检索结果-南通市图书馆

Online Pareto optimal control of mean-field stochastic multi-player systems using policy iteration

在线全文

学校读者我要写书评

暂无评论

Science china(Information Sciences) 2024年第4期67卷 21-37页

作者： Xiushan JIANG Yanshuang wang Dongya ZHAO ling SHI college of New Energy China University of Petroleum(East China) Department of Electronic and Computer engineering Hong Kong University of Science and Technology

In this study, the Pareto optimal strategy problem was investigated for multi-player mean-field stochastic systems governed by It? differential equations using the reinforcement learning(RL) method.A partially model-free solution for Pareto-optimal control was derived. First, by applying the convexity of cost functions, the Pareto optimal control problem was solved using a weighted-sum optimal control problem. Subsequently, using on-policy RL, we present a novel policy iteration(PI) algorithm based on the Hrepresentation technique. In particular, by alternating between the policy evaluation and policy update steps,the Pareto optimal control policy is obtained when no further improvement occurs in system performance,which eliminates directly solving complicated cross-coupled generalized algebraic Riccati equations(GAREs).Practical numerical examples are presented to demonstrate the effectiveness of the proposed algorithm.

关键词： mean-field stochastic systems Pareto optimal control policy iteration scheme $\mathcal{H}$-representation

Nitric oxide assists nitrogen reduction reaction on 2. MBene: A theoretical study

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Chinese Chemical Letters 2024年第5期35卷 428-433页

作者： Chaozheng He Jia wang ling Fu Wei Wei Henan engineering Center of New Energy Battery Materials College of Chemistry and Chemical EngineeringShangqiu Normal UniversityShangqiu 476000China School of Chemistry and Chemical engineering Shandong Provincial Key Laboratory/Collaborative Innovation Center of Chemical Energy Storage&Novel Cell TechnologyLiaocheng UniversityLiaocheng 252059China Institute of Environment and Energy Catalysis Shaanxi Key Laboratory of Optoelectronic Functional Materials and DevicesSchool of Materials Science and Chemical EngineeringXi’an Technological UniversityXi’an 710021China college of Resources and Environmental engineering Tianshui Normal UniversityTianshui 741001China

Electrocatalytic synthesis of ammonia as an environment-friendly and sustainable development method has received widespread attention in recent ***-dimensional(2.)materials are a promising catalyst for ammonia synthesis due to their large surface *** this work,we have constructed a series of 2. metal borides(MBenes)with transition metal(TM)defects(TMd-MBenes)and comprehensively calculated the reactivity of electrocatalytic synthesis of ammonia-based on density functional *** results have demonstrated that the TMd-MBenes can effectively activate nitrogen oxide(NO)and nitrogen(N2.molecules *** interesting,the co-chemisorption of O atoms,dissociated from NO,can facilitate the spilled of the inert N2.molecules into single N atoms,which can further hydrogenate into ammonia easily with an ultralow limiting potential of 0.59 V on *** research has not only provided clues for catalyst design for experimental study but also paved the way for the industrial application of electrocatalytic ammonia synthesis.

关键词： 2. mbenes Nitrogen electro-reduction DFT N_(2.activation Ammonia synthesis

A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

在线全文

学校读者我要写书评

暂无评论

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

在线全文

学校读者我要写书评

暂无评论

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.

Learning to Branch in Combinatorial Optimization With Graph Pointer Networks

在线全文

学校读者我要写书评

暂无评论

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

FACTORS INFLUENCING THERMAL STRUCTURE IN A TRIBUTARY BAY OF THREE GORGES RESERVOIR

在线全文

学校读者我要写书评

暂无评论

Journal of Hydrodynamics 2011年第4期23卷 407-415页

作者： YU Zhen-zhen wang ling-ling college of water {2. and Hydropower engineering Hohai University Nanjing 210098 China

To better understand the factors influencing the thermal structure of tributaries in the Three Gorges Reservoir （TGR）, a well validated three-dimensional hydrodynamic and water temperature model was proposed to simulate the water temperature distribution in the Xiangxi Bay, a representative tributary of TGR. The numerical results show that water temperature stratification seasonally occurred in the Xiangxi Bay, with stable vertical temperature profiles. It is found from the numerical experiments that three key factors are responsible for the formation of water temperature structure：（1） very often, the locations of thermocline are mainly determined by wind speeds, and the higher the wind speed is, the deeper the thermocline is located beneath the water surface, which could be expressed by a fitted exponential function, （2. the thermal structure is affected by static stability of water column, and the thermocline becomes closer to the water surface and its thickness increases with the increase of temperature, （3） due to the effect of the thermal density inflow, the water temperature of the hypolimnion tends to be uniform, however, even under the condition of larger inflow discharge, the influence of the inflow on the epilitnnion and the thermocline is not significant.

