检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Schmidinger, Jonas Vogel, Sebastian Barkov, Viacheslav Pham, Anh-Duy Gebbers, Robin Tavakoli, Hamed Correa, Jose Tavares, Tiago R. Filippi, Patrick Jones, Edward J. Lukas, Vojtech Boenecke, Eric Ruehlmann, Joerg Schroeter, Ingmar Kramer, Eckart Paetzold, Stefan Kodaira, Masakazu Wadoux, Alexandre M.J.-C. Bragazza, Luca Metzger, Konrad Huang, Jingyi Valente, Domingos S.M. Safanelli, Jose L. Bottega, Eduardo L. Dalmolin, Ricardo S.D. Farkas, Csilla Steiger, Alexander Horst, Taciara Z. Ramirez-Lopez, Leonardo Scholten, Thomas Stumpf, Felix Rosso, Pablo Costa, Marcelo M. Zandonadi, Rodrigo S. Wetterlind, Johanna Atzmueller, Martin Osnabrück University Joint Lab Artificial Intelligence and Data Science Osnabrück Germany Department of Agromechatronics Potsdam Germany Piracicaba Brazil The University of Sydney Sydney Institute of Agriculture Sydney Australia Mendel University in Brno Department of Agrosystems and Bioclimatology Brno Czech Republic Leibniz Institute of Vegetable and Ornamental Crops Next Generation Horticultural Systems Grossbeeren Germany Eberswalde University for Sustainable Development Landscape Management and Nature Conservation Eberswalde Germany Soil Science and Soil Ecology Bonn Germany Tokyo University of Agriculture and Technology Institute of Agriculture Tokyo Japan LISAH Univ. Montpellier AgroParisTech INRAE IRD L'Institut Agro Montpellier France Agroscope Field-Crop Systems and Plant Nutrition Nyon Switzerland University of Wisconsin-Madison Department of Soil Science Madison United States Federal University of Viçosa Department of Agricultural Engineering Viçosa Brazil Woodwell Climate Research Center Falmouth United States Academic Coordination Santa Maria Brazil Soil Department Santa Maria Brazil Division of Environment and Natural Resources Aas Norway University of Rostock Chair of Geodesy and Geoinformatics Rostock Germany Federal Technological University of Paraná Dois Vizinhos Brazil BÜCHI Labortechnik AG Data Science Department Flawil Switzerland Imperial College London Imperial College Business School London United Kingdom University of Tübingen Department of Geosciences Tübingen Germany University of Tübingen DFG Cluster of Excellence Machine Learning for Science’ Germany Bern University of Applied Sciences Competence Center for Soils Zollikofen Switzerland Simulation and Data Science Müncheberg Germany Federal University of Jataí Institute of Agricultural Sciences Jatai Brazil Federal University of Mato Grosso Instute of Agricultural and Environmental Scinces Sinop Brazil Department of Soil and Environment Skara

Digital soil mapping (DSM) relies on a broad pool of statistical methods, yet determining the optimal method for a given context remains challenging and contentious. Benchmarking studies on multiple datasets are needed to reveal strengths and limitations of commonly used methods. Existing DSM studies usually rely on a single dataset with restricted access, leading to incomplete and potentially misleading conclusions. To address these issues, we introduce an open-access dataset collection called Precision Liming Soil Datasets (LimeSoDa). LimeSoDa consists of 31 field- and farm-scale datasets from various countries. Each dataset has three target soil properties: (1) soil organic matter or soil organic carbon, (2) clay content and (3) pH, alongside a set of features. Features are dataset-specific and were obtained by optical spectroscopy, proximal- and remote soil sensing. All datasets were aligned to a tabular format and are ready-to-use for modeling. We demonstrated the use of LimeSoDa for benchmarking by comparing the predictive performance of four learning algorithms across all datasets. This comparison included multiple linear regression (MLR), support vector regression (SVR), categorical boosting (CatBoost) and random forest (RF). The results showed that although no single algorithm was universally superior, certain algorithms performed better in specific contexts. MLR and SVR performed better on high-dimensional spectral datasets, likely due to better compatibility with principal components. In contrast, CatBoost and RF exhibited considerably better performances when applied to datasets with a moderate number ( © 2025, CC BY-SA.

