检索结果-内蒙古大学图书馆

2023 IEEE International Conference on Communications, Information, Electronic and Energy systems, CIEES 2023

作者： Kuaban, Godlove Suila Czachorski, Tadeusz Gelenbe, Erol Sharma, Sapana Czekalski, Piotr Gliwice Poland Mmec Maharishi Markandeshwar Department of Mathematics Haryana Mullana133203 India Silesian University of Technology Faculty of Automatic Control Electronics and Informatics Gliwice Poland

ISBN: (纸本)9798350336917

The growing concerns about the resource sustainability and environmental impact of deploying billions or trillions of IoT devices in the various sectors of society or economy have given rise to an energy research field known as Green-IoT (G-IoT). G-IoT emphasises the need to prioritise energy efficiency and the reduction of pollution in the IoT ecosystem. This paper presents a Markov model for a self-powered Green IoT device with state-dependent energy consumption. The model evaluates the energy performance of a self-powered Green IoT device. We derive the probability distribution of the energy content of the battery, including the probability that the energy stored in the battery is completely depleted and the density of the lifetime of the IoT device. We investigate the influence of some design parameters on the results. Introducing the threshold at which the device is forced to enter an energy-saving regime significantly increases a G-IoT device's lifetime. Apart from deploying energy-efficient mechanisms to increase the lifetime of a G-IoT device, integrating an efficient energy harvesting system into the device will increase its lifetime and reduce the frequency of battery replacement. © 2023 IEEE.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

LEARNING CONTINUOUS NORMALIZING FLOWS FOR FASTER CONVERGENCE TO TARGET DISTRIBUTION VIA ASCENT REGULARIZATIONS 11

LEARNING CONTINUOUS NORMALIZING FLOWS FOR FASTER CONVERGENCE...

引用

11th International Conference on Learning Representations, ICLR 2023

作者： Chen, Shuangshuang Ding, Sihao Karayiannidis, Yiannis Björkman, Mårten School of Electrical Engineering and Computer Science Royal Institute of Technology Sweden AI Lab Volvo Car Corporation Sweden Department of Automatic Control Lund University Sweden

Normalizing flows (NFs) have been shown to be advantageous in modeling complex distributions and improving sampling efficiency for unbiased *** this work, we propose a new class of continuous NFs, ascent continuous normalizing flows (ACNFs), that makes a base distribution converge faster to a target *** solving such a flow is non-trivial and barely possible, we propose a practical implementation to learn flexibly parametric ACNFs via ascent regularization and apply it in two learning cases: maximum likelihood learning for density estimation and minimizing reverse KL divergence for unbiased sampling and variational *** learned ACNFs demonstrate faster convergence towards the target distributions, therefore, achieving better density estimations, unbiased sampling and variational approximation at lower computational ***, the flows show to stabilize themselves to mitigate performance deterioration and are less sensitive to the choice of training flow length T. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Maximum likelihood estimation

来源：评论

学校读者我要写书评

暂无评论

Design and Realization of Unmanned Vehicle Autonomous Navigation System Based on Binocular Camera 3

Design and Realization of Unmanned Vehicle Autonomous Naviga...

引用

3rd International Conference on Computer Science, Electronic Information Engineering and Intelligent control technology, CEI 2023

作者： Guo, Tianxing Lin, Lianlei Liu, Huanyu Li, Junbao School of Electronics and Information Engineering Harbin Institute of Technology Department of Automatic Test and Control Harbin China Information Countermeasure Technique Institute School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9798350372052

Aiming at the navigation problem of unmanned vehicles in extreme environments such as communication interference and limited GPS signals, this study proposes an autonomous navigation method based on binocular cameras. The method enables the unmanned vehicle to complete the task of localization and map building using only binocular images, without the need for other sensors or signal sources. Meanwhile, this study also proposes a local path planning obstacle avoidance method based on depth map, which, when combined with global localization information, can take into account both local obstacle avoidance and global path navigation, and can cope with random environmental changes. The system uses a single sensor for autonomous obstacle avoidance and navigation, which reduces the computational requirements and ensures the low cost of the navigation system. In order to verify the reliability and effectiveness of the system under signal-constrained conditions, the system is evaluated in a simulation environment and a real field scenario, respectively. The experimental results show that the system is able to achieve reliable localization and path planning under signal-constrained conditions. © 2023 IEEE.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

A DRL-Based Cluster Scheduling Algorithm Configuration Optimization Approach for Artificial Intelligence Jobs

A DRL-Based Cluster Scheduling Algorithm Configuration Optim...

