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Two kinds of average approximation accuracy

CAAI Transactions on Intelligence Technology 2024年第2期9卷 481-490页

作者： Qingzhao Kong Wanting Wang Dongxiao Zhang Wenbin Zhang Department of Science Jimei UniversityXiamenChina Digital Fujian Big Data Modeling and Intelligent Computing Institute Jimei UniversityXiamenChina Department of Computer Science Michigan Technological UniversityHoughtonMichiganUSA

Rough set theory places great importance on approximation accuracy,which is used to gauge how well a rough set model describes a target ***,traditional approximation accuracy has limitations since it varies with changes in the target concept and cannot evaluate the overall descriptive ability of a rough set *** overcome this,two types of average approximation accuracy that objectively assess a rough set model’s ability to approximate all information granules is *** first is the relative average approximation accuracy,which is based on all sets in the universe and has several basic *** second is the absolute average approximation accuracy,which is based on undefinable sets and has yielded significant *** also explore the relationship between these two types of average approximation ***,the average approximation accuracy has practical applications in addressing missing attribute values in incomplete information tables.

关键词： rough sets rough set theory

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Accurate machine learning force fields via experimental and simulation data fusion

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npj Computational Materials 2024年第1期10卷 2512-2521页

作者： Sebastien Röcken Julija Zavadlav Department of Engineering Physics and Computation Multiscale Modeling of Fluid MaterialsTUM School of Engineering and DesignTechnical University of MunichMunichGermany Munich Data Science Institute Technical University of MunichMunichGermany

Machine Learning(ML)-based force fields are attracting ever-increasing interest due to their capacity to span spatiotemporal scales of classical interatomic potentials at quantum-level *** can be trained based on high-fidelity simulations or experiments,the former being the common ***,both approaches are impaired by scarce and erroneous data resulting in models that either do not agree with well-known experimental observations or are under-constrained and only reproduce some *** we leverage both Density Functional Theory(DFT)calculations and experimentally measured mechanical properties and lattice parameters to train an ML potential of *** demonstrate that the fused data learning strategy can concurrently satisfy all target objectives,thus resulting in a molecularmodel of higher accuracycompared to the models trained with a single data *** inaccuracies of DFT functionals at target experimental properties were corrected,while the investigated off-target properties were affected only mildly and mostly *** approach is applicable to any material and can serve as a general strategy to obtain highly accurate ML potentials.

关键词： properties satisfy attracting

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Least Square Estimation for Multiple Functional Linear Model with Autoregressive Errors

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Acta Mathematicae Applicatae Sinica 2025年第1期41卷 84-98页

作者： Meng WANG Ming-liang SHU Jian-jun ZHOU Si-xin WU Min CHEN School of Management University of Science and Technology of ChinaHefei 230026China Academy of Mathematics and System Science Chinese Academy of SciencesBeijing 100190China Yunnan Key Laboratory of Statistical Modeling and Data Analysis Yunnan UniversityKunming 650091China

As an extension of linear regression in functional data analysis, functional linear regression has been studied by many researchers and applied in various fields. However, in many cases, data is collected sequentially over time, for example the financial series, so it is necessary to consider the autocorrelated structure of errors in functional regression background. To this end, this paper considers a multiple functional linear model with autoregressive errors. Based on the functional principal component analysis, we apply the least square procedure to estimate the functional coefficients and autoregression coefficients. Under some regular conditions, we establish the asymptotic properties of the proposed estimators. A simulation study is conducted to investigate the finite sample performance of our estimators. A real example on China's weather data is applied to illustrate the validity of our model.

关键词： multiple functional linear model autoregressive errors principal component analysis consistency

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Rough set model based on variable universe

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CAAI Transactions on Intelligence Technology 2022年第3期7卷 503-511页

作者： Qingzhao Kong Xueer Chang Department of Science Jimei UniversityXiamenChina Digital Fujian Big Data Modeling and Intelligent Computing Institute XiamenChina

Rough set theory has a very good effect in information processing and knowledge *** an information table,the current scholars regard all objects as a universe,and then establish various rough set ***,in the analysis of many data problems,it is more reasonable to select parts of objects which are useful to us or can meet the actual needs as a ***,in order to make up for the deficiency of traditional models,a new model is introduced from the perspective of variable ***,some interesting properties of this model,such as approximation sets,reduct of attributes and maximum part of universe,are *** the study of this paper,it can be seen that the model developed in our paper is not only more accurate but also more effective in describing uncertain knowledge.

