检索结果-内蒙古大学图书馆

China Land Carbon Budget(CLCB1.0):a comprehensive estimate of the land carbon budget in China

National science Review 2025年第4期12卷 15-18页

作者： Jiangzhou Xia Xiaosheng Xia Xuhui Wang Weimin Ju Zhengyang Lin Zhangcai Qin Yuxing Sang Yanzi Yan Wenping Yuan Xu Yue Haicheng Zhang Hao Zhou Qiuan Zhu Tianjin Key Laboratory of Water Resources and Environment Tianjin Normal University School of Atmospheric Sciences Sun Yat-sen University Institute of Carbon Neutrality Sino-French Institute for Earth System ScienceCollege of Urban and Environmental SciencesPeking University International Institute for Earth System Sciences Nanjing University Jiangsu Center for Collaborative Innovation in Geographic Information Resource Development and Application School of Atmospheric Sciences Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies Key Laboratory of Tropical Atmosphere-Ocean System (Ministry of Education) Sun Yat-sen University Department of Soil and Environment Swedish University of Agricultural Sciences Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control Collaborative Innovation Center of Atmospheric Environment and Equipment Technology School of Environmental Science and Engineering Nanjing University of Information Science & Technology (NUIST) Carbon-Water Research Station in Karst Regions of Northern Guangdong School of Geography and Planning Sun Yat-sen University College of Meteorology and Oceanography National University of Defense Technology College of Geography and Remote Sensing Hohai University

The terrestrial ecosystem plays an important role in regulating the regional carbon balance, in particular for China, where ecological projects during past decades [1,2] have led to large increases in China's land carbon sinks, partially offsetting fossil fuel emissions. Therefore, accurate evaluation of land carbon fluxes in China is critical for improving our understanding of the magnitude of China's carbon budget, and projecting its future changes.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Flow-Guided Anomaly Detection Method For Substation Equipment in Changing Scenarios

A Flow-Guided Anomaly Detection Method For Substation Equipm...

引用

2021 China Automation Congress, CAC 2021

作者： Zhang, Qingwei Wang, Jing Wang, Peng Zhou, Wenhao Li, Yingxuan Zhao, Chunhui State Key Laboratory of Smart Grid Protection and Control NAPJ Technology Development Company Limited Nanjing China State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9781665426473

The anomaly detection for substation equipment is of great significance to maintain the safe operation of substations. With the development of deep learning, many anomaly detection methods based on deep convolutional neural networks (CNN) have been proposed. However, the challenge lies in the diversity of the environment and the variety of anomaly types in the substation. This paper proposes a Flow-Guided Anomaly Detection Method, which contains a data augmentation module and a flow-guided feature fusion module. The data augmentation module utilizes CycleGAN to transfer the style of the images to adapt to changing scenarios, such as different illumination and season conditions. The flow-guided feature fusion module extracts the optical flow between the test image and the template image by a pre-trained FlowNet, which represents the change information between the image pair and is universal for different anomaly types. Then the appearance information and change information of the image are aggregated to obtain the fused feature, which contains more semantic information. Finally, the fused feature is utilized to accurately detect a wider range of abnormal types. Experiments show that our proposed method has superior performance in anomaly detection for substation equipment and is more robust to changing scenarios. © 2021 IEEE

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

Multi-Agent Q-Value Mixing Network with Covariance Matrix Adaptation Strategy for the Voltage Regulation Problem

Multi-Agent Q-Value Mixing Network with Covariance Matrix Ad...

引用

第42届中国控制会议

作者： Yiwen Wang Senlin Zhang Meiqin Liu Shanling Dong Ronghao Zheng College of Electrical Engineering Zhejiang University National Key Laboratory of Industrial Control Technology Zhejiang University

control and optimization of power systems typically involves schemes that utilize optimal power flow techniques and comprehensive modeling of various electrical components. However, the extensive integration of renewable energy sources and distributed energy resources makes it difficult to obtain accurate models, making the traditional model-based approaches more challenging. In this paper, we propose a Covariance Matrix Adaptation Q-value network mixing method(CMAQMIX), which is a novel model-free multi-agent reinforcement learning method that combines the advantages of Covariance Matrix Adaptation Evolution Strategy and the Q-value network mixing method to solve the problem of continuous action space. We establish a new multi-agent voltage regulation environment based on CityLearn framework to test the CMAQMIX method. The results show that our proposed method outperforms the Independent Proximal Policy Optimization method and can give immediate action response without the complete domain knowledge of the power system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A nano-sheet graphene-based enhanced thermal radiation composite for passive heat dissipation from vehicle batteries

