检索结果-南通市图书馆

Nonparametric Estimation of Interval-censored Failure Time Data in the Presence of Informative Censoring

在线全文

学校读者我要写书评

暂无评论

Acta Mathematicae Applicatae Sinica 2017年第1期33卷 107-114页

作者： Chun-jie WANG jian-guo sun De-hui WANG Ning-zhong SHI The College of Basic Science Changchun University of Technology Changchun 130012 China Mathematics School and Institute of Jilin University Changchun 130012 China Department of Statistics University of Missouri 146 Middlebush Hall MO 65211. USA Key Laboratory of Applied Statistics of MOE School of Mathematics and Statistics Northeast Normal University Changchun 130024 China

Nonparametric estimation of a survival function is one of the most commonly asked questions in the analysis of failure time data and for this, a number of procedures have been developed under various types of censoring structures （Kalbfleisch and Prentice, 2002）. In particular, several algorithms are available for interval-censored failure time data with independent censoring mechanism （sun, 2006; Turnbull, 1976）. In this paper, we consider the interval-censored data where the censoring mechanism may be related to the failure time of interest, for which there does not seem to exist a nonparametric estimation procedure. It is well-known that with informative censoring, the estimation is possible only under some assumptions. To attack the problem, we take a copula model approach to model the relationship between the failure time of interest and censoring variables and present a simple nonparametric estimation procedure. The method allows one to conduct a sensitivity analysis among others.

关键词： copula models interval censored data dependent censoring nonparametric estimation

Exact Box-Constrained Economic Operating Region for Power Grids Considering Renewable Energy Sources

在线全文

学校读者我要写书评

暂无评论

Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 514-523页

作者： Huating Xu Bin Feng Chutong Wang Chuangxin guo jian Qiu Mingyang sun College of Electrical Engineering Zhejiang UniversityHangzhou 310027China Department of Control Science and Engineering Zhejiang UniversityHangzhou 310027China

The growing integration of renewable energy sources manifests as an effective strategy for reducing carbon emissions. This paper strives to efficiently approximate the set of optimal scheduling plans(OSPs) to enhance the performance of the steady-state adaptive cruise method(SACM) of power grid, improving the ability of dealing with operational uncertainties. Initially, we provide a mathematical definition of the exact boxconstrained economic operating region(EBC-EOR) for the power grid and its dispatchable components. Following this, we introduce an EBC-EOR formulation algorithm and the corresponding bi-level optimization models designed to explore the economic operating boundaries. In addition, we propose an enhanced big-M method to expedite the computation of the EBCEOR. Finally, the effectiveness of the EBC-EOR formulation, its economic attributes, correlation with the scheduling plan underpinned by model predictive control, and the significant improvement in computational efficiency(over twelvefold) are verified through case studies conducted on two test systems..

关键词： Exact box-constrained economic operating region(EBC-EOR) big-M method intelligent scheduling steady-state adaptive cruise uncertainty renewable energy source

Hybrid Model of Power Transformer Fault Classification Using C-set and MFCM – MCSVM

在线全文

学校读者我要写书评

暂无评论

CSEE Journal of Power and Energy Systems 2024年第2期10卷 672-685页

作者： Ali Abdo Hongshun Liu Yousif Mahmoud Hongru Zhang Ying sun Qingquan Li jian guo Shandong Provincial Key Laboratory of UHV Transmission Technology and Equipment School of Electrical EngineeringShandong UniversityJinan 250061China

This paper aims to increase the diagnosis accuracy of the fault classification of power transformers by introducing a new off-line hybrid model based on a combination subset of the et method(C-set)&modified fuzzy C-mean algorithm(MFCM)and the optimizable multiclass-SVM(MCSVM).The innovation in this paper is shown in terms of solving the predicaments of outliers,boundary proportion,and unequal data existing in both traditional and intelligence *** into consideration the closeness of dissolved gas analysis(DGA)data,the C-set method is implemented to subset the DGA data samples based on their type of faults within unrepeated ***,the MFCM is used for removing outliers from DGA samples by combining highly similar data for every subset within the same cluster to obtain the optimized training data(OTD)*** is also used to minimize dimensionality of DGA samples and the uncertainty of transformer condition *** that,the optimized MCSVM is trained by using the(OTD).The proposed model diagnosis accuracy is 93.3%.The obtained results indicate that our model significantly improves the fault identification accuracy in power transformers when compared with other conventional and intelligence models.

