检索结果-内蒙古大学图书馆

Can Digital Intelligence and Cyber-Physical-Social systems Achieve Global Food Security and Sustainability?

IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2070-2080页

作者： Yanfen Wang Mengzhen Kang Yali Liu Juanjuan Li Kai Xue Xiujuan Wang Jianqing Du Yonglin Tian Qinghua Ni Fei-Yue Wang College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049 Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408 State Key Laboratory of Tibetan Plateau Earth System Environment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Grassland Science Beijing Forestry UniversityBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXining 810016 Key Laboratory of Adaptation and Evolution of Plateau Biota Northwest Institute of Plateau BiologyChinese Academy of SciencesXining 810001 Binzhou Institute of Technology Weiqiao-UCAS Science and Technology ParkBinzhou 256606China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078 State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078 Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China IEEE

Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration *** the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the

关键词： Carbon-water balance decision-support digital intelligence(DI) foundation models planning

来源：评论

学校读者我要写书评

暂无评论

Safe RL-based Adaptive Cooperative Game control of Wing Deformation and Flight State Tracking for Morphing Hypersonic Vehicles

引用

IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Wang, Jun-Wei Wang, Feng Wu, Huai-Ning Liu, Zhou-Yang University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Hangzhou International Innovation Institute Hangzhou311115 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

This study addresses the issue of adaptive cooperative game control (ACGC) design for wing deformation and flight state tracking of morphing hypersonic vehicles (MHVs) with variable wing shapes, input constraints and state constraints. To access a better flight control performance, the wing deformation parameter is extended in this work as an auxiliary control input. An oriented-coordinated-control nonlinear differential equation model is first established to describe the complicated longitudinal flight state tracking error dynamics of the MHV. Then, a control barrier function (CBF) is introduced and incorporated into the value function as a risk penalty term of state security constraint. Based on the differential game (DG) theory, the optimal coordinated control problem for the MHV with input constraints and state constraints is treated as a constrained cooperative DG that is further formulated as a Hamilton-Jacobi-Bellman (HJB) equation with barrier and hyperbolic functions. A safe RL algorithm is proposed to solve the above HJB equation and an online Pareto joint control strategy is achieved thereby. Hereafter the stability analysis of the closed-loop state tracking error system is done by the Lyapunov technique. Meanwhile, both state and input constraints are met during the the parameter learning regulation process. At last, a simulation study is performed to support the proposed safe RL-ACGC algorithm. © 2025 IEEE.

关键词： Hyperbolic functions

来源：评论

学校读者我要写书评

暂无评论

Disturbance Rejection for Pedaling Rehabilitation Robot Based on Integration of Equivalent-Input-Disturbance and Repetitive control Methods

Disturbance Rejection for Pedaling Rehabilitation Robot Base...

引用

IEEE International Symposium on Industrial Electronics (ISIE)

作者： Yujian Zhou Jinhua She Feng Wang Makoto Iwasaki School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan Department of Electrical and Mechanical Engineering Nagoya Institute of Technology Nagoya Japan

This study integrated an improved equivalent-input-disturbance (EID) and a repetitive control methods to ensure reference tracking and enhance disturbance-rejection performance for a pedaling rehabilitation robot. A repetitive controller ensures steady-state tracking of a periodic reference input. An EID estimator with a state observer estimates and compensates for the effect of disturbances generated by patients with lower-limb impairment. The stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show the effectiveness of this method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Subspace-Based Non-Dominated Subset Selection Method

A Subspace-Based Non-Dominated Subset Selection Method

引用

Congress on Evolutionary Computation

作者： Qingshan Tan Changhe Li Sanyou Zeng Shengxiang Yang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China School of Computer Science and Informatics De Montfort University Leicester United Kingdom

Environmental selection is an important process in multi-objective evolutionary algorithms (MOEAs). As the evolution progresses, the number of non-dominated solutions increases. This paper is focused on selecting a subset from excess non-dominated solutions for evolutionary or the final output. However, traditional selection methods in classical MOEAs encounter difficulties when dealing with candidate solutions that possess irregular topologies. Although the distance-based subset selection methods are not sensitive to the topologies of the candidate points, they have significant room for reducing computational complexity. In order to address the above issues, a subspace selection method is proposed in this paper. It partitions the objective space into multiple subspaces that have comparable volumes and shapes. The maximal minimum distance of each solution is considered to ensure that the sparsest solution is always chosen first. To save computational costs, only the solutions in the neighboring subspaces are taken into account. The experimental results demonstrate that the proposed subspace selection method outperforms classical selection methods in solving problems with various shapes of the Pareto front.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Hand Detection and Gesture Classification based on Transformer

Hand Detection and Gesture Classification based on Transform...

