检索结果-内蒙古大学图书馆

Boost short-term load forecasts with synthetic data from transferred latent space information

Energy informatics 2022年第1期5卷 1-20页

作者： Heidrich, Benedikt Mannsperger, Lisa Turowski, Marian Phipps, Kaleb Schäfer, Benjamin Mikut, Ralf Hagenmeyer, Veit Karlsruhe Institute of Technology Institute for Automation and Applied Informatics Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen76344 Germany

Sustainable energy systems are characterised by an increased integration of renewable energy sources, which magnifies the fluctuations in energy supply. Methods to to cope with these magnified fluctuations, such as load shifting, typically require accurate short-term load forecasts. Although numerous machine learning models have been developed to improve short-term load forecasting (STLF), these models often require large amounts of training data. Unfortunately, such data is usually not available, for example, due to new users or privacy concerns. Therefore, obtaining accurate short-term load forecasts with little data is a major challenge. The present paper thus proposes the latent space-based forecast enhancer (LSFE), a method which combines transfer learning and data augmentation to enhance STLF when training data is limited. The LSFE first trains a generative model on source data similar to the target data before using the latent space data representation of the target data to generate seed noise. Finally, we use this seed noise to generate synthetic data, which we combine with real data to enhance STLF. We evaluate the LSFE on real-world electricity data by examining the influence of its components, analysing its influence on obtained forecasts, and comparing its performance to benchmark models. We show that the Latent Space-based Forecast Enhancer is generally capable of improving the forecast accuracy and thus helps to successfully meet the challenge of limited available training data. © 2022, The Author(s).

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

A Lightweight Framework for Semantic Segmentation of Biomedical Images

引用

Current Directions in Biomedical Engineering 2023年第1期9卷 190-193页

作者： Rieken Munke, Friedrich Rettenberger, Luca Reischl, Markus Popova, Anna Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany Institute of Biological and Chemical Systems-Functional and Molecular Systems Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany

We introduce a lightweight framework for semantic segmentation that utilizes structured classifiers as an alternative to deep learning methods. Biomedical data is known for being scarce and difficult to label. However, this framework provides a lightweight, easy-to-apply, and fast-to-train approach that can be adapted to changes in image material though efficient retraining. Moreover, the framework is able to adapt to various input sizes making it robust against changes in resolution and is not tied to specialized hardware, which allows efficient application on standard laptops or desktops without GPUs. We benchmark two distinct models, a single structured classifier and an ensemble of structured classifiers, against a U-Net, evaluating overall performance and training speed. The framework is versatile and can be applied to multi-class semantic segmentation. Our study shows that the proposed framework can effectively compete with established deep learning methods on diverse datasets in terms of performance while reducing training time immensely. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Semantic Segmentation

来源：评论

学校读者我要写书评

暂无评论

Breakthrough in permanent cooling of instrumentation electronics - Results of systematic experimental & Analytical refrigerant selection, dynamic seals evaluation and robust engine design

Breakthrough in permanent cooling of instrumentation electro...

引用

Geothermal Resources Council 2018 Annual Meeting: Geothermal's Role in Today's Energy Market, GRC 2018

作者： Holbein, Benedict Karlsruhe Institute of Technology KIT Institute for Automation and Applied Informatics Germany

ISBN: (纸本)0934412235

In the latest compressor tests for continuous cooling of instrumentation electronics runtimes over 200 hours have been reached. Electronic temperatures have been held below 125°C. Different dynamic seal materials and designs in combination with alcohols and solvents as potential refrigerants are evaluated in an environment with 200°C ambient temperature. The overall target is the completion of a compression cooling system for permanent conditioning of downhole electronics below 100°C, running at ambient temperature above 200°C. This will enable the use of standard electronics providing a huge range of functional flexibility and high computational power for data processing with strongly extended duration of use. Besides reliable temperature conditions are not only beneficial for electronics performance but also for well manipulation, solid sampling, maintenance and other downhole operations that require an extensive electronic complexity. Additional result of ongoing work is the development of components with innovative, experimentally approved design, including an evaporator with capillary transport, high temperature dynamic seals and pistons for minimized damage volume. The currently running experiments on different sub-systems with specifically constructed test-beds are targeting the optimization of process parameters and piecewise merging of a complete cycle. In parallel a compressor engine for increased efficiency based on available HT EC motor was designed. The development of a complete system design for modular extension and integration in instrumentation devices will be completed within the next 5 months. © 2018 International Journal of Caring Sciences. All rights reserved.

关键词： Refrigerants

来源：评论

学校读者我要写书评

暂无评论

Light-Field Camera Based Spatial Multiple Small Particle Tracking with Post-processing

Light-Field Camera Based Spatial Multiple Small Particle Tra...

