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A cellular automata downscaling based 1 km global land use datasets (2010–2100)

Science Bulletin 2016年第21期61卷 1651-1661页

作者：李雪草俞乐徐伊迪杨军宫鹏 Terry Sohl Nicholas Clinton Wenyu Li Zhiliang Zhu Xiaoping Liu Ministry of Education Key Laboratory for Earth System Modeling Center for Earth System Science Tsinghua University Joint Center for Global Change Studies U.S. Geological Survey Earth Resources Observation and Science (EROS) Center U.S. Geological Survey School of Geography and Planning and Guangdong Key Laboratory for Urbanization and Geo-simulation Sun Yat-sen University

Global climate and environmental change studies require detailed land-use and land-cover （LULC） information about the past, present, and future. In this paper, we discuss a methodology for downscaling coarse-resolution （i.e., half-degree） future land use scenarios to finer （i.e., 1 km） resolutions at the global scale using a grid-based spatially explicit cellular automata （CA） model. We account for spatial heterogeneity from topography, climate, soils, and socioeconomic variables. The model uses a global 30 m land cover map （2010） as the base input, a variety of biogeographic and socioeconomic variables, and an empirical analysis to downscale coarse-resolution land use information （specifically urban, crop and pasture）. The output of this model offers the most current and finest-scale future LULC dynamics from 2010 to 2100 （with four representative concentration pathway （RCP） scenarios--RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5） at a 1 km resolution within a globally consistent framework. The data are freely available for download, and will enable researchers to study the impacts of LULC change at the local scale.

关键词： LULC modeling Spatial downscaling RCP scenarios Urban expansion

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Hidden Failure Prognosis For Navigation Inertial Platform Using Belief Rule Base Expert system

Hidden Failure Prognosis For Navigation Inertial Platform Us...

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2017 9th International Conference on Modelling, Identification and Control (ICMIC 2017)

作者： Run-Fan Han Gui-Ming Chen Tian-Jun Liao Xiao-Dong Ling Lei-Lei Chang the High-tech Institute of Xi’an the State Key Laboratory of Complex System Simulation Beijing Institute of System Engineering the China Satellite Maritime Tracking and Control Laboratory

The gyro drift is the main factor in affecting the performance of the inertial platform which is an important unit in the navigation *** belief rule base(BRB) is used to construct the failure prognosis model of the inertial platform which holds the following characteristics:(1) the storage lives are long and working lives are short,(2) a lot of testing data can not be obtained,(3) some expert knowledge may be available,and(4) the failure is *** order to solve the problems,two sub-BRBs are used with one employed to capture the relationship between the external stress and hidden failure and the other to construct the forecasting model of hidden *** experimental case study is examined to demonstrate the implementation and potential applications of the proposed failure prognosis model.

关键词： Belief rule base expert system hidden failure prognosis navigation inertial platform

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Warming Up A Backup Control Barrier Function

Warming Up A Backup Control Barrier Function

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2024 China Automation Congress, CAC 2024

作者： Wang, Weijia Meng, Tao Zhao, Xiaofeng Lei, Jiakun Wang, Kun Zhejiang University School of Aeronautics and Astronautics Zhejiang Hangzhou China Modeling and Simulation of Complex Systems National Key Laboratory Beijing China Hagnzhou International Innovation Institute of Beihang University Zhejiang Hangzhou China Beihang University Hangzhou Innovation Istitute Zhejiang Hangzhou China

ISBN: (纸本)9798350368604

Backup control barrier function (Backup CBF) is a tractable formulation that ensure the feasibility of CBF-based quadratic programming (QP) problems through implicitly defined control invariant set. Backup CBF is based on two fundamental ingredients: a known backup set and a fixed backup policy, and the implicitly defined control invariant set is evaluated through forward integration by backup policy in a finite horizon online. However, there is a lack of systematic methods for providing the backup set and backup policy for a system with input constraints, making it difficult to synthesize a backup CBF. In this paper, we propose a method for second-order systems to obtain backup policy and backup set practically, rather than empirical choice, by constructing a more conservative explicit CBF-QP with auxiliary velocity constraints integrated. The proposed method warms up a backup CBF by an explicit conservative CBF-QP under mild assumptions, while without excessive conservatism, allowing the tasks of safety and feasibility to be guaranteed theoretically. We demonstrate the efficacy of the proposed method in simulation. © 2024 IEEE.