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Distributionally robust inverse covariance estimation: The Wasserstein shrinkage estimator

arXiv

引用

arXiv 2018年

作者： Nguyen, Viet Anh Kuhn, Daniel Esfahani, Peyman Mohajerin Risk Analytics and Optimization Chair EPFL Switzerland Delft Center for Systems and Control Delft University of Technology Netherlands

We introduce a distributionally robust maximum likelihood estimation model with a Wasserstein ambiguity set to infer the inverse covariance matrix of a p-dimensional Gaussian random vector from n independent samples. The proposed model minimizes the worst case (maximum) of Stein’s loss across all normal reference distributions within a prescribed Wasserstein distance from the normal distribution characterized by the sample mean and the sample covariance matrix. We prove that this estimation problem is equivalent to a semidefinite program that is tractable in theory but beyond the reach of general purpose solvers for practically relevant problem dimensions p. In the absence of any prior structural information, the estimation problem has an analytical solution that is naturally interpreted as a nonlinear shrinkage estimator. Besides being invertible and well-conditioned even for p > n, the new shrinkage estimator is rotation-equivariant and preserves the order of the eigenvalues of the sample covariance matrix. These desirable properties are not imposed ad hoc but emerge naturally from the underlying distributionally robust optimization model. Finally, we develop a sequential quadratic approximation algorithm for efficiently solving the general estimation problem subject to conditional independence constraints typically encountered in Gaussian graphical models. Copyright © 2018, The Authors. All rights reserved.

关键词： Inverse problems

来源：评论

学校读者我要写书评

暂无评论

Target identity recognition method based on trusted information fusion

引用

International Journal of Performability Engineering 2019年第4期15卷 1235-1246页

作者： Wang, Lu Wen, Chenglin Wu, Lan Department of Electrical Automation Shanghai Maritime University Shanghai201306 China Department of Image and Network Investigation Railway Police College Zhengzhou450053 China Institute of Systems Science and Control Engineering Hangzhou Dianzi University Hangzhou310018 China College of Electrical Engineering Henan University of Technology Zhengzhou450001 China

Safe and reliable target identity recognition is the important foundation of information security. In the complex environment of multi-source target information, in view of the potential impact of many uncertain factors on target identity recognition and the performance requirements of information security in the process of recognition, a trusted target identity recognition method is proposed in this paper. The BP neural network based on momentum factor is used to study and build an ensemble classification model, and based on this model, the trusted target identity recognition model is constructed. According to the relevant information characterized by the model, it can improve the recognition reliability of the target to a certain extent, thus providing more security and credibility for the recognition of the identified target. Finally, the effectiveness and feasibility of the proposed algorithm is verified by simulation experiments under an uncertain set environment. © 2019 Totem Publisher, Inc. All rights reserved.

关键词： Information fusion

来源：评论

学校读者我要写书评

暂无评论

Methods for Improving the Accuracy of the Virtual Assessment of Autonomous Driving

Methods for Improving the Accuracy of the Virtual Assessment...

引用

International Conference on Connected Vehicles and Expo (ICCVE)

作者： Dominik Notz Martin Sigl Thomas Kühbeck Sebastian Wagner Korbinian Groh Christoph Schütz Daniel Watzenig BMW of North America Mountain View CA USA BMW AG München Germany Department of Informatics Chair of Robotics Artificial Intelligence and Embedded Systems Technische Universität Munich München Germany Institute of Automation and Control Graz University of Technology Graz Austria

ISBN: (纸本)9781728101439

Assessing the safety of an autonomous vehicle is an open problem within the research domain for autonomous vehicles. Next to real-world driving tests, simulation and reprocessing of recordings play a crucial role in validating the correct and safe behavior. Current state-of-the-art methods for function reprocessing suffer from several sources of error and hence, might lead to incorrect results. In this work, an overview of the most recent reprocessing methods is given and their shortcomings are described. We suggest the derivation of explicit sensor models and the learning of behavior models for traffic objects. An overview of different levels of sensor and different kinds of agent models is given along with a discussion for the need for statistical and machine learning based models. Furthermore, a novel method, based on infrastructure sensors, to collect the data needed for the derivation of the models is presented.