关键词： Combination subset of set(C-set)method modified fuzzy C-means(MFCM) optimizable multiclass-SVM(MCSVM) optimized training data(OTD)

Amorphous high-entropy phosphoxides for efficient overall alkaline water/seawater splitting

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Journal of Materials Science & Technology 2024年第6期173卷 1-10页

作者： Han-Ming Zhang Lihao Zuo Yuhang Gao Junxia guo Caizhen Zhu jian Xu Jinfeng sun School of Materials Science and Engineering Hebei University of Science and TechnologyShijiazhuangHebei 050018China Hebei Key Laboratory of Flexible Functional Materials ShijiazhuangHebei 0500180China Institute of Low-dimensional Materials Genome Initiative College of Chemistry and Environmental EngineeringShenzhen UniversityShenzhenGuangdong 518060China

Designing and synthesizing cost-effective bifunctional catalysts for overall alkaline water/seawater splitting is still a huge challenge for hydrogen ***,Co/Ni/Fe/Mn based-amorphous high-entropy phosphoxide self-standing electrode(CNFMPO)is synthesized by the facile and fast electrodeposition *** exhibits excellent bifunctional electrocatalytic performances on alkaline water/seawater *** hydrogen evolution reaction(HER)and oxygen evolution reaction(OER)overpotentials of CNFMPO in alkaline water/seawater are as low as 43/73 and 252/282 mV to reach a current density of 10 mA cm^(-2),***,two-electrode electrolyzers with CNFMPO||CNFMPO successfully achieve the current density of 10 mA cm^(-2) at low voltages of 1.54 and 1.56 V for overall alkaline water/seawater splitting,*** exhibits satisfactory long-term stability on overall alkaline water/seawater splitting for the surface reconstruction into active metal hydroxide/(oxy)hydroxide,phosphite,and ***,no hypochlorite is detected during seawater electrolysis for the beneficial chlorite oxidation inhibition of the reconstructed phosphite and *** excellent catalytic performances of CNFMPO are due to the unique amorphous structure,multi-component synergistic effect,beneficial electronic structure modulation,and surface reconstruction during the catalytic reaction ***,CNFMPO has shown potential promotion to the development of the water/seawater splitting industry as a promising substituent for noble-metal *** work provides new insights into the design of efficient bifunctional catalysts for overall water/seawater splitting.

关键词： Amorphous high-entropy phosphoxides Water/seawater splitting Synergistic effect Surface reconstruction Electronic structure modulation Inhibition of chloride oxidation reaction

Harnessing data using symbolic regression methods for discovering novel paradigms in physics

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(Physics,Mechanics & Astronomy) 2024年第6期67卷 1-11页

作者： jianyang guo Wan-jian Yin College of Energy Soochow Institute for Energy and Materials Innovations(SIEMIS)Jiangsu Provincial Key Laboratory for Advanced Carbon Materials and Wearable Energy TechnologiesSoochow UniversitySuzhou 215006China Shanghai Qi Zhi Institute Shanghai 200232China Light Industry Institute of Electrochemical Power Sources Soochow UniversitySuzhou 215006China

In recent years,machine-learning methods have profoundly impacted research in the interdisciplinary fields of ***,most machine-learning models lack interpretability,and physicists doubt the credibility of their conclusions because they cannot be combined with prior physical ***,this review focuses on symbolic regression,which is an interpretable machine-learning ***,the relevant concepts of machine learning are introduced in conjunction with ***,we provide an overview of symbolic regression ***,the recent directions for the application of symbolic regression methods in different subfields of physics are outlined,and an overview of the ways in which the applications of symbolic regression have evolved in the realm of physics is *** major aim of this review is to introduce the basic principles of symbolic regression and explain its applications in the field of physics.

关键词： machine learning genetic programming symbolic regression

Direct numerical simulation of shock wave/boundary layer interaction controlled by steady microjet in a compression ramp

在线全文

学校读者我要写书评

暂无评论

Chinese Journal of Aeronautics 2024年第10期37卷 83-102页

作者： Ruoye XIAO Dong sun jian YU School of Aeronautic Science and Engineering Beihang UniversityBeijing 100191China State Key Laboratory of Aerodynamics Mianyang 621000China

Shock wave/boundary layer interaction in a 24°turning angle of the compression ramp at Mach number 2.9 controlled by steady microjet is investigated using direct numerical *** different jet spacings which are termed as sparse,moderate and dense are considered,and the induced vortex system and shock structures are compared.A moderate jet spacing configuration is found to generate counter-rotating vortex pairs that transport high-momentum fluid towards the vicinity of wall and strengthen the boundary layer to resist separation,reducing the separation *** dense jet spacing configuration creates a larger momentum deficit region,reducing the friction downstream of the *** of pressure and pressure gradient reveals that dense jet spacing configuration reduces the intensity of separation *** impact of varying jet spacings on the turbulent kinetic energy transport mechanism is also investigated by decomposing the budget terms in the transport ***,the spectral characteristics of the separation region are studied using power spectral density and dynamic mode decomposition methods,revealing that moderate jet spacing configuration suppresses low-frequency fluctuations in the separation region.