引用

Nano Materials science 2024年第4期6卷 443-455页

作者： Ji-Xiang Wang Christopher Salmean Jiaxin Li Chaojie Lei Jun Li Mingliang Zhong Bo Qi Yufeng Mao Hebei Key Laboratory of Man-machine Environmental Thermal Control Technology and Equipment Hebei Vocational University of Technology and EngineeringHebei 054000PR China College of Electrical Energy and Power EngineeringYangzhou UniversityYangzhou225009PR China Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and TechnologyKowloonHong Kong SARPR China China Academy of Launch Vehicle Technology Beijing100076PR China Beijing Sino-Spark Technology Co. Ltd.Beijing100191PR China School of Environmental Science and Engineering Suzhou University of Science and TechnologySuzhou215009PR China Institute of Optics and Electronics Chinese Academy of SciencesChengdu610209PR China National Key Laboratory of Optical Field Manipulation Science and Technology Chinese Academy of SciencesChengdu610209PR China Taizhou Wavexploration Energy Ltd. Taizhou225513PR China Department of Electrical and Computer Engineering University of TorontoTorontoM5S3G4Canada

In response to thermal runaway(TR)of electric vehicles,recent attention has been focused on mitigation strategies such as efficient heat dredging in battery thermal *** management with particular focus on battery cooling has been becoming increasingly *** usually happened when an electric vehicle is unpowered and *** this state,traditional active battery cooling schemes are disabled,which can easily lead to dangerous incidents due to loss of cooling ability,and advanced passive cooling strategies are therefore gaining ***,we developed an enhanced thermal radiation material,consisting of~1μm thick multilayered nano-sheet graphene film coated upon the heat dissipation surface,thereby enhancing thermal radiation in the *** surface was characterized on the nanoscale,and tested in a battery-cooling *** found that the graphene-based coating's spectral emissivity is between 91% and 95% in the mid-infrared region,and thermal experiments consequently illustrated that graphene-based radiative cooling yielded up to15.1% temperature reduction when compared to the uncoated *** the novel graphene surface to augment a heat pipe,the temperature reduction can be further enlarged to 25.6%.The new material may contribute to transportation safety,global warming mitigation and carbon neutralization.

关键词： Battery thermal management Nano-sheet graphene Functional material Passive cooling Thermal radiation

来源：评论

学校读者我要写书评

暂无评论

Dynamic Multi-Robot Path Planning in Narrow-Lane Environments with One-Way Constraint 6

Dynamic Multi-Robot Path Planning in Narrow-Lane Environment...

引用

6th International Conference on Intelligent Autonomous Systems, ICoIAS 2023

作者： Song, Zhenyu Zheng, Ronghao Zhang, Senlin Liu, Meiqin College of Electrical Engineering Zhejiang University Hangzhou310027 China Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xian710049 China

ISBN: (纸本)9798350371253

With the rapid development of the logistics industry, the path planning problem for automated guided vehicles (AGVs) in warehousing systems has become a prominent research topic. Traditional multi-robot path planning algorithms often perform poorly in narrow-lane environments found in warehouses. This paper proposes an improved dynamic multi-robot path planning algorithm specifically tailored for narrow-lane environments. By constraining the traversal directions within narrow lanes and dynamically determining the optimal directions, this algorithm achieves efficient multi-robot path planning and enhances the quality of robot paths. The effectiveness of the algorithm is theoretically proven in this paper. Extensive simulation data demonstrates that our algorithm efficiently generates high-quality paths in high-density narrow-lane warehouse environments. © 2023 IEEE.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Hybrid evolutionary algorithm with sequence difference-based differential evolution for multi-objective fuzzy flow-shop scheduling problem

引用

International Journal of Internet Manufacturing and Services 2022年第4期8卷 308-329页

作者： Zhang, Wenqiang Li, Chen Yang, Weidong Gen, Mitsuo College of Information Science and Engineering Henan University of Technology Zhengzhou450001 China Henan Key Laboratory of Grain Photoelectric Detection and Control Henan University of Technology Zhengzhou450001 China Fuzzy Logic Systems Institute Tokyo University of Science Tokyo162-8601 Japan

In the actual production process of a factory, there are often many uncertain factors, and researchers usually use fuzzy time to express this uncertainty. In this regard, a hybrid evolutionary algorithm with sequence difference-based differential evolution (HEA-SDDE) is proposed to solve fuzzy flow-shop scheduling problem (FFSP). Firstly, the algorithm uses a hybrid sampling strategy based a multi-objective evolutionary algorithm to guide the population to quickly converge to multiple areas of the Pareto front (PF). Secondly, the proposed algorithm applies a sequence difference-based differential evolution (SDDE) strategy, which uses exchanging sequences to determine the sequence differences between individuals, thereby improving the poorly performing individuals in the population. The experiment compares HEA-SDDE with multiple algorithms on 12 problems of different scales for the multi-objective fuzzy flow-shop scheduling problem (MoFFSP). The results demonstrate that the proposed HEA-SDDE has good convergence and distribution performance. Copyright © 2022 Inderscience Enterprises Ltd.

关键词： Machine shop practice

来源：评论

学校读者我要写书评

暂无评论

Few-shot Underwater Acoustic Target Recognition Based on Siamese Network 42

Few-shot Underwater Acoustic Target Recognition Based on Sia...