引用

International Symposium on automation, Mechanical and Design Engineering, SAMDE 2021

作者： Zhang, Miao Matthes, Jörg Aleksandrov, Krasimir Gehrmann, Hans-Joachim Vogelbacher, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany Institute for Technical Chemistry Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9783031099083

Multi-object detection and tracking is one of the most significant tasks in computer vision, which has been widely applied in various fields, such as biomedicine, automatic driving, and video surveillance. In our project, we aim to investigate the flight behavior of different small refuse-derived fuel particles (e.g., plastic, wood, paper, etc.) with sizes around 5 to 30 mm, which are blown into a combustion chamber (rotary kiln) via a lance, by detecting and tracking the particles. By utilizing a calibrated light-field camera, both 2D gray value images and 3D information, including the depth of the scene, are available for investigation. To obtain particle trajectories, accurate temporal localization of the particles is necessary. Thus, we perform an approach combining a 2D detection method and a 3D clustering method for precise detection of the particles at first. Subsequently, the temporal 2D particle localizations are associated into tracklets based on the Kalman filter state estimator and the global nearest neighbor algorithm. Owing to the wrong and incomplete tracklets caused by several inaccurate detections, we present a post-processing method to enhance the tracking performance in the paper. Finally, the optimized 2D particle trajectories are converted into 3D trajectories, and these obtained 3D particle trajectories are analyzed by a polynomial regression for further analysis of the particle flight behavior. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

Impact of Annotation Noise on Histopathology Nucleus Segmentation

引用

Current Directions in Biomedical Engineering 2022年第2期8卷 197-200页

作者： Schilling, Marcel P. Ahuja, Niket Rettenberger, Luca Scherr, Tim Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen 76344 Germany

Deep learning is often used for automated diagnosis support in biomedical image processing scenarios. Annotated datasets are essential for the supervised training of deep neural networks. The problem of consistent and noise-free annotation remains for experts such as pathologists. The variability within an annotator (intra) and the variability between annotators (inter) are current challenges. In clinical practice or biology, instance segmentation is a common task, but a comprehensive and quantitative study regarding the impact of noisy annotations lacks. In this paper, we present a concept to categorize and simulate various types of annotation noise as well as an evaluation of the impact on deep learning pipelines. Thereby, we use the multi-organ histology image dataset MoNuSeg to discuss the influence of annotator variability. We provide annotation recommendations for clinicians to achieve high-quality automated diagnostic algorithms. © 2022 The Author(s), published by De Gruyter.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

Unsupervised GAN epoch selection for biomedical data synthesis

引用

Current Directions in Biomedical Engineering 2023年第1期9卷 467-470页

作者： Böhland, Moritz Bruch, Roman Löffler, Katharina Reischl, Markus Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Hermann-von-Helmholtz-Platz 1 Eggenstein-Leopoldshafen 76344 Germany

Supervised Neural Networks are used for segmentation in many biological and biomedical applications. To omit the time-consuming and tiring process of manual labeling, unsupervised Generative Adversarial Networks (GANs) can be used to synthesize labeled data. However, the training of GANs requires extensive computation and is often unstable. Due to the lack of established stopping criteria, GANs are usually trained multiple times for a heuristically fixed number of epochs. Early stopping and epoch selection can lead to better synthetic datasets resulting in higher downstream segmentation quality on biological or medical data. This article examines whether the Frechet Inception Distance (FID), the Kernel Inception Distance (KID), or the WeightWatcher tool can be used for early stopping or epoch selection of unsupervised GANs. The experiments show that the last trained GAN epoch is not necessarily the best one to synthesize downstream segmentation data. On complex datasets, FID and KID correlate with the downstream segmentation quality, and both can be used for epoch selection. © 2023 the author(s), published by Walter de Gruyter Berlin/Boston.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Simulation-Based Metrological Temperature Ensuring and Control of the Temperature Field in an Induction Furnace Based on Various Parameters

Simulation-Based Metrological Temperature Ensuring and Contr...

引用

International Conference on Computer and automation Engineering, ICCAE

作者： Jan Rybář Samuel Emebu Sayed Yousuf Sayed Sohaibullah Zarghoon Lukáš Bartalský Peter Onderčo Andrej Smetánka Radek Matušů Faculty of Mechanical Engineering Institute of Automation Informatization and Measurement Slovak University of Technology Bratislava Slovakia Department of Separation Science LUT School of Engineering Science Lappeenranta-Lahti University of Technology Lappeenranta Finland Department of Auto mechanical Engineering Faculty of Electro-Mechanic Kabul Polytechnic University Kabul Afghanistan Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Zlín Czech Republic

ISBN: (数字)9798331533816

ISBN: (纸本)9798331533823

Induction heating is widely used in industrial furnaces because of its rapid response time and high energy efficiency. To design and optimize these furnaces, computer-aided simulations are essential. This study aims to develop an accurate temperature field model for a square cross-section steel billet in an induction furnace by leveraging various parameters in COMSOL Multiphysics software. The simulation analysis incorporated temperature dynamics, considering skin depth, temperaturedependent, and constant parameters of the steel billet. The datadriven model was converted into a state-space representation utilizing MATLAB's System Identification Toolbox. This conversion facilitated the design of a Linear Quadratic Regulator (LQR) with integral gain and pole placement. Further, these controllers' performance was analyzed, and controllers were successfully implemented to regulate the temperature field of the billet from initial temperature to reference temperature, utilizing the distributed parameter system control circuit.

