检索结果-内蒙古大学图书馆

Internationaler ETG-Kongress 2019: Das Gesamtsystem im Fokusder Energiewende - International ETG Congress 2019: The Overall System in the Focus of the Energy Turnaround

作者： Appino, Riccardo Remo González Ordiano, Jorge Ángel Munzke, Nina Mikut, Ralf Faulwasser, Timm Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany Institute of Electrotechnical Engineering Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany

ISBN: (纸本)9783800749553

Effective scheduling of the power exchange with an external grid is of interest for clusters of devices (including consumption, generation and storage) that aim to participate in energy markets. Scheduling is often performed by means of optimization-based algorithms considering uncertain forecasts of inflexible generation and consumption. In this paper, we assess the performance of a previously proposed scheduling algorithm—based on non-parametric probabilistic forecasts both in terms of power and energy—in a realistic industrial campus setting. Simulation results using real data from the KIT north campus underpin the applicability of the proposed algorithm. © VDE VERLAG GMBH Â Berlin Â Offenbach

关键词： Scheduling algorithms

来源：评论

学校读者我要写书评

暂无评论

Corrigendum to “ALDI++: Automatic and parameter-less discord and outlier detection for building energy load profiles” [Energy Build. 265 (2022) 112096]

引用

Energy and Buildings 2023年 286卷

作者： Matias Quintana Till Stoeckmann June Young Park Marian Turowski Veit Hagenmeyer Clayton Miller College of Design and Engineering National University of Singapore Singapore Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Department of Civil Engineering University of Texas at Arlington USA

来源：评论

学校读者我要写书评

暂无评论

Evaluating Ensemble Post-Processing for Wind Power Forecasts

arXiv

引用

arXiv 2020年

作者： Phipps, Kaleb Lerch, Sebastian Andersson, Maria Mikut, Ralf Hagenmeyer, Veit Ludwig, Nicole Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Department of Economics Karlsruhe Institute of Technology Germany Department of Management and Engineering Division of Energy Systems Linköping University Sweden Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany Excellence Machine Learning University of Tübingen Germany

Capturing the uncertainty in probabilistic wind power forecasts is challenging, especially when uncertain input variables, such as the weather, play a role. Since ensemble weather predictions aim to capture the uncertainty in the weather system, they can be used to propagate this uncertainty through to subsequent wind power forecasting models. However, as weather ensemble systems are known to be biased and underdispersed, meteorologists post-process the ensembles. This postprocessing can successfully correct the biases in the weather variables but has not been evaluated thoroughly in the context of subsequent forecasts, such as wind power generation forecasts. Copyright © 2020, The Authors. All rights reserved.

关键词： Electric power generation

来源：评论

学校读者我要写书评

暂无评论

Diagnostics of the machines and devices based on the simatic prodiag 9th

Diagnostics of the machines and devices based on the simatic...

引用

9th Computer Science On-line Conference, CSOC 2020

作者： Kopcek, Michal Fackova, Miroslava Faculty of Materials Science and Technology in Trnava Institute of Applied Informatics Automation and Mechatronics in Bratislava Slovak University of Technology J. Bottu 52 Trnava91724 Slovakia

ISBN: (纸本)9783030519735

The paper is focused on the diagnostics of machines and devices based on the SIMATIC ProDiag library for the machines produced by company Skartek, s. r. o. The first part is dedicated to theoretical problem description and analysis. The next part of the work describes a sample example with configuration of supervisions, which serves as a demonstration for the implementation of the ProDiag library. Testing of the example and the implemented ProDiag library functions are followed by an evaluation of the ProDiag library’s utility within production of the Skartek company. The next part is comparison of alarm handling by conventional ways and by using the ProDiag library. At the end we will show the advantages and disadvantages of the shown methods of alarm handling. © Springer Nature Switzerland AG 2020.

关键词： Alarm systems

来源：评论

学校读者我要写书评

暂无评论

Departure Counting Process in a Finite-Buffer Queue with Batch Arrivals and Multiple Vacation Policy

SSRN

引用

SSRN 2024年

作者： Marjasz, Rafal Kempa, Wojciech M. Kovtun, Viacheslav Institute of Theoretical and Applied Informatics Polish Academy of Sciences 5 Baltycka Str. Gliwice44-100 Poland Silesian University of Technology Faculty of Applied Mathematics 23 Kaszubska Str. Gliwice44-100 Poland Vinnytsia National Technical University Faculty of Intelligent Information Technologies and Automation Department of Computer Control Systems 95 Khmelnitske Shose Str. Vinnytsia21000 Ukraine

