrarenal pressure during ureteroscopy and beyond

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Asian Journal of Urology 2024年第2期11卷 139-142页

作者： Palle J.S.Osther Susanne S.Osther Maria P.Hesselholt Sofia Byllov Søren K.Lildal Louise F.Øbro Helene Jung Urological research Center Department of UrologyVejle Hospital(a part of Lillebaelt Hospital)University Hospital of Southern DenmarkVejleDenmark Department of Regional Health research University of Southern DenmarkOdenseDenmark

The number of ureterorenoscopic procedures for upper urinary tract stone management has increased dramatically during recent years worldwide[1].Developments in flexible ureteroscope and laser technology have made it possible to successfully address larger and more complex stone scenarios retrogradely.On the other hand,this means that more and more patients are exposed to the potential adverse effects of ureteroscopy[2].In general,ureteroscopy is considered a safe procedure.However,serious complications and even deaths do occur,and these events are most likely underreported[3,4].

关键词： beyond likely ureter

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Estimating Critical Clearing Time of Grid Faults Using DA of State-Reduction Model of Power Systems

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 807-820页

作者： Yang Liu Zhongyang Chen Huanjin Yao Lin Yi Q.H.Wu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China China southern Power Grid research Institute Guangzhou 510663China

This paper proposes a critical clearing time (CCT) estimation method by the domain of attraction (DA) of a state-reduction model of power systems using sum of squares (SOS) programming. By exploiting the property of the Jacobian matrix and the structure of the boundary of the DA, it is found the DA of the state-reduction model and that of the full model of a power system are topological isomorphism. There are one-to-one correspondence relationships between the number of equilibrium points, the type of equilibrium points, and solutions of the two system models. Based on these findings, an expanding interior algorithm is proposed with SOS programming to estimate the DA of the state-reduction model. State trajectories of the full model can be transformed to those of the state-reduction model by orthogonal or equiradius projection. In this way, CCT of a grid fault is estimated with the DA of the state-reduction model. The calculational burden of SOS programming in the DA estimation using the state-reduction model is rather small compared with using the full model. Simulation results show the proposed expanding interior algorithm is able to provide a tight estimation of DA of power systems with higher accuracy and lower time costs.

关键词： Critical clearing time domain of attraction expanding interior algorithm state-reduction model SOS programming

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Topological magnetoelectric response in ferromagnetic axion insulators

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National Science Review 2024年第2期11卷 8-14页

作者： Yuhao Wan Jiayu Li Qihang Liu Department of Physics and Shenzhen Institute for Quantum Science and Engineering(SIQSE) Southern University of Science and Technology Shenzhen Key Laboratory of Advanced Quantum Functional Materials and Devices Southern University of Science and Technology Guangdong Provincial Key Laboratory for Computational Science and Material Design Southern University of Science and Technology

The topological magnetoelectric effect （TME） is a hallmark response of the topological field theory,which provides a paradigm shift in the study of emergent topological phenomena.However,its direct observation is yet to be realized due to the demanding magnetic configuration required to gap all surface states.Here,we theoretically propose that axion insulators with a simple ferromagnetic configuration,such as the MnBi2Te4/（Bi2Te3）nfamily,provide an ideal playground to realize the TME.In the designed triangular prism geometry,all the surface states are magnetically gapped.Under a vertical electric field,the surface Hall currents give rise to a nearly half-quantized orbital moment,accompanied by a gapless chiral hinge mode circulating in parallel.Thus,the orbital magnetization from the two topological origins can be easily distinguished by reversing the electric field.Our work paves the way for direct observation of the TME in realistic axion-insulator materials.

关键词： topological magnetoelectric effect axion insulator magnetic topological materials

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Big data-driven water research towards metaverse

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Water Science and Engineering 2024年第2期17卷 101-107页

作者： Minori Uchimiya USDA-ARS southern Regional research Center 1100 Allen Toussaint BoulevardNew OrleansLA 70124USA

Although big data is publicly available on water quality parameters,virtual simulation has not yet been adequately adapted in environmental chemistry research.Digital twin is different from conventional geospatial modeling approaches and is particularly useful when systematic laboratory/field experiment is not realistic(e.g.,climate impact and water-related environmental catastrophe)or difficult to design and monitor in a real time(e.g.,pollutant and nutrient cycles in estuaries,soils,and sediments).Data-driven water research could realize early warning and disaster readiness simulations for diverse environmental scenarios,including drinking water contamination.

关键词： Data mining Omics Remote sensing Sensor Chemoinformatics

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Multi-Time-Scale Resource Allocation Based on Long-Term Contracts and Real-Time Rental Business Models for Shared Energy Storage Systems

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 454-465页

作者： Yuxuan Zhuang Zhiyi Li Qipeng Tan Yongqi Li Minhui Wan College of Electrical Engineering Zhejiang UniversityHangzhouChina China southern Power Grid Power Generation Company Energy Storage research Institute GuangzhouChina IEEE

The push for renewable energy emphasizes the need for energy storage systems(ESSs)to mitigate the unpre-dictability and variability of these sources,yet challenges such as high investment costs,sporadic utilization,and demand mismatch hinder their broader adoption.In response,shared energy storage systems(SESSs)offer a more cohesive and efficient use of ESS,providing more accessible and cost-effective energy storage solutions to overcome these obstacles.To enhance the profitability of SESSs,this paper designs a multi-time-scale resource allocation strategy based on long-term contracts and real-time rental business models.We initially construct a life cycle cost model for SESS and introduce a method to estimate the degradation costs of multiple battery groups by cycling numbers and depth of discharge within the SESS.Subsequently,we design various long-term contracts from both capacity and energy perspectives,establishing associated models and real-time rental models.Lastly,multi-time-scale resource allocation based on the decomposition of user demand is proposed.Numerical analysis validates that the business model based on long-term contracts excels over models operating solely in the real-time market in economic viability and user satisfaction,effectively reducing battery degradation,and leveraging the aggregation effect for SESS can generate an additional increase of 10.7%in net revenue.

关键词： Capacity allocation long-term contracts shared energy storage system stochastic programming

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