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International Conference on Information Science and Technology (ICIST)

作者： Haoran Lv Junmin Mou Liang Zhang Mengxia Li Pengfei Chen School of Navigation Wuhan University of Technology Wuhan China State Key Laboratory of Maritime Technology and Safety Wuhan China Intelligent Transportation System Research Center Wuhan University of Technology Wuhan China

ISBN: (数字)9798350353334

ISBN: (纸本)9798350353341

Intended to solve the problem of poor generalization of complex collision risk model, this paper proposes a novel collision risk model based on data-driven. Firstly, the main traffic pattern is clustered by Ordering Points to Identify the Clustering Structure algorithm. Afterwards, using probability statistics and mining the altering behaviors identify the abnormal behavior. And then, encounter situation and avoidance behaviors are identified by analyzing the relative motion characteristics of the two ships. Finally, by Kullback-Leibler dispersion and kernel density estimation methods, the key parameters are extracted from encounter data with avoidance behaviors. The collision risk model based on data-driven is constructed. To verify the effectiveness of the proposed method, the method is used in a heavy traffic area, the mouth of Yangtze River, China. The results show that the collision risk model based on data-driven can be more accurate.

关键词： Accuracy Navigation Clustering algorithms Traffic control Data models Trajectory Rivers Data mining Marine vehicles Artificial intelligence

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Study on Capacity Ratio Optimization of Multi-Energy Power system 5

Study on Capacity Ratio Optimization of Multi-Energy Power S...

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5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022

作者： Li, Wensheng Yang, Bin Yuan, Zhenhua Huang, Dan Cheng, Peifen Yun, Jiangyang State Grid Shandong Electric Power Company Economic & Technology Research Institute Jinan China China Electric Power Research Institute Beijing China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China

ISBN: (纸本)9781665479059

In order to achieve the goal of "double carbon", it is urgent to build a new power system with new energy as the main body. It is vital for the construction and planning of new power system to reasonably optimize the installed ratio of various power supplies. To this end, this paper proposes a capacity allocation optimization method of multi energy power system based on complementary equilibrium theory, and establishes the capacity optimization models of multi-energy system such as wind power, thermal power, nuclear power and energy storage with the objective of minimizing the operation cost of the whole network. The model adopts the load characteristics, the output characteristics of new energy and the operation characteristics of energy storage power stations in the target power grid. The annual output time series of wind/photovoltaic and the load series are used as the input of the model. Through the annual time series production simulation calculation, the optimal capacity ratio of wind-photovoltaic-thermal-nuclear-storage system is determined to meet the conditions. Finally, a regional power grid in China is demonstrated as an example to verify the effectiveness and practicability of the proposed model and method. © 2022 IEEE.

关键词： Costs Time series analysis Optimization methods Production Power grids Power systems Planning

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Rethinking Dimensional Rationale in Graph Contrastive Learning from Causal Perspective

arXiv

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arXiv 2023年

作者： Ji, Qirui Li, Jiangmeng Hu, Jie Wang, Rui Zheng, Changwen Xu, Fanjiang Science & Technology on Integrated Information System Laboratory Institute of Software Chinese Academy of Sciences China State Key Laboratory of Intelligent Game China University of Chinese Academy of Sciences China State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China

Graph contrastive learning is a general learning paradigm excelling at capturing invariant information from diverse perturbations in graphs. Recent works focus on exploring the structural rationale from graphs, thereby increasing the discriminability of the invariant information. However, such methods may incur in the mis-learning of graph models towards the interpretability of graphs, and thus the learned noisy and task-agnostic information interferes with the prediction of graphs. To this end, with the purpose of exploring the intrinsic rationale of graphs, we accordingly propose to capture the dimensional rationale from graphs, which has not received sufficient attention in the literature. The conducted exploratory experiments attest to the feasibility of the aforementioned roadmap. To elucidate the innate mechanism behind the performance improvement arising from the dimensional rationale, we rethink the dimensional rationale in graph contrastive learning from a causal perspective and further formalize the causality among the variables in the pre-training stage to build the corresponding structural causal model. On the basis of the understanding of the structural causal model, we propose the dimensional rationale-aware graph contrastive learning approach, which introduces a learnable dimensional rationale acquiring network and a redundancy reduction constraint. The learnable dimensional rationale acquiring network is updated by leveraging a bi-level meta-learning technique, and the redundancy reduction constraint disentangles the redundant features through a decorrelation process during learning. Empirically, compared with state-of-the-art methods, our method can yield significant performance boosts on various benchmarks with respect to discriminability and transferability. The code implementation of our method is available at https://***/ByronJi/DRGCL. Copyright © 2023, The Authors. All rights reserved.