关键词： water temperature stratification numerical simulation density current influencing factors wind force static stability of water inflow discharge Three Gorges Reservoir (TGR)

Stabilizing zinc anode using zeolite imidazole framework functionalized separator for durable aqueous zinc-ion batteries

在线全文

学校读者我要写书评

暂无评论

Journal of Energy Chemistry 2024年第3期90卷 23-31,I0003页

作者： Weisong Zhang Xinyan Zhu ling Kang Ziyu Peng Jing Zhu Liang Pan Lei Dai Shude Liu ling {2. Yongguang Liu Zhangxing He School of Chemical engineering North China University of Science and TechnologyTangshan 063009HebeiChina Shanghai Key Laboratory of Multidimensional Information Processing East China Normal UniversityShanghai 201620China college of Textiles Donghua UniversityShanghai 201620China

Aqueous zinc-ion batteries(AZIBs) hold great promise as a viable alternative to lithium-ion batteries owing to their high energy density and environmental ***,AZIBs are consistently plagued by the formation of zinc dendrites and concurrent side reactions,which significantly diminish their overall service life,In this study,the glass fiber separator(GF) is modified using zeolite imidazole salt framework-8(ZIF-8),enabling the development of efficient ***-8,which is abundant in nitrogen content,efficiently regulates the desolvation of [Zn(H_(2.O)_(6)]^(2.) to inhibit hydrogen ***,it possesses abundant nanochannels that facilitate the uniform deposition of Zn~(2.) via a localized action,thereby hindering the formation of *** insulating properties of ZIF-8 help prevent Zn^(2.) and water from trapping electron reduction at the layer surface,which reduces corrosion of the zinc ***,ZIF-8-GF achieves the even transport of Zn^(2.) and regulates the homogeneous deposition along the Zn(002. crystal surface,thus significantly enhancing the electrochemical performance of the AZIBs,In particular,the Zn|Zn symmetric cell with the ZIF-8-GF separator delivers a stable cycle life at0.5 mA cm^(-2. of 2.00 *** Zn|ZIF-8-GF|MnO_(2. cell exhibits reduced voltage polarization while maintaining a capacity retention rate(93.4%) after 12.0 cycles at 1.2.A g^(-1) The unique design of the modified diaphragm provides a new approach to realizing high-performance AZIBs.

关键词： Aqueous zinc-ion batteries Separators modifications ZIF-8 Zn deposition Dendrite-free

Heavy-atom engineered hypoxia-responsive probes for precisive photoacoustic imaging and cancer therapy

在线全文

学校读者我要写书评

暂无评论

Chinese Chemical Letters 2024年第4期35卷 316-320页

作者： ling-ling Wu Xiangchuan Meng Qingyang Zhang Xiaowan Han Feiya Yang Qinghua {2. Hai-Yu Hu Nianzeng Xing Department of Urology National Cancer Center/National Clinical Research Center for Cancer/Cancer HospitalChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijing 100021China State Key Laboratory of Bioactive Substances and Function of Natural Medicine Institute of Materia MedicaPeking Union Medical College and Chinese Academy of Medical SciencesBeijing 100050China

Photoacoustic agents combining photodynamic therapy(PDT) and photothermal therapy(PTT) functions have emerged as potent theranostic agents for combating cancer. The molecular approaches for enhancing the near-infrared(NIR)-absorption and maximizing non-radiative energy transfer are essential for effective photoacoustic imaging(PAI) and therapy applications. In addition, such molecules with high specificity and affinity to cancer cells are urgently needed, which would further decrease the side effect during treatments. In this study, we applied a heavy-atom engineering strategy and introduced p-aminophenol,-thio, and-seleno moieties into NIR heptamethine cyanine(Cy7) skeleton(Cy7-X-NH_(2., X = O, S, Se) to significantly increase photothermal conversion efficiency for PTT and promote intersystem crossing for ***, we designed a series of nitroreductase(NTR)-activated photoacoustic probes(Cy7-X-NO_(2.,X = O, S, Se), and target hypoxic tumors with NTR overexpression. Our prostate cancer targeting probe,Cy7-Se-NO_(2.-KUE, exhibited specific tumor photoacoustic signals and effective tumor killing through outstanding synergistic PTT/PDT in vivo. These findings highlighted a versatile strategy for cancer photoacoustic diagnosis and enhanced phototherapy.

关键词： Heavy-atom effect Phototherapy Photoacoustic imaging Hypoxia-responsive Prostate cancer

Metal nanoparticles for cancer therapy:Precision targeting of DNA damage

在线全文

学校读者我要写书评

暂无评论

Acta Pharmaceutica Sinica B 2024年第3期14卷 1132-1149页

作者： Qian Chen Chunyan Fang Fan Xia Qiyue wang Fangyuan Li Daishun ling Institute of Pharmaceutics Hangzhou Institute of Innovative MedicineCollege of Pharmaceutical SciencesZhejiang UniversityHangzhou 310058China Frontiers Science Center for Transformative Molecules School of Chemistry and Chemical EngineeringNational Center for Translational MedicineShanghai Jiao Tong UniversityShanghai 200240China World Laureates Association(WLA)Laboratories Shanghai 201203China Key Laboratory of Precision Diagnosis and Treatment for Hepatobiliary and Pancreatic Tumor of Zhejiang Province Hangzhou 310009China

Cancer,a complex and heterogeneous disease,arises from genomic ***,DNA damage-based cancer treatments,including radiotherapy and chemotherapy,are employed in clinical ***,the efficacy and safety of these therapies are constrained by various factors,limiting their ability to meet current clinical *** nanoparticles present promising avenues for enhancing each critical aspect of DNA damage-based cancer *** customizable physicochemical properties enable the development of targeted and personalized treatment *** this review,we delve into the design principles and optimization strategies of metal *** shed light on the limitations of DNA damage-based therapy while highlighting the diverse strategies made possible by metal *** encompass targeted drug delivery,inhibition of DNA repair mechanisms,induction of cell death,and the cascading immune ***,we explore the pivotal role of physicochemical factors such as nanoparticle size,stimuli-responsiveness,and surface modification in shaping metal nanoparticle ***,we present insights into the challenges and future directions of metal nanoparticles in advancing DNA damage-based cancer therapy,paving the way for novel treatment paradigms.

关键词： DNA damage Metal nanoparticles Nucleus-targeting DNA repair inhibition Immune response Size optimization Stimuli-responsiveness Surface modification