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Semi-asynchronous personalized federated learning for short-term photovoltaic power forecasting

Digital Communications and Networks 2023年第5期9卷 1221-1229页

作者： Weishan Zhang Xiao Chen Ke He Leiming Chen Liang Xu Xiao Wang Su Yang College of Computer Science and Technology China University of Petroleum(East China)China Sichuan Energy Internet Research Institute Tsinghua UniversityChina School of Computer and Communication Engineering Beijing University of Science and TechnologyChina State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina School of Computer Science Fudan UniversityChina

Accurate forecasting for photovoltaic power generation is one of the key enablers for the integration of solar photovoltaic systems into power *** deep-learning-based methods can perform well if there are sufficient training data and enough computational ***,there are challenges in building models through centralized shared data due to data privacy concerns and industry *** learning is a new distributed machine learning approach which enables training models across edge devices while data reside *** this paper,we propose an efficient semi-asynchronous federated learning framework for short-term solar power forecasting and evaluate the framework performance using a CNN-LSTM *** design a personalization technique and a semi-asynchronous aggregation strategy to improve the efficiency of the proposed federated forecasting *** evaluations using a real-world dataset demonstrate that the federated models can achieve significantly higher forecasting performance than fully local models while protecting data privacy,and the proposed semi-asynchronous aggregation and the personalization technique can make the forecasting framework more robust in real-world scenarios.

关键词： Photovoltaic power forecasting Federated learning Edge computing CNN-LSTM

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Stochastic Block Models for complex Network Analysis: A Survey

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ACM Transactions on Knowledge Discovery from Data 2025年第3期19卷 1-35页

作者： Liu, Xueyan Song, Wenzhuo Musial, Katarzyna Li, Yang Zhao, Xuehua Yang, Bo College of Computer Science and Technology Jilin University Changchun China School of Information Science and Technology Northeast Normal University Changchun China Complex Adaptive Systems Lab Data Science Institute University of Technology Sydney Sydney Australia Aviation University of the Air Force Changchun China School of Digital Media Shenzhen Institute of Information Technology Shenzhen China Key Laboratory of Symbolic Computation and Knowledge Engineer Jilin University Ministry of Education Changchun China

complex networks enable to represent and characterize the interactions between entities in various complex systems which widely exist in the real world and usually generate vast amounts of data about all the elements, their behaviors and interactions over time. The studies concentrating on new network analysis approaches and methodologies are vital because of the diversity and ubiquity of complex networks. The stochastic block model (SBM), based on Bayesian theory, is a statistical network model. SBMs are essential tools for analyzing complex networks since SBMs have the advantages of interpretability, expressiveness, flexibility and generalization. Thus, designing diverse SBMs and their learning algorithms for various networks has become an intensively researched topic in network analysis and data mining. In this article, we review, in a comprehensive and in-depth manner, SBMs for different types of networks (i.e., model extensions), existing methods (including parameter estimation and model selection) for learning optimal SBMs for given networks and SBMs combined with deep learning. Finally, we provide an outlook on the future research directions of SBMs. © 2025 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： complex Networks Structural Pattern Discovery Stochastic Block models Learning Methods of SBMs

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Maximising Influence Spread in complex Networks by Utilising Community-Based Driver Nodes as Seeds 1

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9th Annual International Conference on Information Management and Big Data, SIMBig 2022

作者： Sadaf, Abida Mathieson, Luke Bródka, Piotr Musial, Katarzyna Complex Adaptive Systems Lab School of Computer Science University of Technology Sydney Sydney Australia Department of Artificial Intelligence Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (数字)9783031354458

