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IEEE/CAA Journal of Automatica Sinica 2024年第6期11卷 1342-1357页

作者： Sheng Qi rui Wang Tao Zhang Xu Yang ruiqing Sun ling Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China Xiangjiang Laboratory Changsha 410205China College of Computer National University of Defense TechnologyChangsha 410073China Department of Automation Tsinghua UniversityBeijing 100084China IEEE

Traditional large-scale multi-objective optimization algorithms(LSMOEAs)encounter difficulties when dealing with sparse large-scale multi-objective optimization problems(SLM-OPs)where most decision variables are *** a result,many algorithms use a two-layer encoding approach to optimize binary variable Mask and real variable Dec ***,existing optimizers often focus on locating non-zero variable posi-tions to optimize the binary variables ***,approxi-mating the sparse distribution of real Pareto optimal solutions does not necessarily mean that the objective function is *** data mining,it is common to mine frequent itemsets appear-ing together in a dataset to reveal the correlation between *** by this,we propose a novel two-layer encoding learning swarm optimizer based on frequent itemsets(TELSO)to address these *** mined the frequent terms of multiple particles with better target values to find mask combinations that can obtain better objective values for fast ***-mental results on five real-world problems and eight benchmark sets demonstrate that TELSO outperforms existing state-of-the-art sparse large-scale multi-objective evolutionary algorithms(SLMOEAs)in terms of performance and convergence speed.

关键词： Evolutionary algorithms learning swarm optimiza-tion sparse large-scale optimization sparse large-scale multi-objec-tive problems two-layer encoding.

Enhancing Evolutionary Algorithms With Pattern Mining for Sparse Large-Scale Multi-Objective Optimization Problems

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1786-1801页

作者： Sheng Qi rui Wang Tao Zhang Weixiong Huang Fan Yu ling Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China College of Systems Engineering National University of Defense TechnologyChangsha 410073and also with the Xiangjiang LaboratoryChangsha 410205China College of Transportation and Engineering Central South UniversityChangsha 410073China Department of Automation Tsinghua UniversityBeijing 100084China

Sparse large-scale multi-objective optimization problems(SLMOPs)are common in science and ***,the large-scale problem represents the high dimensionality of the decision space,requiring algorithms to traverse vast expanse with limited computational ***,in the context of sparse,most variables in Pareto optimal solutions are zero,making it difficult for algorithms to identify non-zero variables *** paper is dedicated to addressing the challenges posed by *** start,we introduce innovative objective functions customized to mine maximum and minimum candidate *** substantial enhancement dramatically improves the efficacy of frequent pattern *** this way,selecting candidate sets is no longer based on the quantity of nonzero variables they contain but on a higher proportion of nonzero variables within specific ***,we unveil a novel approach to association rule mining,which delves into the intricate relationships between non-zero *** novel methodology aids in identifying sparse distributions that can potentially expedite reductions in the objective function *** extensively tested our algorithm across eight benchmark problems and four real-world *** results demonstrate that our approach achieves competitive solutions across various challenges.

关键词： Evolutionary algorithms pattern mining sparse large-scale multi-objective problems(SLMOPs) sparse large-scale optimization.

Possible Habitats for NH_(3),NH_(2)D,H^(13)CN,HC^(15)N,SO,and C^(18)O in the Initial Conditions of High-mass Star Formation

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Research in Astronomy and Astrophysics 2024年第4期24卷 237-252页

作者： Quan-ling Cui Chuan-Peng Zhang Jun-jie Wang National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China College of Science Qiqihar UniversityQiqihar 161006China Guizhou Radio Astronomical Observatory Guizhou UniversityGuiyang 550000China

The initial condition of high-mass star formation is a complex area of study because of the high densities(n_(H_(2))>106cm^(-3))and low temperatures(T_(dust)<18 K)*** such conditions,many molecules become depleted from the gas phase by freezing out onto dust ***,the N-bearing and deuterated species could remain gaseous under these extreme conditions,suggesting that they may serve as ideal *** this paper,using the Plateau de Bure Interferometer and Very Large Array observations at 1.3 mm,3.5 mm,and 1.3 cm,we investigate the possible habitats for NH_(3),NH_(2)D,H^(13)CN,HC^(15)N,SO,and C^(18)O in eight massive precluster and protocluster clumps G18.17,G18.21,G23.97N,G23.98,G23.44,G23.97S,G25.38,and *** found that the NH3cores are in good agreement with the 3.5 mm peak emission,but the NH_(3)is much more extended than the 3.5 mm emission *** SO distributions agree well with the 3.5 mm peaks for the evolved star formation stage,but we did not detect any SO emission in the four earliest star formation sources.C^(18)O is a poor tracer in conditions of the cold(■18 K)and dense(■10^(4)cm^(-3))cores,e.g.,the prestellar *** also found that the NH_(2)D cores are mainly located in the temperature range of 13.0-20.0 K,and the NH_(2)D lines may be strongly depleted above 20 K.