关键词： approximation universe describing

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A HIGH ORDER SCHEME FOR FRACTIONAL DIFFERENTIAL EQUATIONS WITH THE CAPUTO-HADAMARD DERIVATIVE

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Journal of Computational Mathematics 2025年第3期43卷 615-640页

作者： Xingyang Ye Junying Cao Chuanju Xu School of Science Jimei UniversityXiamen 361021China School of Data Science and Information Engineering Guizhou Minzu UniversityGuiyang 550025China School of Mathematical Sciences and Fujian Provincial Key Laboratory of Mathematical Modeling and High Performance Scientific Computing Xiamen UniversityXiamen 361005China

In this paper,we consider numerical solutions of the fractional diffusion equation with theαorder time fractional derivative defined in the Caputo-Hadamard sense.A high order time-stepping scheme is constructed,analyzed,and numerically *** contribution of the paper is twofold:1)regularity of the solution to the underlying equation is investigated,2)a rigorous stability and convergence analysis for the proposed scheme is performed,which shows that the proposed scheme is 3+αorder *** numerical examples are provided to verify the theoretical statement.

关键词： Caputo-Hadamard derivative Fractional differential equations High order scheme Stability and convergence analysis

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Ship AIS Trajectory Outlier Identification Model under High-speed Sampling Conditions 4

Ship AIS Trajectory Outlier Identification Model under High-...

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4th International Symposium on Computer Technology and Information science, ISCTIS 2024

作者： Wang, Han Chen, Qilong Jimei University College of Science Xiamen China Jimei University Digital Fujian Big Data Modeling and Intelligent Computing Institute College of Science Xiamen China

ISBN: (纸本)9798350354560

In order to efficiently identify the outliers of ship AIS trajectories under high-speed sampling conditions, this paper proposes an outlier identification model based on ship position distance distribution. Taking the ship AIS track data of Yangshan port as an example, the kernel density is used to estimate the daily ship position distance distribution, and then the threshold is determined and the outliers are screened out. In this paper, it is proved that the ship position distance distributions on two adjacent days are approximate, so the threshold value of yesterday can be substituted into today to identify today's outliers effectively. The experimental results show that in the application environments of Yangshan Port waters where the average rate of ship AIS track data writing into the database is 43 items/sec and the coastal waters of East China Sea where the average rate of ship AIS track data writing into the database is 287 items/sec, the model is able to efficiently identify the outliers of the ship AIS trajectories. © 2024 IEEE.

关键词： Trajectories

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New Distributed Partitioning Approach for Large Spatial Networks 4

New Distributed Partitioning Approach for Large Spatial Netw...

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4th International Conference on Digital Age and Technological Advances for Sustainable Development, ICdata 2023

作者： Aggour, Hafssa Mabrouk, Aziz Approximation Problem Modeling & Data Science Research Team Abdelmalek Essaadi University Tétouan Morocco

ISBN: (纸本)9798350311112

In urban areas, geographic spread of spatial networks continually produces massive data. In fact, the analysis of these spatial networks is squarely related to the partitioning of networks into sub-networks in a balanced manner using scalable analysis methods with the aim of minimizing processing time, namely, partitioning parallel and distributed with (Big data, ML). Our objective, consist to partition in a distributed way a large spatial network into several Subnets. Therefore, we are conducting a comparative study of distributed partitioning algorithms such as Clustering and Hierarchical Clustering methods with the method that we have proposed in another paper [26] allowing to decompose the spatial network into sub-networks taking into account the Euclidean proximity between the nodes and the different Voronoï generators. the comparative study of the three partitioning methods that we have implemented, namely, Clustering, Hierarchical Clustering and our proposed method, have allowed us to deduce that our method is the most reliable and competitive compared to others, in terms of balance partitions as well as in terms of optimizing the partitioning time. © 2023 IEEE.

关键词： Cluster analysis

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Accelerating the transition to cobalt-free batteries:a hybrid model for LiFePO_(4)/graphite chemistry

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npj Computational Materials 2024年第1期10卷 3101-3112页

作者： Gabriele Pozzato Xueyan Li Donghoon Lee Johan Ko Simona Onori Energy Science and Engineering Stanford UniversityStanfordCA 94305USA Assistant Manager Research TeamTech CenterLG Energy Solution MichiganTroyMI 48083USA Specialist Data Modeling Algorithm TeamBattery R&DLG Energy SolutionDaejeon R&D Campus34122 KoreaSouth Korea Professional Data Modeling Algorithm TeamBattery R&DLG Energy SolutionGwacheon R&D Campus13818 KoreaSouth Korea