ISBN: (纸本)9783031354441

Finding a small subset of influential nodes to maximise influence spread in a complex network is an active area of research. Different methods have been proposed in the past to identify a set of seed nodes that can help achieve a faster spread of influence in the network. This paper combines driver node selection methods from the field of network control, with the divide-and-conquer approach of using community structure to guide the selection of candidate seed nodes from the driver nodes of the communities. The use of driver nodes in communities as seed nodes is a comparatively new idea. We identify communities of synthetic (i.e., Random, Small-World and Scale-Free) networks as well as twenty-two real-world social networks. Driver nodes from those communities are then ranked according to a range of common centrality measures. We compare the influence spreading power of these seed sets to the results of selecting driver nodes at a global level. We show that in both synthetic and real networks, exploiting community structure enhances the power of the resulting seed sets. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： complex networks

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Effect of Zn and Y Additions on Grain Boundary Movement of Mg Binary Alloys During Static Recrystallization

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Acta Metallurgica Sinica(English Letters) 2023年第2期36卷 179-191页

作者： Zhen Jiang Dongfeng Shi Jin Zhang Tianming Li Liwei Lu Light Alloy Research Institute Central South UniversityChangsha410083China State Key Laboratory of High Performance and Complex Manufacturing Central South UniversityChangsha410083China Material Systems for Nanoelectronics Chemnitz University of Technology09111ChemnitzGermany School of Materials Science and Engineering Hunan University of Science and TechnologyXiangtan411201China

Texture evolution in rolled Mg-1 wt%Zn and Mg-1 wt%Y binary alloys was analyzed by quasi-in situ electron backscatter diffraction(EBSD)during static ***-1 wt%Zn and Mg-1 wt%Y alloys exhibited strong basal texture at the initial recrystallization *** grain growth annealing,the basal texture component{0001}<1120>was increased in Mg-1 wt%Zn alloy and that of Mg-1 wt%Y alloy was decreased to be a random *** and Y atoms segregated strongly to the recrystallized grain boundaries in Mg-1 wt%Zn alloy and Mg-1 wt%Y alloy,***,Zn and Y elements facilitated the grain boundary movements along contrary directions during grain *** Mg-1 wt%Zn alloy,due to the Zn element segregation on grain boundaries,the grains consisted of a strong texture grew more easily because the grain boundary migration tended to move from the orientation close to normal direction to the orientation near to transverse direction or rolling ***,after grain growth,the volume fraction of texture component{0001}<1120>was increased by consuming the neighboring grains,leading to a stronger basal *** the contrary,in the Mg-1 wt%Y alloy,the Y element segregation caused the opposite direction of grain boundary migration,resulting in a random texture.

关键词： Static recrystallization Texture evolution Solute segregation

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Distinguishing Sensitive and Insensitive Options for the Winograd Schema Challenge 28th

Distinguishing Sensitive and Insensitive Options for the ...

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28th International Conference on Database systems for Advanced Applications, DASFAA 2023

作者： Li, Dong Wang, Pancheng He, Liangliang Pang, Kunyuan Li, Shasha Tang, Jintao Wang, Ting College of Computer Science and Technology National University of Defense Technology Changsha China Key Laboratory of Software Engineering for Complex Systems Changsha China

ISBN: (纸本)9783031306747

The Winograd Schema Challenge (WSC) is a popular benchmark for commonsense reasoning. Each WSC instance has a component that corresponds to the mention of the correct answer option of the two options in the context. We observe that the answers of many instances are insensitive to the options. In this paper, based on this observation, we propose an approach based on fine-tuning the pre-trained language model for WSC by distinguishing sensitive and insensitive options. First, we split WSC instances into option-sensitive and insensitive categories, and use option expanding and option masking strategies to weaken the options so that the model does not pay attention to options when they are insensitive during fine-tuning. Second, we treat the two categories as intermediate-task of each other, and use transfer learning to improve the performance. We fine-tune BERT-Large and T5-XXL with our approach on WINOGRANDE, a new dataset of WSC, and the experiment shows our method outperforms baselines by a large margin, achieving state-of-the-art, which indicates the effectiveness of our instance-distinguishing strategy. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Large dataset

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On Weighted Compactness of Commutators of Bilinear Vector-valued Singular Integral Operators and Applications