关键词： galaxies:star formation techniques:interferometric methods:observational

Printable,flexible ceramic fiber paper based on electrospinning

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Rare Metals 2024年第6期43卷 2739-2746页

作者： Yong-Shuai Xie Yuan Cheng Yang Lyu rui Li jie-Cai Han National Key Laboratory of Science and Technology on Advanced Composites in Special Environments Harbin Institute of TechnologyHarbin 150001China State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China

Based on the fact that it is challenging for the polymer flexible circuit substrates to meet the requirements of serving in high-temperature environments,this work proposed the idea of using printable ceramic fiber paper as a high-temperature flexible circuit substrate.A ceramic fiber paper with all ceramic components had been developed via electrospinning,solving the problems of low strength and severe strength drop at high temperatures of traditional ceramic fiber *** tensile strength of the prepared ceramic fiber paper is 2.63 MPa,and the reliable service temperature is 1200℃.Its bulk density is about 1.5 times that of traditional ceramic fiber *** can be printed with patterns by commercial inkjet printers like ordinary printing paper and has excellent *** feasibility of ceramic fiber paper as a flexible circuit substrate was verified by constructing a simple *** the fiber paper is significantly bent,the circuit still forms a complete path,which proves that it has a strong application potential for high-temperature flexible circuit substrate and is expected to promote the development of flexible electronic devices serving at extreme high-temperature environments.

关键词： Ceramic fiber paper High temperature Inkjet printing Flexible electronic

A real-world study of the differences in Traditional Chinese Medicine diagnosis and treatment rules for coronavirus disease 2019 between Northern and Southern China

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Journal of Traditional Chinese Medicine 2024年第4期44卷 822-829页

作者： SU rui SU Youzhu WANG Shuo FAN jie LIU Qingquan LIU Mifeng Department of infectious diseases Capital Medical University Beijing Hospital of Traditional Chinese MedicineBeijing 100010China

OBJECTIVE:To explore the differences in Traditional Chinese Medicine(TCM)diagnosis and treatment rules for coronavirus disease 2019(COVID-19)between Northern and Southern China based on the real-world data from 982 COVID-19 ***:All consecutive cases of COVID-19 admitted to the TCM department of designated COVID-19 hospitals in eight provinces and cities were retrospectively *** were divided into a Northern and a Southern group according to the location of the admitting *** symptoms,syndrome elements,syndrome distribution and herbal treatments were *** core prescriptions were extracted using the multiscale backbone-based network comparison algorithm(msbNC).RESULTS:The distribution of syndrome elements showed that dampness was common in Northern and Southern China,wind and heat were more often present in the South,while fire toxin and spleen deficiency were more often encountered in the *** distribution of syndromes showed that the South was dominated by heat dampness accumulating in the lung(55.69%),while the North was dominated by dampness-toxin stagnating in the lung(44.90%).The results of core prescription mining showed that dispelling dampness,dispersing wind,clearing heat and strengthening spleen were the common treatment methods in Northern and Southern *** mild cases,Jinyinhua(Flos Lonicerae)and Lianqiao(Fructus Forsythiae Suspensae)were often used in the South to clear heat and relieve exterior symptoms,while Chaihu(Radix Bupleuri Chinensis)and Huangqin(Radix Scutellariae Baicalensis)were often used in the North to relieve muscles by expelling *** moderate cases,Chaihu(Radix Bupleuri Chinensis),Qinghao(Herba Artemisiae Annuae),and Shigao(Gypsum Fibrosum)were often used to clear heat of Tri-jiao Channel and stomach in the South,while Fuling(Poria),Chenpi(Pericarpium Citri Reticulatae),and Dangshen(Radix Codonopsis)were often used to invigorate spleen and remove dampness in the *** severe cases

