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China’s carbon neutrality:an extensive and profound systemic reform

Frontiers of Environmental Science & Engineering 2023年第2期17卷 1-7页

作者： Xi Lu Dan Tong Kebin He State Key Joint Laboratory of Environment Simulation and Pollution Control and School of Environment Tsinghua UniversityBeijing 100084China Institute for Carbon Neutrality Tsinghua UniversityBeijing 100084China Beijing Laboratory of Environmental Frontier Technologies Tsinghua UniversityBeijing 100084China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing 100084China Department of Earth System Science Ministry of Education Key Laboratory for Earth System ModelingInstitute for Global Change StudiesTsinghua UniversityBeijing 100084China

China is the largest developing economy and carbon dioxide emitter in the world,the carbon neutrality goal of which will have a profound influence on the mitigation pathway of global climate *** transition towards a carbon-neutral society is integrated into the construction of ecological civilization in China,and brings profound implications for China’s socioeconomic ***,we not only summarize the major challenges in achieving carbon neutrality in China,but also identify the four potential new opportunities:namely,the acceleration of technology innovations,narrowing regional disparity by reshaping the value of resources,transforming the industrial structure,and co-benefits of pollution and carbon ***,we provide five policy suggestions and highlight the importance of balancing economic growth and carbon mitigation,and the joint efforts among the government,the enterprises,and the residents.

关键词： Carbon neutrality Energy structure Technology-dependent society Coordinated mitigation for air pollutants and CO_(2)

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Error correction iterative finite element method based on charge-conservative for the stationary inductionless magnetohydrodynamic system

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ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik 2025年第5期105卷

作者： Yande Xia Yun-Bo Yang Department of Mathematics Yunnan Normal University Kunming PR China Yunnan Key Laboratory of Model Analytical Mathematics and Application Yunnan Normal University Kunming PR China Key Laboratory of Complex System Modeling and Application for Universities in Yunnan Yunnan Normal University Kunming PR China

In this paper, we propose and analyze a new error correction iterative finite element method (FEM) based on charge-conservative for solving the stationary inductionless magnetohydrodynamic (MHD). The method consists of first solving the inductionless MHD equations by the Oseen iterative scheme to obtain an approximate solution, and then an error correction strategy is applied to control the error arising from the linearization of the nonlinear inductionless MHD equations. The proposed method not only retains the advantages of the classical Oseen iterative scheme but also leads to a rapid rate of convergence. It is shown that the convergence rate of the new method is greatly improved under the uniqueness condition. Stability analysis and error estimates are provided. Numerical results are presented to verify the applicability and effectiveness of the new method.

关键词： Nonlinear equations

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A credible mechanism of service about data resource in cloud computing

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International Journal of Network Security 2018年第4期20卷 754-761页

作者： Li, Yunfa Shen, Yangyang Li, Mingyi Key Laboratory of Complex Systems Modeling and Simulation School of Computer Hangzhou Dianzi University Xiasha Higher Education Zone Hangzhou Zhejiang Province310018 China

In order to protect the security of service in cloud computing, we propose a credible mechanism of service for data resource. In the mechanism, we first build a system model and put forward its implementation process. Then, we design an encryption method used in the system model. On this basis, we discuss the function of the third party trusted platform. All of these constitute a credible mechanism of service about data resource in cloud computing. In order to verify the feasibility of the mechanism, a series of experiments have been done. The experimental results show that it is feasible to ensure the security of service about data resource in cloud computing. © 2018, Femto Technique Co., Ltd.

关键词： Cryptography

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SOME REMARKS ON LIOUVILLE TYPE THEOREMS FOR THE 3D STEADY TROPICAL CLIMATE MODEL

arXiv

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arXiv 2025年

作者： Dong, Yanyan Zhang, Zhibing School of Mathematics and Physics Anqing Normal University Anqing246133 China School of Mathematics and Physics Key Laboratory of Modeling Simulation and Control of Complex Ecosystem in Dabie Mountains Anhui Higher Education Institutes Anqing Normal University Anqing246133 China

Observing the special structure of the system and using the Poincaré-Sobolev inequality, we establish Liouville type theorems for the 3D steady tropical climate model under certain conditions on u, v, ∇θ. Our results extend and improve a Liouville type result of Cho-In-Yang (arXiv:2312.17441).MSC Codes 35B53, 35Q35, 35A02 © 2025, CC BY.