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Acta Mathematica Sinica,English Series 2025年第1期41卷 169-190页

作者： Zhengyang Li Liu Lu Fanghui Liao Qingying Xue School of Mathematics&Computational Science Hu’nan University of Science and TechnologyXiangtan 411201P.R.China School of Mathematics&Computational Science Xiangtan UniversityXiangtan 411105P.R.China School of Mathematical Sciences Laboratory of Mathematics and Complex Systems Ministry of EducationBeijing Normal UniversityBeijing 100875P.R.China

Let T be a bilinear vector-valued singular integral operator satisfies some mild regularity conditions,which may not fall under the scope of the theory of standard Calder¬on–Zygmund *** anyb^(→)=(b_(1),b_(2))∈(CMO(R^(n)))^(2),let[T,b_(j)]e_(j)(j=1,2),[T,→b]_(α)be the commutators in the j-th entry and the iterated commutators of T,*** this paper,for all p_(0)>1,p0/2

关键词： Weighted compactness commutators multilinear square functions Fourier multiplier operator

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Forecast of peak infection and estimate of excess deaths in COVID-19 transmission and prevalence in Taiyuan City,2022 to 2023

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Infectious Disease Modelling 2024年第1期9卷 56-69页

作者： Jia-Lin Wang Xin-Long Xiao Fen-Fen Zhang Xin Pei Ming-Tao Li Ju-Ping Zhang Juan Zhang Gui-Quan Sun Complex Systems Research Center Shanxi UniversityTaiyuan030006China School of Mathematical Sciences Shanxi UniversityTaiyuan030006China School of Mathematics North University of ChinaTaiyuan030051China College of Mathematics Taiyuan University of TechnologyTaiyuan030024China Complex Systems and Data Science Key Laboratory of Ministry of Education Taiyuan030006China

In this paper,with the method of epidemic dynamics,we assess the spread and prevalence of COVID-19 after the policy adjustment of prevention and control measure in December 2022 in Taiyuan City in China,and estimate the excess population deaths caused by *** on the transmission mechanism of COVID-19 among individuals,a dynamic model with heterogeneous contacts is established to describe the change of control measures and the population's social behavior in Taiyuan *** model is verified and simulated by basing on reported case data from November 8th to December 5th,2022 in Taiyuan city and the statistical data of the questionnaire survey from December 1st to 23rd,2022 in Neijiang *** with reported numbers of permanent residents and deaths from 2017 to 2021 in Taiyuan city,we apply the dynamic model to estimate theoretical population of 2022 under the assumption that there is no effect of *** addition,we carry out sensitivity analysis to determine the propagation character of the Omicron strain and the effect of the control *** a result of the study,it is concluded that after adjusting the epidemic policy on December 6th,2022,three peaks of infection in Taiyuan are estimated to be from December 22nd to 31st,2022,from May 10th to June 1st,2023,and from September 5th to October 13th,2023,and the corresponding daily peaks of new cases can reach 400000,44000 and 22000,*** the end of 2022,excess deaths can range from 887 to 4887,and excess mortality rate can range from 3.06%to 14.82%.The threshold of the infectivity of the COVID-19 variant is estimated 0.0353,that is if the strain infectivity is above it,the epidemic cannot be control with the previous normalization measures.

关键词： Taiyuan city COVID-19 Dynamic model Epidemic scale Epidemic peak Excess death

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Porous carbon material production from microwave-assisted pyrolysis of peanut shell

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Carbon Research 2023年第1期2卷 1-17页

作者： Qiu, Tianhao Li, Chengxiang Guang, Mengmeng Zhang, Yaning School of Energy Science and Engineering Harbin Institute of Technology Harbin150001 China State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China