The increased adoption of lithium-iron-phosphate batteries,in response to the need to reduce the battery manufacturing process’s dependence on scarce minerals and create a resilient and ethical supply chain,comes with many *** design of an effective and high-performing battery management system(BMS)for such technology is one of those *** this work,a physics-based model describing the two-phase transition operation of an iron-phosphate positive electrode—in a graphite anode battery—is integrated with a machine-learning model to capture the hysteresis and path-dependent behavior during transient *** machine-learning component of the proposed“hybrid”model is built upon the knowledge of the electrochemical internal states of the battery during charge and discharge operation over several driving *** hybrid model is experimentally validated over 15 h of driving,and it is shown that the machine-learning component is responsible for a small percentage of the total battery behavior(i.e.,it compensates for voltage hysteresis).The proposed modeling strategy can be used for battery performance analysis,synthetic data generation,and the development of reduced-order models for BMS design.

关键词： battery driving hysteresis

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Behavior and mechanism of pre-oxidation improvement on fluidization in the fluidized reduction of titanomagnetite

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International Journal of Minerals,Metallurgy and Materials 2024年第11期31卷 2458-2465页

作者： Haoyan Sun Ajala Adewole Adetoro Zhiqiang Wang Qingshan Zhu State Key Laboratory of Mesoscience and Engineering Institute of Process EngineeringChinese Academy of SciencesBeijing 100190China School of Chemical Engineering University of Chinese Academy of SciencesBeijing 100049China Data Science AI modeling CentreUniversity of HullHull HU67RXUK

The direct reduction process is an important development direction of low-carbon ironmaking and efficient comprehensive utilization of poly-metallic iron ore,such as ***,the defluidization of reduced iron particles with a high metallization degree at a high temperature will seriously affect the operation of fluidized bed *** the pre-oxidation enhancing reduction and the particle surface modification of titanomagnetite,the behavior and mechanism of pre-oxidation improvement on fluidization in the fluidized bed reduction of titanomagnetite are systematically studied in this ***-oxidation treatment of titanomagnetite can significantly lower the critical stable reduction fluidization gas velocity to 0.17 m/s,which is reduced by 56%compared to that of titanomagnetite reduction without pre-oxidation,while achieving a metallization degree of>90%,Corresponding to the different reduction fluidization behaviors,three pre-oxidation operation regions have been divided,taking oxidation degrees of 26%and 86%as the *** on the particle surface morphology evolution in the pre-oxidation-reduction process,the relationship between the surface morphology of pre-oxidized ore and the reduced iron with fluidization properties is *** improving method of pre-oxidation on the reduction fluidization provides a novel approach to prevent defluidization by particle surface modification,especially for the fluidized bed reduction of poly-metallic iron ore.

关键词： fluidization direct reduction pre-oxidation titanomagnetite iron whisker

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Eigen microstate analysis unveils climate dynamics

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science China(Physics,Mechanics & Astronomy) 2025年第4期68卷 91-100页

作者： Hua Tu Shang Wang Jun Meng Yongwen Zhang Xiaosong Chen Deliang Chen Jingfang Fan School of Systems Science/Institute of Nonequilibrium Systems Beijing Normal UniversityBeijing 100875China Key Laboratory of Earth System Numerical Modeling and Application Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Data Science Research Center Faculty of ScienceKunming University of Science and TechnologyKunming 650500China Department of Earth System Science Tsinghua UniversityBeijing 100084China Department of Earth Sciences University of GothenburgGothenburg 40530Sweden Potsdam Institute for Climate Impact Research Potsdam 14412Germany

The Earth's climate operates as a complex,dynamically interconnected system,driven by both anthropogenic and natural forcings and modulated by nonlinear interactions and feedback *** study employs a theoretical framework and the Eigen Microstate(EM)approach of statistical physics to examine global surface temperature variations since 1948,as revealed by a global *** identified EMs significantly correlated with key climate phenomena such as the global monsoon system,tropical climates,and El Niñ*** analysis reveals that these EMs have increasingly influenced global surface temperature variations over recent decades,highlighting the critical roles of hemispheric differences,land-sea contrasts,and tropical climate fluctuations in a warming ***,we used model simulations from more than 10 Coupled Model Intercomparison Project Phase 6(CMIP6)under three future climate scenarios to perform a comparative analysis of the changes in each EM *** results indicate that under future warming scenarios,tropical climate fluctuations will become increasingly dominant,while traditional hemispheric and monsoonal patterns may *** shift underscores the importance of understanding tropical dynamics and their impact on global climate from a physics-based *** study provides a new perspective on understanding and addressing global climate change,enhancing the theoretical foundation of this critical field,and yielding findings with significant practical implications for improving climate models and developing effective mitigation and adaptation strategies.

关键词： statistical physics nonlinear dynamics complex systems climate change

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