关键词： Climate models

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An Intelligent Ranking Evaluation Method of simulation Models Based on Graph Neural Network 15th

An Intelligent Ranking Evaluation Method of Simulation Model...

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15th EAI International Conference on simulation Tools and Techniques, SIMUTools 2023

作者： Yang, Fan Ma, Ping Zhang, Jianchao Cheng, Huichuan Li, Wei Yang, Ming Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Complex System Modeling and Simulation Harbin150080 China Chinese Aeroengine Research Institute Beijing101304 China

ISBN: (纸本)9783031575228

To validate the alternative simulation models and select the most credible one when the models have multivariate and correlated outputs, an intelligent ranking evaluation method of simulation models based on Graph Neural Network (GNN) is proposed. The process of ranking evaluation is divided into three parts: graph structure conversion for evaluation data, feature extraction based on Graph Representation Learning (GRL) and ranking evaluation based on feature distance. A graph structure modeling method is presented to provide the pre-define graph structure for further GRL primarily. Next the interdependencies and dynamic evolutionary patterns among variables are captured by GNN so that the graph representations of evaluation data can be obtained. Then ranking evaluation is achieved by similarity measurement of the graph representations. In the end, the effectiveness of the proposed method on feature extraction of evaluation data and simulation models ranking is illustrated through an application example on a prediction model for aerodynamic parameters of a certain flight vehicle. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2024.

关键词： Feature extraction

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An Intelligent simulation Result Validation Method Based on Variational Autoencoder 23rd

An Intelligent Simulation Result Validation Method Based on ...

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23rd Asia simulation Conference, AsiaSim 2024

作者： Yang, Fan Ma, Ping Li, Wei Tao, Chao Yang, Ming Zhang, Jianchao Cheng, Huichuan Control and Simulation Center Harbin Institute of Technology Harbin150080 China National Key Laboratory of Complex System Modeling and Simulation Harbin150080 China Chinese Aeroengine Research Institute Beijing101304 China

ISBN: (纸本)9789819772247

Validation for complex system simulation faces the challenges of a large amount of validation data, which comes in the form of extensive samples and prolonged time series. To address this issue, this paper proposes an intelligent simulation result validation method based on Variational Autoencoder (VAE), achieving model validation through intelligent feature extraction and feature consistency metrics. Initially, we present the overall validation framework, which consists of feature extraction and simulation result validation, and detail the steps of the validation process. Subsequently, the principles and procedures of the feature extraction and simulation result validation methods are thoroughly discussed. The feature extraction is achieved by learning the distribution parameters of the latent space using a VAE model. Feature differences across various aspects are measured by three distance metrics and are further converted into simulation credibility. Finally, the effectiveness and superiority of this method are demonstrated through a case study on validating a drone delivery model. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Digital elevation model

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Relationship graph learning network for visual relationship detection 2

Relationship graph learning network for visual relationship ...

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2nd ACM International Conference on Multimedia in Asia, MMAsia 2020

作者： Li, Yanan Yu, Jun Zhan, Yibing Chen, Zhi Key Laboratory of Complex Systems Modeling and Simulation School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781450383080