关键词： Quadratic programming

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Sectoral Crediting Mechanism: How to Work in China

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Energy Procedia 2016年 88卷 187-192页

作者： Shuai Gao Can Wang State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC) and School of Environment Tsinghua University Beijing 100084 China Ministry of Education Key Laboratory for Earth System Modeling Center for Earth System Science Tsinghua University Beijing 100084 China

Using the method of conjoint analysis, this paper assesses corporate preferences for the policy alternatives of the sectoral crediting mechanism (SCM) aiming at supporting the discussions and development of this instrument. Data was collected in all 11 prefecture-level cities of Shanxi province, China. modeling analysis confirms that companies are most concerned about the following three policy attributes, domestic policy instruments, the relationship with the clean developing mechanism (CDM) and the principle of Common but Differentiated Responsibilities (CBDR). Companies prefer a policy alternative that has a domestic policy instrument in which installations with voluntary targets receive tradable units, can co-exist with the CDM, and can get financial and technical assistance from developed countries. Meanwhile, the coverage of the SCM has the potential to expand to small companies that are the most inefficient under the premise of controlling transaction costs.

关键词： Sectoral crediting mechanism Companies Conjoint analysis China

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DMGA: A Directional-Mutation Genetic Algorithm for CDMS Problem of Kafka

DMGA: A Directional-Mutation Genetic Algorithm for CDMS Prob...

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IEEE International Conference on Networking, Sensing and Control

作者： Hanbo Ma Yaofei Ma Haitao Yuan Meijia Wang Jingwei Hu Yihuan Wang Hanbo Yang School of Automation Science and Electrical Engineering Beihang University Beijing China Beijing Simulation Center National Key Laboratory of Modeling and Simulation for Complex Systems Beijing China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

With the increasing role of distributed message systems (DMS) represented by Kafka in handling large-scale data streams, it is critical to improve system performance by optimizing configuration parameters in different production environments. Due to the target system possessing numerous configuration parameters and the complex interactions between them, parameter optimization becomes a complex and time-consuming process that relies heavily on human effort and an iterative trial-and-error approach. At present, this type of configuration parameter problem has been classified as the Configuration of Distributed Message systems (CDMS) problem, for which the goal is to obtain the optimal set of parameters for achieving the best performance. In order to deal with this complex problem, an automatic optimization method is proposed in this paper, which combines an automatic script-based deployment and running framework with an improved Genetic Algorithm (GA) in cooperation with the Random Forest (RF) and statistical methods, named the Directional-Mutation Genetic Algorithm (DMGA). The framework and algorithm are designed to find the best configuration efficiently, obtaining optimal parameters accurately without human supervision. Actual results of comparison experiments based on the Kafka system show that the DMGA algorithm significantly improves the data throughput performance of Kafka, and its optimization speed is more efficient than the basic GA, highlighting its potential to quickly optimize Kafka's operational efficiency in different scenarios.

关键词： Statistical analysis system performance Production Throughput Sensors Tuning Streams Genetic algorithms Message systems Convergence

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International market mechanism under Paris Agreement: Insights from China

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Energy Procedia 2018年 152卷 829-834页

The international discussion on the design of international market mechanism proposed in Paris agreement is still pending and it is important to add our views to the discussion in the negotiation. It is important to understand companies’ preferences in designing and planning market-based instruments. This paper uses the conjoint analysis to evaluate companies’ preferences for policy alternatives of this mechanism. Data were collected from 81 companies in Shanxi province, China. The results show that companies are most concerned about four policy attributes, policies at the national level, transition of CDM projects, compliance period and flexible mechanism. The ideal policy alternative should distribute directly the tradable units to companies, co-exist with the clean developing mechanism, have longer compliance period and allow companies to bank or borrow the tradable units. The sectors with lower competition level, advanced production technologies and lower energy intensity should be given to priority when taking part in the international market mechanism.

关键词： International market mechanism MSDM Paris agreement Conjoint analysis China

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Optimizing the Power Generation Structure for Low Carbon Development Target in China: A Comparison Study of Endogenous and Exogenous Technology Improvements

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Energy Procedia 2019年 158卷 4055-4060页

作者： Hai Huang Jingxuan Hui Wenjia Cai Can Wang State Key Joint Laboratory of Environment Simulation and Pollution Control (SKLESPC) and School of Environment Tsinghua University Beijing 100084 China Ministry of Education Key Laboratory for Earth System Modeling and Department of Earth System Science Tsinghua University Beijing 100084 China