引用

Chinese automation Congress (CAC)

作者： Genghui Pei Chi Xu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Engineering Research Center of Intelligent Technology for Geo-Exploration Ministy of Education Wuhan China Engineering Research Center of Intelligent Technology for Geo-Geo-Exploration Ministy of Education Wuhan China

Hand detection and gesture recognition are an important branch of artificial intelligence, which are widely used in daily life, such as interaction between human and machines, communication using signals, virtual reality and so on. In order to realize gesture recognition in unconstrained situations, we propose a novel end-to-end model based on Transformer, which can detect multiple hands in a picture. Our network can be roughly divided into the following three stages. In the first stage, we will extract feature maps of different layers by convolutional network from monocular RGB images. In the second stage, features are sent into the codec module based on Transformer, and hand detection is further carried out through multi-layer perceptrons with the decoding vectors as the input. In the third stage, we combine the attention weight maps obtained in the second step with the features of different layers in the first step to complete the gesture recognition task. From the experiment results, our network accurately identifies the positions of multiple hands in the picture and correctly recognizes hand gestures.

关键词： Solid modeling Codecs automation Gesture recognition Virtual reality Transformers Feature extraction

来源：评论

学校读者我要写书评

暂无评论

Fast control Strategy of Grid-forming Inverter Based on Power Feedforward

Fast Control Strategy of Grid-forming Inverter Based on Powe...

引用

Chinese control Conference (CCC)

作者： Sheng Zhang Zhijian Fang Qine Liu Muchao Xiang Dingbang Huang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China State Grid Hubei Electric Power Co. Ltd Xiangyang Power Supply Company Xiangyang China Electric Power Scientific Research Institute of State Grid Hubei Electric Power Co. Ltd Wuhan China

Grid-forming inverter is widely used in grid-connected systems of distributed generation because of its frequency and voltage support capacity and good stability in microgrid, but its large inertia will affect the dynamic response speed of grid-forming inverter. In order to solve this problem, this paper introduces the loop that affects the dynamic response of grid-forming inverter, and carries out small signal modeling for active loop, analyzes the dynamic performance indicators and determinants of typical second-order system. Thus, a method of adding power feedforward coefficient to the forward channel of the power loop is designed, and the response speed of the system with or without feedforward coefficient under the unit step response is compared. Finally, the simulation results show that adding the power feedforward coefficient can improve the response speed of the grid-forming inverter during startup and power switching, then achieves the effect of fast control.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Multi-Kernel Principal Component Analysis Method for Quality-Related Fault Detection

A Multi-Kernel Principal Component Analysis Method for Quali...

引用

Youth Academic Annual Conference of Chinese Association of automation (YAC)

作者： Lingxia Mu Biyu Lei Ding Liu School of Automation and Information Engineering Xi’an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi’an University of Technology Xi’an China

ISBN: (纸本)9781665465373

In this paper, a multi-kernel principal component analysis (MKPCA) method for quality-related fault detection is proposed. The initial space is firstly mapped to a new space. The correlated information between the new space and output quality is then obtained by the kernel function. Meanwhile, with consideration of the advantage of global function and local function, a weight factor which combines them together is introduced to construct a multi-kernel function. In this way, the algorithm achieves better learning ability. The new space is projected to two mutually orthogonal subspaces, i.e., quality-related part and quality-unrelated part. In each subspace, fault information is expressed by different statistical indicators. The numerical example is presented to evaluate the performance of the MKPCA. The results show better reliability and high fault detection rate through proper spatial decomposition and kernel function construction.