Visual relationship detection aims to predict the relationships between detected object pairs. It is well believed that the correlations between image components (i.e., objects and relationships between objects) are significant considerations when predicting objects' relationships. However, most current visual relationship detection methods only exploited the correlations among objects, and the correlations among objects' relationships remained underexplored. This paper proposes a relationship graph learning network (RGLN) to explore the correlations among objects' relationships for visual relationship detection. Specifically, RGLN obtains image objects using an object detector, and then, every pair of objects constitutes a relationship proposal. All relationship proposals construct a relationship graph, in which the proposals are treated as nodes. Accordingly, RGLN designs bi-stream graph attention subnetworks to detect relationship proposals, in which one graph attention subnetwork analyzes correlations among relationships based on visual and spatial information, and the other analyzes correlations based on semantic and spatial information. Besides, RGLN exploits a relationship selection subnetwork to ignore redundant information of object pairs with no relationships. We conduct extensive experiments on two public datasets: the VRD and the VG datasets. The experimental results compared with the state-of-the-art demonstrate the competitiveness of RGLN. © 2021 ACM.

关键词： Semantics

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Control Design of Flight simulation Turntable Based on Model-Free Adaptive Control

Control Design of Flight Simulation Turntable Based on Model...

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2023 China Automation Congress, CAC 2023

作者： Yue, Mingtan Zhang, Yu Huo, Xin Control & Simulation Center Harbin Institute of Technology Harbin150080 China Beijing Simulation Center National Key Laboratory of Modeling and Simulation for Complex Systems Beijing100854 China

ISBN: (纸本)9798350303759

Aiming at the problem of periodic interference in flight simulation turntables, a design method of full-form dynamic linearization model free adaptive control (FFDL-MFAC) is proposed. An equivalent dynamic linearized data model is established at each dynamic operating point of the closed-loop system to achieve adaptive control of the nonlinear system, which gives the controller the advantage of online adjustment of internal parameters and improves the robustness of the control system. Aiming at the difficulty of parameter adjustment caused by the increase of dimension of the pseudo partial derivative matrix, a PID-like MFAC parameter adjustment method is proposed, which greatly reduces the difficulty of parameter adjustment of the model-free adaptive controller. The simulation results of MFAC and PID show that the designed FFDL-MFAC controller outperforms the conventional PID in tracking command signals and suppressing periodic disturbances. © 2023 IEEE.

关键词： Controllers

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Research on information capability based high-performance information sharing in the simulation grid

Research on information capability based high-performance in...

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2010 International Conference on Computer modeling and simulation, ICCMS 2010

作者： Zhang, Ying-Chao Zhang, Jing Chen, Xin Yu, Qin-Zhang Zhang, Hao Beijing Institute of System Engineering National Key Laboratory of Science and Technology on Complex Systems Simulation Beijing China

ISBN: (纸本)9780769539416

For the purpose of achieving high-performance information sharing in the simulation grid, an information capability-based Three Phase High-performance Information Sharing Approach (TPHPISA for short) is advanced. The main idea of TPHPISA is selecting those information sources with highest information capability and executing the best query plan. To illustrate how TPHPISA works, an application example of implementing high-performance information sharing in the stock market simulation grid is thoroughly analyzed. At last, the searching efficiency and accuracy of TPHPISA are demonstrated through comparing with other similar method. © 2010 IEEE.

关键词： Information analysis

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Machine Learning Security Analysis Framework Based on Threat Matrix 8

Machine Learning Security Analysis Framework Based on Threat...

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8th International Conference on Data Science in Cyberspace, DSC 2023

作者： Li, Hu Ma, Qiongmin Zhang, Ming Kuang, Xiaohui National Key Laboratory of Science and Technology on Information System Security Beijing China National Key Laboratory for Complex Systems Simulation Beijing China

ISBN: (纸本)9798350331035

Machine Learning and Artificial Intelligence technology accelerates technological progress and promotes social development, but also brings many security problems. Machine learning models may be affected, deceived, controlled or destroyed at different stages, e.g. training and inference, which may lead to serious consequences. In view of the main stages of the life cycle of machine learning, we summarizes the related attack and defense technologies based on threat matrix, makes a comprehensive and systematic analysis on the security issues of machine learning, and puts forward several security protection suggestions for intelligent information systems. © 2023 IEEE.

关键词： Artificial Intelligence Machine Learning Security Analysis Threat Matrix

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