关键词： Graphic methods

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A Transient Voltage Stability Preventive Control Strategy for DC Receiving-end Power system 8

A Transient Voltage Stability Preventive Control Strategy fo...

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8th International Conference on Power and Renewable Energy, ICPRE 2023

作者： Tu, Lian Zhang, Shuiping Guo, Hengdao Bao, Bo Zhu, Yihua Zuo, Jian Power Dispatch and Control Center of Guangdong Power Grid Co. Ltd China Southern Power Grid 510000 China State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid 510663 China National Energy Power Grid Technology R&D Centre 510663 China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System 510663 China

ISBN: (纸本)9798350328813

With the increase of DC feed power and the decrease of the number of synchronous machines, receiving-end power system takes a serious threat to the transient voltage stability. Therefore, a transient voltage stability preventive control strategy for DC receiving-end power system is proposed in this paper. The whole method is decomposed into three sub-problems: transient voltage stability assessment, sensitivity computation and optimal control. A transient voltage stability index suitable for the sensitivity method is used to construct the transient voltage stability constraints. The accuracy and efficiency of the solution algorithm are improved by limiting the effective control interval of sensitivity and selection of the initial control set. The method has been applied in a provincial power grid in southern China. The results verifies the effectiveness of the proposed method. © 2023 IEEE.

关键词： DC receiving-end power system preventive control sensitivity transient voltage stability

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Predicting influenza-like illness trends based on sentinel surveillance data in China from 2011 to 2019:A modelling and comparative study

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Infectious Disease Modelling 2024年第3期9卷 816-827页

作者： Xingxing Zhang Liuyang Yang Teng Chen Qing Wang Jin Yang Ting Zhang Jiao Yang Hongqing Zhao Shengjie Lai Luzhao Feng Weizhong Yang School of Population Medicine and Public Health Chinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing100073China State Key Laboratory of Respiratory Health and Multimorbidity China Key Laboratory of Pathogen Infection Prevention and Control(Peking Union Medical College) Ministry of EducationChina National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionChina Department of Management Science and Information System Faculty of Management and EconomicsKunming University of Science and TechnologyKunming650506China Department of Applied Mathematics&Statistics Stony Brook UniversityStony BrookNY11794-3600USA WorldPop School of Geography and Environmental ScienceUniversity of SouthamptonSouthamptonSO171BJUK

Background Influenza is an acute respiratory infectious disease with a significant global disease ***,the coronavirus disease 2019 pandemic and its related non-pharmaceutical interventions(NPIs)have introduced uncertainty to the spread of ***,comparative studies on the performance of innovative models and approaches used for influenza prediction are ***,this study aimed to predict the trend of influenza-like illness(ILI)in settings with diverse climate characteristics in China based on sentinel surveillance data using three approaches and evaluate and compare their predictive *** The generalized additive model(GAM),deep learning hybrid model based on Gate Recurrent Unit(GRU),and autoregressive moving average-generalized autoregressive conditional heteroscedasticity(ARMA—GARCH)model were established to predict the trends of ILI 1-,2-,3-,and 4-week-ahead in Beijing,Tianjin,Shanxi,Hubei,Chongqing,Guangdong,Hainan,and the Hong Kong Special Administrative Region in China,based on sentinel surveillance data from 2011 to *** relevant metrics,namely,Mean Absolute Percentage Error(MAPE),Root Mean Squared Error(RMSE),and R squared,were calculated to evaluate and compare the goodness of fit and robustness of the three *** Considering the MAPE,RMSE,and R squared values,the ARMA—GARCH model performed best,while the GRU-based deep learning hybrid model exhibited moderate performance and GAM made predictions with the least accuracy in the eight settings in ***,the models’predictive performance declined as the weeks ahead ***,blocked cross-validation indicated that all models were robust to changes in data and had low risks of *** Our study suggested that the ARMA—GARCH model exhibited the best accuracy in predicting ILI trends in China compared to the GAM and GRU-based deep learning hybrid ***,in the future,the ARMA—GARCH model may be used