关键词： Autonomous vehicles Machine learning Intelligent agents Vehicle detection Sensor systems Data collection Simulation Data reprocessing Autonomous Vehicles Vehicle detection Sensor systems Intelligent agents Data Collection Methods reprocessing simulating Artificial Intelligence Machine Learning Error Sources derivation Sensors

来源：评论

学校读者我要写书评

暂无评论

network Resilience

arXiv

引用

arXiv 2020年

作者： Liu, Xueming Li, Daqing Ma, Manqing Szymanski, Boleslaw K. Eugene Stanley, H. Gao, Jianxi Key Laboratory of Image Information Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China School of Reliability and Systems Engineering Beihang University Beijing100191 China College of Safety Science and Engineering Civil Aviation University of China Tianjin 300300 China Department of Computer Science Rensselaer Polytechnic Institute TroyNY12180 United States Network Science and Technology Center Rensselaer Polytechnic Institute TroyNY12180 United States Center for Polymer Studies Department of Physics Boston University BostonMA02215 United States

Many systems on our planet shift abruptly and irreversibly from the desired state to an undesired state when forced across a "tipping point". Some examples are mass extinctions within ecosystems, cascading failures in infrastructure systems, and changes in human and animal social networks. The ability to avoid such regime shifts or to recover quickly from such a non-resilient state demonstrates a system's resilience;system resilience is a quality that enables a system to adjust its activities to retain its basic functionality when errors and failures occur. In the past 50 years, attention has been paid almost exclusively to low-dimensional systems;scholars have focused on the calibration of the resilience functions of such systems and the identification of indicators of early warning signals based on two to three connected components. In recent years, taking advantage of network theory and the availability of lavish real datasets, network scientists have begun to explore real-world complex networked multidimensional systems, as well as their resilience functions and early warning indicators. This report presents a comprehensive review of resilience functions and regime shifts in complex systems in domains such as ecology, biology, society, and infrastructure. The research approach includes empirical observations, experimental studies, mathematical modeling, and theoretical analysis. We also review the definitions of some ambiguous terms, including robustness, resilience, and stability. Copyright © 2020, The Authors. All rights reserved.

关键词： Complex networks

来源：评论

学校读者我要写书评

暂无评论

Navigation Function Used for Parallel Parking in Restricted Area by a Differentially-Driven Mobile Robot

引用

IFAC-PapersOnLine 2017年第1期50卷 4312-4317页

作者： Przybyła M. Kowalczyk W. Kozłowski K. Poznań University of Technology Chair of Control and Systems Engineering ul. Piotrowo 3A Poznań Poland

This work has examined the use of navigation function for the motion task of parallel parking performed by mobile robot with kinematic constraints working in two-dimensional environment with obstacles. Classic navigation function (NF) approach assumes omnidirectional robot. In this paper NF extended with orientation component was tested. It can be tuned to guarantee global convergence to the target position with desired orientation. This paper provides results of experiments with simulated as well as physical robot, showing typical behavior of the method, as well as authors’ remarks on its benefits and disadvantages. © 2017

关键词： motion control navigation function obstacle avoidance parallel parking unicycle

来源：评论

学校读者我要写书评

暂无评论

Bayesian model selection for change point detection and clustering

arXiv

引用

arXiv 2019年

作者： Mazhar, Othmane Rojas, Cristian R. Fischione, Carlo Hesamzadeh, Mohammad R. Division of Decision And Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Network And Sytems Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Electric Power And Energy Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology StockholmSE-100 44 Sweden

We address the new problem of estimating a piece-wise constant signal with the purpose of detecting its change points and the levels of clusters. Our approach is to model it as a nonparametric penalized least square model selection on a family of models indexed over the collection of partitions of the design points and propose a computationally efficient algorithm to approximately solve it. Statistically, minimizing such a penalized criterion yields an approximation to the maximum a-posteriori probability (MAP) estimator. The criterion is then analyzed and an oracle inequality is derived using a Gaussian concentration inequality. The oracle inequality is used to derive on one hand conditions for consistency and on the other hand an adaptive upper bound on the expected square risk of the estimator, which statistically motivates our approximation. Finally, we apply our algorithm to simulated data to experimentally validate the statistical guarantees and illustrate its behavior. Copyright © 2019, The Authors. All rights reserved.

关键词： Least squares approximations

来源：评论

学校读者我要写书评

暂无评论

Towards multi-object detection and tracking in urban scenario under uncertainties 4

Towards multi-object detection and tracking in urban scenari...