引用

42nd Chinese control Conference, CCC 2023

作者： Yang, Haizhou Liu, Meiqin Zhang, Senlin Zheng, Ronghao Dong, Shanling Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China College of Electrical Engineering Zhejiang University Hangzhou310027 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an710049 China

ISBN: (纸本)9789887581543

Underwater acoustic target recognition is a widely investigated issue in the field of underwater acoustics. Many good results have been reported for underwater acoustic target recognition. However, in practical applications, the strong demand for labeled data for underwater acoustic target recognition is a big obstacle. In order to solve this problem, researchers have explored few-shot learning and unsupervised methods in various papers. A Siamese network is proposed which is composed of one-dimensional convolution and Long Short-Term Memory (LSTM) neural networks, called 1DCLSN. A structure for 1DCLSN is designed which combines contrastive information with label information and obtains satisfactory recognition results. In addition, the contrastive loss function with a different clustering term is modified to improve the performance. With only few labeled training samples, the performance of the proposed approach is better than those of other deep learning methods. The experiment shows the great potential of our method. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Underwater acoustics

来源：评论

学校读者我要写书评

暂无评论

Mean square stability for Markov jump Boolean networks

引用

science China(Information sciences) 2020年第1期63卷 190-199页

作者： Liqing WANG Mei FANG Zheng-Guang WU State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University College of Automation Harbin Engineering University

In this paper, one of the stability definitions of Markov jump Boolean networks(MJBNs), called mean square stability(MSS), is investigated. Some necessary and sufficient conditions are presented to guarantee the MSS of such MJBNs. Moreover, one of the necessary and sufficient conditions for MSS is obtained in terms of linear programming, which implies that MSS is equivalent to global stability with probability 1 for MJBNs. Furthermore, the construction of Lyapunov function is given and also another theorem based on the Lyapunov function is derived to ensure the MSS of MJBNs. Finally, a numerical example is provided to illustrate the profits of our results.

关键词： mean square stability MSS Boolean network BN stochastic stability Markovian jump parameters semi-tensor product STP Lyapunov function

来源：评论

学校读者我要写书评

暂无评论

A Neural Additive Domain Adaptation Network with Interpretability for Fault Detection in Various Operating Conditions

A Neural Additive Domain Adaptation Network with Interpretab...

引用

IEEE International Conference on industrial technology (ICIT)

作者： Cheng Su Weimin Zhong Dan Yang Linlin Li Xin Peng State Key Laboratory of Industrial Control Technology East China University of Science and Technology Shanghai China Key Laboratory of Smart Manufacturing in Energy Chemical Process East China University of Science and Technology Shanghai China Department of Control Science and Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

Domain adaptation (DA) can be used for fault detection under multiple operating conditions. However, the lack of interpretability of DA models prevents potential users from understanding the decisions made by models. To give a solution, a neural additive domain adaptation network (NADAN) is proposed, which is constructed based on a neural additive model (NAM). Benefiting from the structural advantages of NAM, the predictions of NADAN are interpretable. Specifically, NADAN is able to explain how each feature affects the decision of the model. In addition, NADAN consists of two modules, feature learning (FL) and domain adaptation (DA), and achieves domain alignment through the combination of FL and DA. The FL module is pretrained to learn high-order features. The DA module takes learned features as input and achieves domain alignment based on multi-kernel maximum mean discrepancy (MK-MMD). Compared to the raw data, the learned features are more task-relevant, which helps to improve the performance of NADAN on DA. Furthermore, NADAN augments the feature dimensions during DA to measure the inter-domain differences in detail, which in turn achieves better domain alignment. Experiments on datasets generated from wastewater treatment simulation model demonstrate the effectiveness of the proposed NADAN.

关键词： Representation learning Adaptation models Additives Fault detection Computational modeling Feature extraction Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Designing edge-based and node-based fully distributed algorithms for aggregative games with the adaptive technique

引用

Automatica 2025年 179卷

作者： Wang, Dong Chen, Mingfei Lian, Jie Lin, Peng Wu, Zhengguang Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education School of Control Science and Engineering Dalian University of Technology Dalian China School of Automation Central South University Changsha China Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

This paper focuses on aggregative games with local feasibility decision sets in a partial-decision information scenario. To seek the Nash equilibrium in a fully distributed manner, adaptive algorithms with edge-based and node-based control gains are designed. In the edge-based adaptive algorithm, an auxiliary dynamics is developed with the consensus protocol and adaptively adjusts the edges’ weights. In the node-based adaptive algorithm, fully distributed decision-seeking is achieved by dynamically modifying the player's weight based on the overall consensus error. By virtue of the designed adaptive parameters, players update decisions without any global information. Utilizing Lyapunov stability theory and the comparison lemma, the proposed algorithms converge exponentially to a small neighborhood of the Nash equilibrium. Furthermore, the proposed adaptive algorithms are extended to the prescribed-time case by combining the prescribed-time gain function and exponential adaptive parameters. Finally, numerical simulations are presented to demonstrate the effectiveness of the proposed algorithms. © 2025 Elsevier Ltd

关键词： Adaptive algorithms

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：