关键词： Correlation automation Fault detection Feature extraction Eigenvalues and eigenfunctions Reliability Matrix decomposition

来源：评论

学校读者我要写书评

暂无评论

Scene Classification Using Deep Networks Combined with Visual Attention

引用

Journal of Sensors 2022年第0期2022卷

作者： Shi, Jing Zhu, Hong Li, Yuxing Li, Yanghui Du, Sen School of Automation and Information Engineering Xi'An University of Technology Xi'an710048 China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'An University of Technology Xi'an710048 China

In view of the scene's complexity and diversity in scene classification, this paper makes full use of the contextual semantic relationships between the objects to describe the visual attention regions of the scenes and combines with the deep convolution neural networks, so that a scene classification model using visual attention and deep networks is constructed. Firstly, the visual attention regions in the scene image are marked by using the context-based saliency detection algorithm. Then, the original image and the visual attention region detection image are superimposed to obtain a visual attention region enhancement image. Furthermore, the deep convolution features of the original image, the visual attention region detection image, and the visual attention region enhancement image are extracted by using the deep convolution neural networks pretrained on the large-scale scene image dataset Places. Finally, the deep visual attention features are constructed by using the multilayer deep convolution features of the deep convolution networks, and a classification model is constructed. In order to verify the effectiveness of the proposed model, the experiments are carried out on four standard scene datasets LabelMe, UIUC-Sports, Scene-15, and MIT67. The results show that the proposed model improves the performance of the classification well and has good adaptability. © 2022 Jing Shi et al.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Large Receptive Field Boundary Matching Networks for Generating Better Proposals

Large Receptive Field Boundary Matching Networks for Generat...

引用

第40届中国控制会议

作者： Lei Xu Jiexi Liu Bo Chen Beijing Institute of Technology School of Automation Key Laboratory of Complex System Intelligent Control and Decision

Temporal Action Detection is a research hotspot in Video *** is necessary not only to give the specific moments of the beginning and end of each action instance in the video,but also to give the category of the action *** present,most of the methods in temporal action detection are divided into two steps:The video is divided into a series of video clips to determine whether each clip is an action instance,and the fragments that are not an action instance are deleted;Segments that may be action instances are then classified to get the final *** present,the difficulties in action detection research mainly include the following two points:1) The boundary is not *** from action recognition,action detection requires precise positioning,but an action in life is often not very *** is also the reason why the mean average precision(mAP) of action detection is low at present.2) The time span is *** life,an action often spans a very long *** movements such as waving can last for a few seconds,while long movements such as rock climbing or cycling can last for tens of minutes,which makes it extremely difficult for us to extract *** view of the above difficulties,this paper proposes a large receptive field boundary matching network(LRFBMN) model which takes advantage of the relationship between proposals to improve the accuracy of proposal *** model is mainly divided into two parts:1) Clipping feature map is processed by large kernel convolution,and then proposal feature is generated by ROI-pooling;2) The proposals are arranged in a certain order to form a fixed graph,and the information exchange between graph nodes is realized by using convolution with *** experiments,this model is 2.35% higher than baseline and 1.06% higher than state-of-the-art in THUMOS14 data set.

关键词： Temporal Action Detection Video Understanding Proposal Large Receptive Field

来源：评论

学校读者我要写书评

暂无评论

An attention-based RGBD dual-branch gesture recognition network

An attention-based RGBD dual-branch gesture recognition netw...

引用

第40届中国控制会议

作者： Bo Chen Pengwei Xie Nan Hao Beijing Institute of Technology School of Automation Key Laboratory of Complex System Intelligent Control and Decision

In this work,we use a hierarchical architecture based on detector-classifier for gesture recognition *** the operation of the architecture,the detector,which is essentially the switch of the classifier,is always *** the output of the detector is true,then the classifier is activated and returns a classification label for the input video *** work focuses on the improvement of detectors and *** the detector,we introduce an attention mechanism to guide the network to focus on the space and channel where the gesture is *** the classifier,based on the RGB information stream,we use an independent branch to extract the features of the depth stream,and finally merge the two *** gestures move in a three-dimensional space,depth information can make up for the lack of RGB *** show that on the Egogesture test set,our detector achieves 98.86% accuracy on RGB input,while the classifier achieves 93.85% *** the same time,our gesture recognition architecture can fully meet the real-time requirements.

关键词： Gesture Recognition RGBD feature fusion attention mechanism real-time

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：