关键词： Influenza-like illness Influenza Sentinel surveillance China Predicting Modeling

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Interaction between internal solitary waves and the seafloor in the deep sea

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Deep Underground Science and Engineering 2024年第2期3卷 149-162页

作者： Zhuangcai Tian Jinjian Huang Jiaming Xiang Shaotong Zhang Jinran Wu Xiaolei Liu Tingting Luo Jianhua Yue State Key Laboratory of Intelligent Construction and Healthy Operation and Maintenance of Deep Underground Engineering China University of Mining and TechnologyXuzhouChina Research Center for Deep Ocean Science and Underwater Engineering China University of Mining and TechnologyXuzhouChina Frontiers Science Center for Deep Ocean Multispheres and Earth System Key Lab of Submarine Geosciences and Prospecting TechniquesMOECollege of Marine GeosciencesOcean University of ChinaQingdaoChina Institute for Learning Sciences&Teacher Education Australian Catholic UniversityBrisbaneQueenslandAustralia Shandong Provincial Key Laboratory of Marine Environment and Geological Engineering Ocean University of ChinaQingdaoChina Department of Chemical and Biomolecular Engineering National University of SingaporeSingaporeSingapore School of Resources and Geosciences China University of Mining and TechnologyXuzhouChina

Internal solitary wave(ISW),as a typical marine dynamic process in the deep sea,widely exists in oceans and marginal seas *** interaction between ISW and the seafloor mainly occurs in the bottom boundary *** the seabed boundary layer of the deep sea,ISW is the most important dynamic *** study analyzed the current status,hotspots,and frontiers of research on the interaction between ISW and the seafloor by *** on the action of ISW on the seabed,such as transformation and reaction,a large amount of research work and results were systematically analyzed and *** this basis,this study analyzed the wave–wave interaction and interaction between ISW and the bedform or slope of the seabed,which provided a new perspective for an in‐depth understanding of the interaction between ISW and the ***,the latest research results of the bottom boundary layer and marine engineering stability by ISW were introduced,and the unresolved problems in the current research work were *** study provides a valuable reference for further research on the hazards of ISW to marine engineering geology.

关键词： bottom boundary layer interaction internal solitary wave seafloor sediment

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Tuning Mechanical Behaviors of Highly Entangled Hydrogels with the Random Distribution of Mobile Entanglements

SSRN

引用

SSRN 2023年

作者： Liu, Jinlong Lu, Di Chen, Bin Department of Engineering Mechanics Zhejiang University Hangzhou China Intelligent Robotic Research Center Zhejiang Laboratory Hangzhou311100 China Key Laboratory of Soft Machines and Smart Devices of Zhejiang Province Hangzhou China Beijing System Design Institute of the Electro-mechanic Engineering Beijing China

Highly entangled hydrogels exhibit excellent mechanical properties, including high toughness, high stretchability, low hysteresis, etc. By considering the evolution of randomly distributed entanglements within the polymer network upon mechanical stretches, here we have developed a constitutive theory to describe the large stretch behaviors of these hydrogels. In the theory, we utilize a representative volume element in the shape of a cube, within which there exist one averaged chain segment along each edge and a mobile entanglement at each corner. By employing an explicit method, we decouple the elasticity of the hydrogels from the sliding motion of the entanglements within them and derive the stress-stretch relations for these hydrogels. Our theoretical analysis is in agreement with experiment and highlights the significant influence of the entanglement distribution within the hydrogels on their elasticity. We have also implemented our developed constitutive theory into a commercial finite element software and subsequent simulations demonstrate that the exact distribution of entanglements strongly affects mechanical behaviors of structures of these hydrogels. Overall, our theory provides valuable insights into the deformation mechanism of highly entangled hydrogels and can aid in the design of these hydrogels with enhanced performance. © 2023, The Authors. All rights reserved.