引用

4th International Conference on Vehicle technology and Intelligent Transport systems, VEHITS 2018

作者： Kampker, Achim Sefati, Mohsen Abdul Rachman, Arya S. Kreisköther, Kai Campoy, Pascual Chair of Production Engineering of E-Mobility Components RWTH Aachen University Aachen Germany Delft Center for Systems and Control Delft University of Technology Delft Netherlands Computer Vision and Aerial Robotics Group Centre of Automatics and Robotics Universidad Politécnica de Madrid Madrid Spain

ISBN: (纸本)9789897582936

Urban-oriented autonomous vehicles require a reliable perception technology to tackle the high amount of uncertainties. The recently introduced compact 3D LIDAR sensor offers a surround spatial information that can be exploited to enhance the vehicle perception. We present a real-time integrated framework of multi-target object detection and tracking using 3D LIDAR geared toward urban use. Our approach combines sensor occlusion-aware detection method with computationally efficient heuristics rule-based filtering and adaptive probabilistic tracking to handle uncertainties arising from sensing limitation of 3D LIDAR and complexity of the target object movement. The evaluation results using real-world pre-recorded 3D LIDAR data and comparison with state-of-the-art works shows that our framework is capable of achieving promising tracking performance in the urban situation. Copyright © 2018 by SCITEPRESS – Science and technology Publications, Lda. All rights reserved.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Autonomous Multi-vehicle Consensus for High-order systems 36

Autonomous Multi-vehicle Consensus for High-order Systems

引用

第36届中国控制会议

作者： Yonggui Liu Chunjie Zhai Huanli Gao The Key Laboratory of Autonomous Systems and Network Control Ministry of Educationthe College of Automatic Science and EngineeringSouth China University of Technology

ISBN: (纸本)9781538629185

Multi-vehicle deployment can be formulated as a cooperation formation problem using the weighted consensus *** objectives are that make adjacent vehicles keep the constant spacing and all vehicles approach the common velocity and ***,it is preferred that vehicle platoon has fast convergence and strong robustness when disturbances *** achieve these goals,the third-order dynamics are established for vehicle platoon that are regarded as connected vehicle systems（CVSs） and distributed control protocols are designed to implement cooperation *** paper focuses on analysis of stability and stability margin for the *** sufficient and necessary conditions on stability of the CVSs are achieved using the algebraic graph theory and the Routh-Hurwitz stability *** the sufficient conditions,which are determined by the controller gains and the model parameter,but are independent on eigenvalues of the Laplacian matrix of the corresponding network topology,are *** characterize convergent speed of CVSs,the conditions on stability margin of CVSs are also *** are shown to verify validation of the results.

关键词： Vehicle platoon consensus connected vehicle systems leader-following control cooperative control

来源：评论

学校读者我要写书评

暂无评论

Robust gain-scheduled control of variable stiffness actuators

引用

IFAC-PapersOnLine 2017年第1期50卷 8804-8809页

作者： Misgeld B.J.E. Hewing L. Liu L. Leonhardt S. Philips Chair for Medical Information Technology RWTH Aachen University Aachen Germany Institute for Dynamic Systems and Control ETH Zurich Zurich Switzerland

Variable stiffness actuators were introduced to decouple an otherwise stiff actuator from the load by an adjustable elasticity. This variable elastic element can be used as torque sensor, acts as an energy storage, decouples the actuator for exogenous high frequency excitation inputs and contributes towards shock resistance and safety in human-robot interaction scenarios. However, the variable element complicates the design of torque and impedance controllers which have to be synthesized by employing contradicting design objectives, such as minimisation of the output impedance, robust stability and performance. Moreover, the system to be controlled consists of an additional control-loop to set-up the stiffness of the elastic element in real-time. To overcome these synthesis problems, we present a new controller design procedure that imposes a positive-real constraint on the load output port function to guarantee a stable interaction with respect to a passive, yet otherwise unknown environments. Additional design requirements are subsequently cast into a generalised plant. Ultimately, a H∞ - nonsmooth design procedure is employed to design a torque controller under these constraints and is tested in in silico experiments with the Mechanical Rotational Impedance Actuator (MeRIA). © 2017

关键词： gain-scheduling Mechatronics rehabilitation robotics robust control variable stiffness actuators

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：