The power generation system will play a decisive role in realizing China’s low carbon development goals. When identifying the optimized power generation structure to meet a set of given low carbon goals, the technology parameters are an important determinant of the results. In previous studies, most models exogenously set the technologies’ cost changes, which usually bring a great bias. This article establishes an endogenous (for solar photovoltaic and wind power generation technology costs) optimization model of China’s power sector and simulated the sector from 2014 to 2040. Two scenarios were built to investigate the optimized performance of the power sector: the Business as Usual scenario (BAU) and the Intended National Determined Contribution scenario (NDC). In addition, this paper compares the differences in the optimization results under the two methods for treatment of technology change in the model, exogenous and endogenous. In the BAU scenario, emerging technologies account for 40.7% of the total installed capacity in 2040. Due to the variation of the costs in the exogenous setting, the solar power and other emerging technologies develop slowly and the optimization results are significantly different from that of the endogenous setting. In the NDC scenario, the proportion of emerging technologies increases more, accounting for 43.7% of the total installed capacity, of which wind power and solar power account for 12.2% and 11.5% respectively, and the total CO 2 emissions peak around 2033. We conclude from the comparison that, for the NDC scenarios, although there are some differences in investment cost in the first few years, different settings for technology change in the model don’t significantly affect the renewable energy demand and final policy decisions.

关键词： power sector technology parameters learning curve carbon dioxide emissions

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Autonomous Decision Making with Reinforcement Learning in Multi-UAV Air Combat

Autonomous Decision Making with Reinforcement Learning in Mu...

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IEEE International Conference on systems, Man and Cybernetics

作者： Xutao Feng Yaofei Ma Liping Zhao Hanbo Yang Beihang University School of Automation Science and Electrical Engineering Beijing China National Key Laboratory of Modeling and Simulation for Complex Systems Beijing Simulation Center Beijing China

A multi-agent decision network based on QMIX is proposed in this paper to cope with the coordination decision problem of multiple UAV air combat missions. To speed up the training process, three improvements are introduced: 1) An improved $\epsilon$ -decaying method that enable some tutor to help in action selection at the early stage of the training. This measure greatly improves the exploring efficiency when the network are far from being fully trained; 2) State pruning and action mask measures are applied during the training. The former improves the effectiveness of the input state information, and the latter reduces unnecessary action exploring. 3) A gradually training configuration is used to make the training process more robust, where the combat adversaries are configured as the static targets, the randomly maneuver vehicles, and the Min-Max strategy vehicles respectively. The multi-UAV air combat scenarios are built up and the experiments are conducted. The results shows that these improvements have significantly improved training efficiency.

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Foreword

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Particuology 2011年第4期9卷 319-319页

作者： Ning Yang Wei Ge Jinghai Li State key laboratory of Multiphase complex systems, Institute of Process Engineering, Chinese Academy of Sciences, Beijing 100190, China Aibing Yu laboratory for simulation and modeling of Particulate systems, School of Materials Science and Engineering, The University of New South Wales, Sydney, NSW 2052, Australia State Key Laboratory of Multiphase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing 100190 China Laboratory for Simulation and Modeling of Particulate Systems School of Materials Science and Engineering The University of New South Wales Sydney NSW 2052 Australia

Granular materials are ubiquitous in nature and engineering. They display both fluid- and solid-like behavior with fascinating complexity and remarkable uniqueness. Their behavior at different scales is strongly coupl... 详细信息

关键词： materials different Understanding size effects structures complexity challenge products display nature high

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MD-TransUNet: TransUNet with Multi-attention and Dilated Convolution for Brain Stroke Lesion Segmentation 19th

MD-TransUNet: TransUNet with Multi-attention and Dilated C...

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19th EAI International Conference on Collaborative Computing: Networking, Applications and Worksharing, CollaborateCom 2023

作者： Xu, Jie Wan, Jian Zhang, Xin School of Computer Science and Technology Hangzhou Dianzi University Zhejiang310018 China Key Laboratory of Complex Systems Modeling and Simulation Ministry of Education Ministry of Education Beijing China School of Information and Electronic Engineering Zhejiang University of Science and Technology Zhejiang China Key Laboratory of Marine Ecosystem Dynamics Second Institute of Oceanography Ministry of Natural Resources Hangzhou China

ISBN: (纸本)9783031545276

The accurate segmentation of stroke lesion regions holds immense significance in shaping treatment strategies and rehabilitation protocols. Due to the large difference in the volume of stroke lesion areas and the great similarity between lesion areas and normal tissues, most of the existing methods for lesion segmentation cannot deal with these problems well. This paper proposes a novel network named MD-TransUNet for the segmentation of stroke lesions, whose framework is based on the UNet architecture. To fully obtain deep image features, it uses ResNet50 for downsampling. MD (multi-dilated) module is employed as the skip connection to gain more receptive fields. Different receptive fields can adapt to varying volumes of lesion areas. Then, a feature extraction module with multi-level attention mechanism is designed using ConvLSTM, non-local spatial attention, and channel attention modules to suppress useless information expression in skip connections and upsampling processes while focusing more on effective spatial and channel information in features. The experiments show that our proposed network gets superior performance than benchmark methods and indicates the generalization and effectiveness of the proposed model. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Convolution

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