关键词： Hydrogels

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Cooperative Prediction Approach for the Small-Signal Stability Margin of Renewable Power system Based on Vertical Federated Learning

Cooperative Prediction Approach for the Small-Signal Stabili...

引用

Power systems and Electrical Technology (PSET), IEEE International Conference on

作者： Xiang Lai Zhihao Chen Yun Liu Tianchen Dai Haiqing Cai Haohan Gu Wei Chen School of Electric Power Engineering South China University of Technology Guangzhou China State Key Laboratory of HVDC CSG Electric Power Research Institute Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China

ISBN: (数字)9798350353204

ISBN: (纸本)9798350353211

Since sub-synchronous oscillations have been frequently witnessed in large-scale wind farms under weak grid conditions, it is significant to predict the critical stability situations in short term so that timely preventative actions can be taken to avoid potential small-signal stability (SS) risks. To this end, this paper proposes a SS prediction approach based on the grid strength metric of generalized short-circuit ratio (gSCR) under the mechanism of vertical federated learning. Specifically, the improved ridge regression prediction model is employed and its corresponding distributed training and the distributed predicting are derived by utilizing the separable characteristic of gradient vector calculation in the context of federated learning. On this basis, the original largescale predicting problem is decomposed into a large number of small-scale subproblems, and each subproblem is calculated locally by the corresponding wind farm. The feature data information of adjacent wind farms can be effectively used to improve the accuracy of the prediction of the stability margin while ensuring the data privacy and security of all participants. Finally, simulation results illustrate the effectiveness and efficiency of the proposed approach under various scenarios.

关键词： Training Accuracy Federated learning Simulation Power system stability Wind farms Predictive models Stability analysis Vectors Security

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DogGet: A Legged Manipulation system in Human Environments 12

DogGet: A Legged Manipulation System in Human Environments

引用

12th International Conference on CYBER Technology in Automation, Control, and intelligent systems, CYBER 2022

作者： Linghan, Meng Cong, Wang Shengguo, Cui Qifeng, Zhang Baoqi, Zhai State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Guangzhou511458 China Key Laboratory of Marine Robotics Liaoning Province Shenyang110169 China University of the Chinese Academy of Sciences Beijing100049 China Guangdong Institute of Intelligent Unmanned System Guangzhou511458 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

The problem of population ageing in today's world is becoming increasingly serious, and the capacity gap in the service industry for elderly people is increasing. Especially in the current epidemic environment, the deartificialization of the service industry is imminent. For service tasks of seniors, there is no doubt that legged robots are the best choice for service tasks due to there flexibility and agility. However, complex service tasks require a mobile robotic system that integrates functions such as localization, navigation, recognition, and grasping. To this end, we propose a mobile robotic system to accomplish some daily service work such as finding and grasping some articles for daily use and then delivering them to a proposed place. We show that the system is universally applicable and highly efficient in daily environments. Videos of the experiments can be viewed at https://***/xPeBzDf6D_k or https://***/video/BV1QZ4yli7qx. © 2022 IEEE.

关键词： HTTP

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A Novel Thrust Allocation Method for Underwater Robots 12

A Novel Thrust Allocation Method for Underwater Robots

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12th International Conference on CYBER Technology in Automation, Control, and intelligent systems, CYBER 2022

作者： Zheng, Xin-Hui Wang, Cong Yang, Xue-Jiao Tian, Qi-Yan Zhang, Qi-Feng Zhai, Bao-Qi State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Guangzhou511458 China Key Laboratory of Marine Robotics Liaoning Province Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Guangdong Institute of Intelligent Unmanned System Guangzhou511458 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Underwater vehicles with normal thruster configuration methods are unsatisfying in position-keeping tasks because of their limited manoeuvrability. To this end, this paper proposes an underwater ve-hicle with a novel thruster configuration method and solves the thrust allocation problem by the sequential quadratic programming(SQP) algorithm. Comparisons between the performance of the proposed thruster configuration method and the most widely used config-uration method are given based on the UUVSimulator and Gazebo. Numerical simulations show that vehicle with the proposed thrust configuration method has better performance in manoeuvrability and energy consumption. © 2022 IEEE.

关键词： Energy utilization

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