关键词： Shock wave/boundary layer interaction Compression ramp Steady microjet Different jet spacings Direct numerical simulation

Substrate screening for superclean graphene growth using firstprinciples calculations

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Nano Research 2024年第4期17卷 2216-2222页

作者： Zhihao Li Xiucai sun Xiaoli sun Wan-jian Yin Zhongfan Liu College of Energy Soochow Institute for Energy and Materials InnovationS(SIEMIS)and Jiangsu Provincial Key Laboratory for Advanced Carbon Materials and Wearable Energy TechnologiesSoochow UniversitySuzhou 215006China Graphene Basic Science Research Center Beijing Graphene Institute(BGI)Beijing 100095China Center for Nanochemistry Beijing Science and Engineering Center for NanocarbonsBeijing National Laboratory for Molecular ScienceCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China

Suppressing the formation of amorphous surface carbon and contaminants during the preparation of graphene by chemical vapor deposition remains an ongoing ***,we analyzed how substrate characteristics affect graphene quality by simulating margin extension,the nucleation process,and defect pegging configurations on mono-crystalline oriented metal substrates with the aim of enhancing graphene *** formation energy and nucleation potential,which are indirect substrate–graphene interaction features,were found to appropriately evaluate graphene *** crystallographic orientation of the metal substrate was discovered to be critical for producing superclean graphene.A low graphene defect density and high nucleation rate on the Cu(100)facet guarantee growth of high-quality graphene,especially in terms of suppressing the formation of amorphous *** addition,rapid kink growth and self-healing on the Cu(100)facet facilitate rapid graphene synthesis,which is also promoted by rapid kink splicing and margin self-repair on this *** study provides theoretical insight useful for the synthesis of superclean graphene.

关键词： superclean graphene defects nucleation metal substrates density functional theory calculations

Adversarial data splitting for domain generalization

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5期67卷 28-42页

作者： Xiang GU jian sun Zongben XU School of Mathematics and Statistics Xi'an Jiaotong University

Domain generalization aims to learn a model that is generalizable to an unseen target domain,which is a fundamental and challenging task in machine learning for out-of-distribution generalization. This paper proposes a novel domain generalization approach that enforces the learned model to be able to generalize well over the train/val subset splitting of the training dataset. This idea is modeled herein as an adversarial data splitting framework, formulated as a min-max optimization problem inspired by the metalearning approach. The min-max optimization problem is solved by iteratively splitting the training dataset into the training and val subsets to maximize the domain shift measured by the objective function and updating the model parameters to enable the model to generalize well from the training subset to the val subset by minimizing the objective function. This adversarial training approach does not assume the known domain labels of the training data; instead, it automatically investigates the “hard” splitting of the train/val subsets to learn the generalizable model. Extensive experimental results using three benchmark datasets demonstrate the superiority of this approach. In addition, we derive a generalization error bound for the theoretical understanding of our proposed approach.

关键词： domain generalization adversarial learning data splitting meta-learning out of distribution

Evaluation of water management on arsenic methylation and volatilization in arsenic-contaminated soils strengthened by bioaugmentation and biostimulation

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Journal of Environmental Sciences 2024年第3期137卷 515-526页

作者： Peng Chen Yi Liu guo-Xin sun State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China Key Laboratory of Aquatic Botany and Watershed Ecology Wuhan Botanical GardenChinese Academy of SciencesWuhan 430074China University of Chinese Academy of Sciences Beijing 100049China

Arsenic(As) fate in paddy fields has been one of the most significant current issues due to the strong As accumulation potential of rice plants under fooded conditions. However,no attempt was done to explore As methylation and volatilization under non-fooded conditions. Herein, we investigated the effects of water management on As methylation and volatilization in three arsenic-contaminated soils enhanced by biostimulation with strawderived organic matter and bioaugmentation with genetic engineered Pseudomonas putida KT2440(GE P. putida). Under fooded conditions, the application of biochar(BC), rice straw(RS)and their combination(BC+RS) increased total As in porewater. However, these effects were greatly attenuated under non-fooded conditions. Compared with RS amendment alone, the combination of GE P. putida and RS further promoted the As methylation and volatilization,and the promotion percentage under non-fooded conditions were significantly higher than that under fooded conditions. The combined GE P. putida and RS showed the highest efficiency in As methylation(88 μg/L) and volatilization(415.4 μg/(kg·year)) in the non-fooded soil with moderate As contamination. Finally, stepwise multiple linear regression analysis presented that methylated As, DOC and p H in porewater were the most important factors contributing to As volatilization. Overall, our findings suggest that combination of bioaugmentation with GE P. putida and biostimulation with RS/BC+RS is a potential strategy for bioremediation of arsenic-contaminated soils by enhancing As methylation and volatilization under non-fooded conditions.

关键词： Arsenic methylation Arsenic volatilization Water management Straw incorporation Bioaugmentation