关键词： COVID-19 medicine,Chinese traditional North-South difference core prescription syndrome retrospective studies

Analysis of Health Service Utilization and its Influencing Factors among Patients with Pneumoconiosis in China

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Biomedical and Environmental Sciences 2021年第1期34卷 83-88页

作者： WANG Huan Qiang JIA Jun Lin JIANG Zhao Qiang JIN Qi LI Dong Xia ling rui jie LI Ying CUI Ping CHEN Gang ZHAO Hong Yu LI Yan WEN Ke LYU Xiang Pei LOU Jian Lin LI Tao National Institute of Occupational Health and Poison Control Chinese Center for Disease Control and PreventionBeijing 100050China Hangzhou Medical College(Zhejia ng Academy of Medical Sciences) Hangzhou 310013ZhejiangChina Center for Clinical Big Data and Analytics The Second Affiliated HospitalZhejiang University School of MedicineHangzhou 310009ZhejiangChina Guizhou Hospital for Occupational Disease Prevention and Control Guiyang 550006GuizhouChina Hubei Hospital for Occupational Diseases Wuhan 430000HubeiChina Hunan Prevention and Treatment Center for Occupational Disease Changsha 410007HunanChina Shandong Academy of Occupational Health and Occupational Medicine Jinan 250062ShandongChina Beidaihe Hospital for Occupational Disease Prevent on and ControlState Administration of Production SafetyQinhuangdao 066100HebeiChina Yunnan Hospital for Occupational Diseases Kunming 650011YunnanChina Jilin Hospital for Occupational Disease Prevention and Control Changchun 132000JilinChina

Pneumoconiosis,an interstitial lung disease that occurs from breathing in certain kinds of damaging dust particles,is a major occupational disease in *** diagnosed with occupational pneumoconiosis can avail of free medical treatment,whereas patients without a diagnosis of occupational diseases cannot not claim free medical treatment in most provinces from the government before *** study aimed to analyze the priority of medical facility selection and its influencing factors among patients with pneumoconiosis.

关键词： diagnosis treatment among

Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 157-169页

作者： rui Wang Zhiming Zhou Kaiwen Li Tao Zhang ling Wang Xin Xu Xiangke Liao IEEE the Xiangjiang Laboratory and the College of Systems Engineering National University of Defense TechnologyChangsha 410073China the Institute of Automation Chinese Academy of SciencesBeijing 100190China the College of Systems Engineering National University of Defense TechnologyChangsha 410073 the Hunan Key Laboratory of Multi-Energy System Intelligent Interconnection Technology Changsha 410073China the Department of Automation Tsinghua UniversityBeijing 100084China the College of Intelligence Science and Technology National University of Defense TechnologyChangsha 410073China the College of Computer Science and Technology National University of Defense TechnologyChangsha 410073China

Traditional expert-designed branching rules in branch-and-bound(B&B) are static, often failing to adapt to diverse and evolving problem instances. Crafting these rules is labor-intensive, and may not scale well with complex *** the frequent need to solve varied combinatorial optimization problems, leveraging statistical learning to auto-tune B&B algorithms for specific problem classes becomes attractive. This paper proposes a graph pointer network model to learn the branch rules. Graph features, global features and historical features are designated to represent the solver state. The graph neural network processes graph features, while the pointer mechanism assimilates the global and historical features to finally determine the variable on which to branch. The model is trained to imitate the expert strong branching rule by a tailored top-k Kullback-Leibler divergence loss function. Experiments on a series of benchmark problems demonstrate that the proposed approach significantly outperforms the widely used expert-designed branching rules. It also outperforms state-of-the-art machine-learning-based branch-and-bound methods in terms of solving speed and search tree size on all the test instances. In addition, the model can generalize to unseen instances and scale to larger instances.

关键词： Branch-and-bound(B&B) combinatorial optimization deep learning graph neural network imitation learning

A Matching Algorithm with Reinforcement Learning and Decoupling Strategy for Order Dispatching in On-Demand Food Delivery

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Tsinghua Science and Technology 2024年第2期29卷 386-399页

作者： Jingfang Chen ling Wang Zixiao Pan Yuting Wu jie Zheng Xuetao Ding Department of Automation Tsinghua UniversityBeijing 100084China Department of Delivery Technology MeituanBeijing 100102China