关键词： Billets Analytical models Temperature Accuracy Computational modeling Furnaces Mathematical models Temperature control Steel Induction heating

来源：评论

学校读者我要写书评

暂无评论

Uncertainty Quantification for Optimal Power Flow Problems

Uncertainty Quantification for Optimal Power Flow Problems

引用

90th Annual Meeting of the International Association of applied Mathematics and Mechanics, GAMM 2019

作者： Mühlpfordt, Tillmann Hagenmeyer, Veit Faulwasser, Timm Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Karlsruhe Germany

The need to de-carbonize the current energy infrastructure, and the increasing integration of renewables pose a number of difficult control and optimization problems. Among those, the optimal power flow (OPF) problem—i.e., the task to minimize power system operation costs while maintaining technical and network limitations—is key for operational planning of power systems. The influx of inherently volatile renewable energy sources calls for methods that allow to consider stochasticity directly in the OPF problem. Here, we present recent results on uncertainty quantification for OPF problems. Modeling uncertainties as second-order continuous random variables, we will show that the OPF problem subject to stochastic uncertainties can be posed as an infinite-dimensional L2-problem. A tractable reformulation thereof can be obtained using polynomial chaos expansion (PCE), under mild assumptions. We will show advantageous features of PCE for OPF subject to stochastic uncertainties. For example, multivariate non-Gaussian uncertainties can be considered easily. Finally, we comment on recent progress on a Julia package for PCE. © 2019 The Authors Proceedings in applied Mathematics & Mechanics published by Wiley-VCH Verlag GmbH & Co. KGaA Weinheim.

关键词： Uncertainty analysis

来源：评论

学校读者我要写书评

暂无评论

Data analytics in the electricity sector – A quantitative and qualitative literature review

引用

Energy and AI 2020年第1期1卷 145-167页

作者： Frederik vom Scheidt Hana Medinova Nicole Ludwig Bent Richter Philipp Staudt Christof Weinhardt Institute for Information Systems and Marketing Karlsruhe Institute of TechnologyKaiserstr.8976133 KarlsruheGermany Institute for Automation and Applied Informatics Karlsruhe Institute of TechnologyHermann-von-Helmholtz-Platz 176344 Eggenstein-LeopoldshafenGermany

The rapid transformation of the electricity sector increases both the opportunities and the need for Data *** recent years,various new methods and fields of application have been *** research is growing and becoming more diverse and specialized,it is essential to integrate and structure the fragmented body of scientific *** therefore conduct a systematic review of studies concerned with developing and applying Data Analytics methods in the context of the electricity value ***,we provide a quantitative high-level overview of the status quo of Data Analytics research,and show historical literature growth,leading countries in the field and the most intensive international ***,we qualitatively review over 200 high-impact studies to present an in-depth analysis of the most prominent applications of Data Analytics in each of the electricity sector’s areas:generation,trading,transmission,distribution,and *** each area,we review the state-of-the-art Data Analytics applications and *** addition,we discuss used data sets,feature selection methods,benchmark methods,evaluation metrics,and model complexity and run *** the findings from the different areas,we identify best practices and what researchers in one area can learn from other ***,we highlight potential for future research.

关键词： Data analytics Electricity Machine learning Generation Price Transmission Distribution Consumption

来源：评论

学校读者我要写书评

暂无评论

An Optimization-based Approach for Automated Generation of Residential Low-Voltage Grid Models Using Open Data and Open Source Software

An Optimization-based Approach for Automated Generation of R...

引用

2022 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2022

作者： Cakmak, Huseyin K. Janecke, Luc Weber, Moritz Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Eggenstein-Leopoldshafen Germany

ISBN: (数字)9781665480321

ISBN: (纸本)9781665480321

The contribution of the present paper is a new, more refined method for the automated creation of large-scale detailed distribution grid models based solely on publicly available GIS and statistical data. Utilizing the street layouts in Open Street Maps as potential cable routes, a graph representation is created and complemented by residential units that are extracted from the same data source. This graph structure is adjusted to match the electrical low-voltage grid topology by solving a variation of the minimum cost flow linear optimization problem with provided data on secondary substations. In a final step, the generated grid representation is transferred to a DIgSILENT PowerFactory model including photovoltaic systems. The presented workflow uses open source software and is fully automated and scalable. It allows the generation of ready-to-use distribution grid simulation models for given 20kV substation locations and additional data on residential unit properties for improved results. The performance of the developed method with respect to grid utilization is presented for a selected suburban residential area with power flow simulations for eight scenarios including current residential photovoltaic installation and a future scenario with full photovoltaic expansion. For the latter, the simulation results indicate heavy congestion in the low-voltage grid for full photovoltaic capacity deployment without batteries. Furthermore, the suitability of the generated models for quasi-dynamic simulations is shown. © 2022 IEEE.

关键词： Open source software

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：