引用

IEEE International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Shilin Wen Wei Liang Siyan Zhu Ke Qiu Xiaoning Wu Department Three of Command and Control North Automatic Control Technology Institute Taiyuan China School of Computer Science and Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9798350377033

ISBN: (纸本)9798350377040

With the widespread application of machine learning technology across multiple domains, artificial intelligence (AI) jobs have become significant workloads for cloud service providers. However, current cloud platforms rely on pre-set scheduling algorithms, making it difficult to adjust configurations in real-time according to characteristics of AI jobs, thereby limiting job completion efficiency. Additionally, the heterogeneity and dynamism of AI jobs increase the difficulty of resource prediction and scheduling. In order to address this issue, this paper proposes an effective approach based on Deep Reinforcement Learning (DRL), by using DRL technology to adjust scheduling algorithm configurations online, converting the optimization process into a Markov process for model training, so as to optimize configurations in real-time and reduce job completion time. Simultaneously, to shorten the data sampling time for DRL training, this paper develops a cluster simulation scheduler that can efficiently simulate cluster running states, which can accelerate DRL training. Experimental results demonstrate that the simulation scheduler exhibits fast simulation rates and high simulation accuracy, and our proposed approach effectively reduces job completion time in small-scale clusters, thereby enhancing cluster resource utilization.

关键词： Training Electrical engineering Limiting Scheduling algorithms Clustering algorithms Markov processes Real-time systems Resource management Artificial intelligence Optimization

来源：评论

学校读者我要写书评

暂无评论

Interconnecting Separate Transportation systems by Introducing Exchange Points 8

Interconnecting Separate Transportation Systems by Introduci...

引用

8th IEEE International Smart Cities Conference, ISC2 2022

作者： Esztergar-Kiss, Domokos Ansariyar, Alireza Katona, Geza Systems and Control Lab Institute for Computer Science and Control Budapest Hungary Budapest University of Technology and Economics Department of Transport Technology and Economics Budapest Hungary

ISBN: (数字)9781665485616

ISBN: (纸本)9781665485616

To provide seamless information for the travelers, an effective transnational door-to-door journey planner is required, where information from different operators, combined solutions, and value-added parameters appear in a realistic environment. Thus, the aim is to support seamless mobility solutions and create multimodal transport networks connecting separate systems. The elaborated method realizes this by identifying the potential exchange points between separate networks and by filtering the suitable exchange points to run the routing algorithm between the local journey planners. The proposed solution builds on a flexible algorithm, which parameters can be easily updated and extended. In case of any changes, using the formulated theoretical background, an up-to-date and realistic implementation can be derived from the foundations of the framework. In addition, the elaborated method is fully capable to cover wide geographical areas and to provide a transferable solution. © 2022 IEEE.

关键词： Heuristic algorithms

来源：评论

学校读者我要写书评

暂无评论

On the Gaussian Filtering for Nonlinear Dynamic systems Using Variational Inference 27

On the Gaussian Filtering for Nonlinear Dynamic Systems Usin...

引用

27th International Conference on Information Fusion, FUSION 2024

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Li, Ji University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Locaris Electronic Technology Co. Ltd Zhengzhou China

ISBN: (纸本)9781737749769

This paper introduces a new variational Gaussian filtering approach for estimating the state of a nonlinear dynamic system. We first assume that the predictive distribution of the state is Gaussian and derive an iterative method for updating the state posterior in the natural parameter space through KullbackLeibler divergence minimization. The obtained update rule is the same as that of the conjugate-computation variational inference technique in Bayesian learning. The derivation here is simpler and more insightful. We then impose a Wishart prior on the inverse of the state prediction covariance to take into account the impact of approximating the state predictive distribution using a Gaussian density on the state posterior estimation. The prediction covariance is identified jointly with the state using variational inference and the established state posterior update rule to achieve the desired Gaussian filtering. Simulation study examines the performance of the proposed filtering framework in target tracking based on bearing and range measurements. © 2024 ISIF.

关键词： Wiener filtering

来源：评论

学校读者我要写书评

暂无评论

Diagonally Square Root Integrable Kernels in System Identification

arXiv

引用

arXiv 2023年

作者： Khosravi, Mohammad Smith, Roy S. Delft Center for Systems and Control Delft University of Technology Netherlands Automatic Control Laboratory ETH Zürich Switzerland

In recent years, the reproducing kernel Hilbert space (RKHS) theory has played a crucial role in linear system identification. The core of a RKHS is the associated kernel characterizing its properties. Accordingly, this work studies the class of diagonally square root integrable (DSRI) kernels. We demonstrate that various well-known stable kernels introduced in system identification belong to this category. Moreover, it is shown that any DSRI kernel is also stable and integrable. We look into certain topological features of the RKHSs associated with DSRI kernels, particularly the continuity of linear operators defined on the respective RKHSs. For the stability of a Gaussian process centered at a stable impulse response, we show that the necessary and sufficient condition is the diagonally square root integrability of the corresponding kernel. Furthermore, we elaborate on this result by providing proper interpretations. Copyright © 2023, The Authors. All rights reserved.