The study investigates the departure counting process in a finite-buffer queueing system with batch arrivals and multiple vacation policy. A representation for the mixed double transform of the number of departures up to the fixed time moment is obtained in the explicit form applying analytic approach based on integral equations and linear algebra. Numerical study is attached that focuses on understanding the impact of various system parameters on the behaviour of the mean number of packets processed within a fixed time frame. Utilizing numerical experiments, the study examines the influence of vacation duration, initial buffer state, arrival intensity, and processing rate on the departure process. Results reveal significant dependencies between these parameters and the transient behaviour of the queueing system. Notably, the service speed parameter demonstrates the most substantial influence on the mean number of processed packets, followed by the arrival rate. Conversely, variations in vacation duration and initial packet count exhibit comparatively minor effects on system behaviour. Overall, the findings provide valuable insights into the dynamics of departure processes in finite-buffer queue systems with batch arrivals and multiple vacation policies, offering implications for system optimization and performance enhancement strategies. © 2024, The Authors. All rights reserved.

关键词： Integral equations

来源：评论

学校读者我要写书评

暂无评论

ED4GAP: Efficient Detection for GOOSE-Based Poisoning Attacks on IEC 61850 Substations

ED4GAP: Efficient Detection for GOOSE-Based Poisoning Attack...

引用

IEEE International Conference on Smart Grid Communications (SmartGridComm)

作者： Atul Bohara Jordi Ros-Giralt Ghada Elbez Alfonso Valdes Klara Nahrstedt William H. Sanders Information Trust Institute University of Illinois at Urbana-Champaign Reservoir Labs Institute of Automation and Applied Informatics Karlsruhe Institute of Technology

ISBN: (数字)9781728161273

ISBN: (纸本)9781728163598

Devices in IEC 61850 substations use the generic object-oriented substation events (GOOSE) protocol to exchange protection-related events. Because of its lack of authentication and encryption, GOOSE is vulnerable to man-in-the-middle attacks. An adversary with access to the substation network can inject carefully crafted messages to impact the grid's availability. One of the most common such attacks, GOOSE-based poisoning, modifies the StNum and SqNum fields in the protocol data unit to take over GOOSE publications. We present ED4GAP, a network- level system for efficient detection of the poisoning attacks. We define a finite state machine model for network communication concerning the attacks. Guided by the model, ED4GAP analyzes network traffic out-of-band and detects attacks in real-time. We implement a prototype of the system and evaluate its detection accuracy. We provide a systematic approach to assessing bottlenecks, improving performance, and demonstrating that ED4GAP has low overhead and meets GOOSE's timing constraints.

关键词： Substations Protocols Relays IEC Standards Security Real-time systems Ethernet

来源：评论

学校读者我要写书评

暂无评论

*** – A Julia Package for Polynomial Chaos in Systems and Control

arXiv

引用

arXiv 2020年

作者： Mühlpfordt, Tillmann Zahn, Frederik Hagenmeyer, Veit Faulwasser, Timm Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Department of Electrical Engineering and Information Technology Technical University Dortmund Dortmund Germany

Polynomial chaos expansion (pce) is an increasingly popular technique for uncertainty propagation and quantification in systems and control. Based on the theory of Hilbert spaces and orthogonal polynomials, pce allows for a unifying mathematical framework to study systems under arbitrary uncertainties of finite variance;we introduce this problem as a so-called mapping under uncertainty. For practical pce-based applications we require orthogonal polynomials relative to given probability densities, and their quadrature rules. With *** we provide a Julia software package that delivers the desired functionality: given a probability density function, *** offers several numerical routines to construct the respective orthogonal polynomials, and the quadrature rules together with tensorized scalar products. *** is the first pce-related software written in Julia, a scientific programming language that combines the readability of scripted languages with the speed of compiled languages. We provide illustrating numerical examples that show both pce and *** in action. Copyright © 2020, The Authors. All rights reserved.