The on-demand food delivery(OFD)service has gained rapid development in the past decades but meanwhile encounters challenges for further improving operation *** order dispatching problem is one of the most concerning issues for the OFD platforms,which refer to dynamically dispatching a large number of orders to riders reasonably in very limited decision *** solve such a challenging combinatorial optimization problem,an effective matching algorithm is proposed by fusing the reinforcement learning technique and the optimization ***,to deal with the large-scale complexity,a decoupling method is designed by reducing the matching space between new orders and ***,to overcome the high dynamism and satisfy the stringent requirements on decision time,a reinforcement learning based dispatching heuristic is *** be specific,a sequence-to-sequence neural network is constructed based on the problem characteristic to generate an order priority ***,a training approach is specially designed to improve learning ***,a greedy heuristic is employed to effectively dispatch new orders according to the order priority *** real-world datasets,numerical experiments are conducted to validate the effectiveness of the proposed *** results show that the proposed algorithm can effectively solve the problem by improving delivery efficiency and maintaining customer satisfaction.

关键词： order dispatching on-demand delivery reinforcement learning decoupling strategy sequence-to-sequence neural network

Impurity formation mechanism of silicon carbide crystals smelted by Acheson process

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Journal of Iron and Steel Research International 2024年第6期31卷 1367-1375页

作者： Dong Feng Hong-qiang Ru Xu-dong Luo jie-gang You ling Zhang School of Materials and Metallurgy University of Science and Technology LiaoningAnshan 114051LiaoningChina Key Laboratory for Anisotropy and Texture of Materials(Ministry of Education) Institute of Advanced CeramicsSchool of Materials Science and EngineeringNortheastern UniversityShenyang 110819LiaoningChina Liaoning Institute of Science and Technology Benxi 117004LiaoningChina

In order to further promote the application of SiC refractories in modern steel metallurgy,the occurrence forms and formation mechanism of impurities in SiC crystals smelted by Acheson process were *** techniques of inductively coupled plasma-atomic emission spectrometry,X-ray diffraction,and scanning electron microscopy were combined to examine the types and occurrence forms of impurities in smelted SiC *** results showed that the main impurities in the SiC are free Si,free C,oxides(CaO·Al_(2)O_(3)·2SiO_(2),3Al_(2)O_(3)·2SiO_(2),CaO·SiO_(2) and SiO_(2))and alloy phases(Fe_(x)Si_(y),Fe_(x)Si_(y)Ti_(z) and Fe_(x)Al_(y)Si_(z)).The formation process of impurities during the smelting of SiC can be described as follows:At high temperature,the SiO_(2) and Fe,Ti related oxide impurities present in the raw materials are reduced to Si,Fe,and Ti metal *** the reduction process,the free Si,Fe_(x)Si_(y) and Fe_(x)Si_(y)Ti_(z) are precipitated from the melt during *** Si primarily exists in aggregated form within the SiC crystal,while the alloy phase is predominantly found at the interface between SiC and free Si,with Fe_(x)Si_(y)Ti_(z) embedded within *** the end of the cooling process,other impurity oxides such as Al_(2)O_(3),CaO,and some unreduced SiO_(2) solidify to form calcium-aluminum-silicate glass phases,predominantly located between SiC *** remaining C from the reaction is mainly dispersed as free C within the SiC crystal and at the interface between SiC and free Si.

关键词： Impurity element Formation mechanism Smelted SiC crystal SiC refractory Occurrence form

A robust triaxial localization method of AE source using refraction path

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International Journal of Mining Science and Technology 2024年第4期34卷 521-530页

作者： Yichao rui jie Chen Jiongkun Chen Jiadong Qiu Zilong Zhou Wenzhong Wang Jinyang Fan State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing UniversityChongqing 400044China School of Resources and Safety Engineering Chongqing UniversityChongqing 400044China School of Resources Environment and Safety Engineering University of South ChinaHengyang 421001China School of Resources and Safety Engineering Central South UniversityChangsha 410083China Coal Geological Exploration Institute of Gansu Lanzhou 730030China

Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization *** the end,a robust triaxial localization method of AE source using refraction path is ***,the control equation of the refraction path is established according to the sensor coordinates and arrival ***,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation ***,the refraction points in different directions are solved using Snell’s law and orthogonal ***,the source coordinates are iteratively solved by weighted correction *** feasibility and accuracy of the proposed method are verified by pencil-lead breaking *** simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.

关键词： Acoustic emission(AE) Source localization Robust method Refraction paths Weight estimations