关键词： Impulse response

来源：评论

学校读者我要写书评

暂无评论

How improving performance may imply losing consistency in event-triggered consensus

arXiv

引用

arXiv 2024年

作者： Meister, David Antunes, Duarte J. Allgöwer, Frank University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart Germany Eindhoven University of Technology Eindhoven Netherlands

Event-triggered control is often argued to lower the average triggering rate compared to time-triggered control while still achieving a desired control goal, e.g., the same performance level. However, this property, often called consistency, cannot be taken for granted and can be hard to analyze in many settings. In particular, although numerous decentralized event-triggered control schemes have been proposed in the past years, their performance properties with respect to time-triggered control remain mostly unexplored. In this paper, we therefore examine the performance properties of event-triggered control (relative to time-triggered control) for a single-integrator consensus problem with a level-triggering rule. We consider the long-term average quadratic deviation from consensus as a performance measure. For this setting, we show that enriching the information the local controllers use improves the performance of the consensus algorithm but renders a previously consistent event-triggered control scheme inconsistent. In addition, we do so while deploying optimal control inputs which we derive for both information cases and all triggering schemes. With this insight, we can furthermore explain the relationship between two contrasting consistency results from the literature on decentralized event-triggered control. We support our theoretical findings with simulation results. © 2024, CC BY-NC-ND.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Diagnosing faults in electric motors using B-splines and Bayesian Mixture Model

Diagnosing faults in electric motors using B-splines and Bay...

引用

International Conference on Methods and Models in Automation and Robotics (MMAR)

作者： Kacper Jarzyna Bartłomiej Gawęda Jerzy Baranowski Department of Automatic Control & Robotics AGH University of Science & Technology Kraków Poland

ISBN: (数字)9798350362343

ISBN: (纸本)9798350362350

Diagnosing faults in electric motors is crucial for various applications, from everyday devices to industrial machinery. Authors propose a method for identifying motor faults using acoustic signals, which are easy to capture with microphones. Proposed approach involves analyzing these signals using Functional Data Analysis (FDA), representing frequency patterns with B-splines and Bayesian Mixture Model as classifier. In this paper, there was developed a classifier to categorize five motor fault types based on these transformed signals. By focusing on frequencies up to 2500 Hz relevant to motor issues, authors aim to detect faults without needing complex equipment and greatly shorten computation time. This approach yields promising results.

关键词： Fault diagnosis Time-frequency analysis Electric potential Focusing Mixture models Bayes methods Splines (mathematics)

来源：评论

学校读者我要写书评

暂无评论

Locating Faults on Overhead Power Transmission Lines of 110 kV and Above Using Emergency Mode Parameters

Locating Faults on Overhead Power Transmission Lines of 110 ...

引用

International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Dmitriy Sharygin Galina Filatova Andrey Yablokov Department of electric power systems automatic control Ivanovo State Power Engineering University (ISPU) Ivanovo Russia

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

The article is devoted to the development of new fault location algorithms based on emergency mode parameters at instantaneous values on overhead power transmission lines of 110 kV and above. Increasing the accuracy of fault location algorithms is an important and urgent task. The methodological and simulation errors of fault location are directly related to the configuration of the power transmission line. The presence of parallel power transmission lines, mutual induction or branch substations affects the accuracy of fault location. In this work, the authors modernize their own previously developed fault location algorithms based on instantaneous values for complex power transmission line configurations. The developed fault location algorithms do not require additional corrections or means for processing primary signals and can be successfully applied when using data from digital in-strumental transformers. The studies of the algorithms were carried out on the simulation models of the overhead power lines in the Simulink/MATLAB software package. The remote fault location of the damage was carried out according to the parameters of the emergency mode. The assignment of parameters for the simulation modeling is carried out using the Monte Carlo method with subsequent statistical processing of the results and the construction of a justified inspection zone.

关键词： Instrument transformers Power transmission lines Accuracy Substations Voltage measurement Software packages Software algorithms Fault location Inspection Transmission line measurements

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：