关键词： Orthogonal functions

来源：评论

学校读者我要写书评

暂无评论

Automated File Labeling for Heterogeneous Files Organization Using Machine Learning

引用

Computers, Materials & Continua 2023年第2期74卷 3263-3278页

作者： Sagheer Abbas Syed Ali Raza MAKhan Muhammad Adnan Khan Atta-ur-Rahman Kiran Sultan Amir Mosavi School of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science GC University LahorePakistan Riphah School of Computing&Innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Software Pattern Recognition and Machine Learning LabGachon UniversitySeongnam13120Korea Department of Computer Science College of Computer Science and Information Technology(CCSIT)Imam Abdulrahman Bin Faisal University(IAU)P.O.Box 1982Dammam31441Saudi Arabia Department of CIT The Applied CollegeKing Abdulaziz UniversityJeddah31261Saudi Arabia John von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Institute of Information Engineering Automation and MathematicsSlovak University of Technology in BratislavaBratislava81107Slovakia Faculty of Civil Engineering TU-DresdenDresden01062Germany

File labeling techniques have a long history in analyzing the anthological trends in computational *** situation becomes worse in the case of files downloaded into systems from the ***,most users either have to change file names manually or leave a meaningless name of the files,which increases the time to search required files and results in redundancy and duplications of user ***,no significant work is done on automated file labeling during the organization of heterogeneous user files.A few attempts have been made in topic ***,one major drawback of current topic modeling approaches is better *** rely on specific language types and domain similarity of the *** this research,machine learning approaches have been employed to analyze and extract the information from heterogeneous corpus.A different file labeling technique has also been used to get the meaningful and`cohesive topic of the *** results show that the proposed methodology can generate relevant and context-sensitive names for heterogeneous data files and provide additional insight into automated file labeling in operating systems.

关键词： Automated file labeling file organization machine learning topic modeling

来源：评论

学校读者我要写书评

暂无评论

FedKDC: Consensus-Driven Knowledge Distillation for Personalized Federated Learning in EEG-Based Emotion Recognition

引用

IEEE Journal of Biomedical and Health informatics 2025年 PP卷 PP页

作者： Qiu, Xihang Qiu, Wanyong Zhang, Ye Qian, Kun Li, Chun Hu, Bin Schuller, Bjorn W. Yamamoto, Yoshiharu Beijing100081 China Beijing Institute of Technology School of Automation School of Medical Technology Beijing100081 China Shenzhen MSU-BIT University MSU-BIT-SMBU Joint Research Center of Applied Mathematics Shenzhen518172 China Beijing Institute of Technology School of Mathematics and Statistics Beijing100081 China Imperial College London GLAM – the Group on Language Audio & Music LondonSW7 2AZ United Kingdom Technische Universität München CHI Chair of Health Informatics Munich80333 Germany Germany Educational Physiology Laboratory Graduate School of Education University of Tokyo Tokyo1138654 Japan

Federated learning (FL) has gained prominence in electroencephalogram (EEG)-based emotion recognition because of its ability to enable secure collaborative training without centralized data. However, traditional FL faces challenges due to model and data heterogeneity in smart healthcare settings. For example, medical institutions have varying computational resources, which creates a need for personalized local models. Moreover, EEG data from medical institutions typically face data heterogeneity issues stemming from limitations in participant availability, ethical constraints, and cultural differences among subjects, which can slow model convergence and degrade model performance. To address these challenges, we propose FedKDC, a novel FL framework that incorporates clustered knowledge distillation (CKD). This method introduces a consensus-based distributed learning mechanism to facilitate the clustering process. It then enhances the convergence speed through intraclass distillation and reduces the negative impact of heterogeneity through interclass distillation. Additionally, we introduce a DriftGuard mechanism to mitigate client drift, along with an entropy reducer to decrease the entropy of aggregated knowledge. The framework is validated on the SEED, SEED-IV, SEED-FRA, and SEED-GER datasets, demonstrating its effectiveness in scenarios where both the data and the models are heterogeneous. Experimental results show that FedKDC outperforms other FL frameworks in emotion recognition, achieving a maximum average accuracy of 85.2%, and in convergence efficiency, with faster and more stable convergence. © 2013 IEEE.

关键词： Federated learning

来源：评论

学校读者我要写书评

暂无评论

Evaluating contextualized language models for Hungarian

arXiv

引用

arXiv 2021年

作者： Ács, Judit Lévai, Dániel Nemeskey, Dávid Márk Kornai, András Department of Automation and Applied Informatics Budapest University of Technology and Economics Hungary Institute for Computer Science and Control Hungary Alfréd Rényi Institute of Mathematics Hungary

We present an extended comparison of contextualized language models for Hungarian. We compare huBERT, a Hungarian model against 4 multilingual models including the multilingual BERT model. We evaluate these models through three tasks, morphological probing, POS tagging and NER. We find that huBERT works better than the other models, often by a large margin, particularly near the global optimum (typically at the middle layers). We also find that huBERT tends to generate fewer subwords for one word and that using the last subword for token-level tasks is generally a better choice than using the first one. Copyright © 2021, The Authors. All rights reserved.

关键词： Computational linguistics

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：