Due to the complex porous structure, biochar usually has good adsorption capacity. Therefore, compared with direct combustion, conversion of peanut shell into biochar by pyrolysis is considered to be an environmentally friendly and efficient method for agricultural solid waste disposal. In this study, biochar production from microwave-assisted pyrolysis of peanut shell was detailed. The yields, surface topographies, and pore structures (pore size distribution and micropore volume) of biochars prepared at different pyrolysis temperatures (700, 750, 800, 850, 900, and 950 °C), microwave powers (350, 400, 450, 500, and 550 W), and residence times (0.5, 1.0, 1.5, 2.0, and 3.0 h) were elaborated. The results showed that the biochar yield gradually decreased and finally stabilized to around 30% while the specific surface area improved within the range of 4.68–67.29 m2/g when the pyrolysis temperature, microwave power, or residence time increased. Biochar with micropore was first obtained at pyrolysis temperature of 800 °C, microwave power of 500 W, and residence time of 2.0 h. This study further proposed quantitative relationships between the pore structures of peanut shell based biochars and experimental conditions (pyrolysis temperature, microwave power and residence time). The results presented in this study can provide guidance for the reuse of peanut shell and the production of porous biochar. The peanut shell biochar prepared in this study can be used in soil remediation, air purification, liquid purification and other fields for its porous structural characteristics. © 2023, The Author(s).

关键词： Waste incineration

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Mitigating overtrust towards robot in mixed reality interfaces 1

Mitigating overtrust towards robot in mixed reality interfac...

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1st International Conference on Artificial Intelligence and Human-Computer Interaction, ArtInHCI 2023

作者： He, Di Zhao, Changshun Zhang, Kaiyue Yang, Hongrong Liu, Ying University of Electronic Science and Technology of China Chengdu China National Key Laboratory for Complex Systems Simulation Beijing China Officers College of PAP Chengdu China

ISBN: (纸本)9781643685083

This research focuses on the role of trust in human-agent interaction, particularly in the context of home robot systems. The study found that participants were more likely to collaborate when they understood the agent's intentions. The research involved 36 participants working with an agent across three different interfaces to complete household tasks. The results showed that clear agent intentions can increase cooperation and calibrate trust to an appropriate level. © 2024 The Authors.

关键词： Human robot interaction

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Energy-Saving Distributed Flexible Job Shop Scheduling Optimization with Dual Resource Constraints Based on Integrated Q-Learning Multi-Objective Grey Wolf Optimizer

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Computer Modeling in Engineering & sciences 2024年第8期140卷 1459-1483页

作者： Hongliang Zhang Yi Chen Yuteng Zhang Gongjie Xu School of Management Science and Engineering Anhui University of TechnologyMa’anshan243032China Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes Anhui University of TechnologyMa’anshan243032China Department of Industrial Engineering School of Mechanical EngineeringNorthwestern Polytechnical UniversityXi’an710072China

The distributed flexible job shop scheduling problem(DFJSP)has attracted great attention with the growth of the global manufacturing *** DFJSP research only considers machine constraints and ignores worker *** one critical factor of production,effective utilization of worker resources can increase ***,energy consumption is a growing concern due to the increasingly serious environmental ***,the distributed flexible job shop scheduling problem with dual resource constraints(DFJSP-DRC)for minimizing makespan and total energy consumption is studied in this *** solve the problem,we present a multi-objective mathematical model for DFJSP-DRC and propose a Q-learning-based multi-objective grey wolf optimizer(Q-MOGWO).In Q-MOGWO,high-quality initial solutions are generated by a hybrid initialization strategy,and an improved active decoding strategy is designed to obtain the scheduling *** further enhance the local search capability and expand the solution space,two wolf predation strategies and three critical factory neighborhood structures based on Q-learning are *** strategies and structures enable Q-MOGWO to explore the solution space more efficiently and thus find better Pareto *** effectiveness of Q-MOGWO in addressing DFJSP-DRC is verified through comparison with four algorithms using 45 *** results reveal that Q-MOGWO outperforms comparison algorithms in terms of solution quality.

关键词： Distributed flexible job shop scheduling problem dual resource constraints energy-saving scheduling multi-objective grey wolf optimizer Q-learning

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