检索结果-内蒙古大学图书馆

27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Mohebbi, Mohammad Reza Hassan Zada, Mohammad Javad Rostami-Shahrbabaki, Majid Doller, Mario Yamnenko, Iuliia University of Applied Sciences Josef Ressel Center Vision2Move Project Tirol Kufstein Austria University of Passau Department of Computer Science Germany Technical University of Munich Traffic Engineering and Control Germany National Technical University of Ukraine Igor Sikorsky Kyiv Polytechnic Institute Department of Electronic Devices and Systems Kyiv Ukraine

ISBN: (纸本)9798331505929

Accurate short-term network-wide traffic prediction is essential to guarantee high service quality in urban traffic control systems. Nevertheless, traffic state time series represent network-scale spatiotemporal co-movement patterns and location-specific features. Therefore, hybrid statistical machine learning (ml) algorithms could be utilized to accommodate the aforementioned characteristics. In this paper, a hybrid random forest (rf) and extreme gradient boosting tree (XGBoost) model is introduced for network-wide traffic prediction. Moreover, a multi-noise oriented basis wavelet transform (OBT) filter is employed to pre-process the original time series, and improve the predictive accuracy. The RF model captures the traffic co-movements and the XGBoost extracts the local information. Comparative analysis of the hybrid algorithm and deep learning-based benchmarks indicate better performance of the proposed methodology in hourly traffic state prediction of 30 loop detectors, located in the paris city center. Hence, the hybrid decision-tree-based mechanism is a useful framework for real-time network traffic forecasting offering fewer trainable (hyper-)parameters, and thus, lower computational cost. © 2024 IEEE.

关键词： Time series

来源：评论

学校读者我要写书评

暂无评论

Laundry Cluster Management Using Cloud 18

Laundry Cluster Management Using Cloud

引用

18th Conference on computer Science and Intelligence systems, FedCSIS 2023

作者： Salach, Mateusz Trybus, Bartosz Pawlowicz, Bartosz Hubacz, Marcin Department of Complex Systems Rzeszow University of Technology Al. Powstancow Warszawy 12 Rzeszow35-959 Poland Department of Computer and Control Engineering Rzeszow University of Technology Al. Powstancow Warszawy 12 Rzeszow35-959 Poland Department of Electronic and Telecommunications Systems Rzeszow University of Technology Al. Powstancow Warszawy 12 Rzeszow35-959 Poland

ISBN: (纸本)9788396744784

Electronic devices in the 21st century have numerous network components, including wireless or wired Internet access modules. Connecting devices to networks and cloud services enables them to access new functionalities and unlock system updates and device security enhancements. The article presents the concept of an intelligent laundry management system based on RFID and cloud computing. The Internet connection not only unlocks additional features of the washing machine, such as different washing modes, but also allows for selecting the appropriate detergent level and washing parameters based on the textile material being washed. Additionally, the paper presents the solution and measurement studies on the accuracy of textile identification. © 2023 Polish Information Processing Society.

关键词： Washing

来源：评论

学校读者我要写书评

暂无评论

Metaheuristic Optimization Through Deep Learning Classification of COVID-19 in Chest X-Ray Images

引用

computers, Materials & Continua 2022年第11期73卷 4193-4210页

作者： Nagwan Abdel Samee El-Sayed M.El-Kenawy Ghada Atteia Mona M.Jamjoom Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Noha E.El-Attar Tarek Gaber Adam Slowik Mahmoud Y.Shams Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura 35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura 35712Egypt Department of Computer Sciences College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh 11671Saudi Arabia Computer Engineering and Control Systems Department Faculty of EngineeringMansoura University35516MansouraEgypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams University11566CairoEgypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Faculty of Computers and Artificial Intelligence Benha UniversityEgypt School of Science Engineeringand EnvironmentUniversity of SalfordUK Faculty of Computers and Informatics Suez Canal UniversityIsmailia41522Egypt Koszalin University of Technology Poland Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt

As corona virus disease(COVID-19)is still an ongoing global outbreak,countries around the world continue to take precautions and measures to control the spread of the *** of the excessive number of infected patients and the resulting deficiency of testing kits in hospitals,a rapid,reliable,and automatic detection of COVID-19 is in extreme need to curb the number of *** analyzing the COVID-19 chest X-ray images,a novel metaheuristic approach is proposed based on hybrid dipper throated and particle swarm *** lung region was segmented from the original chest X-ray images and augmented using various transformation ***,the augmented images were fed into the VGG19 deep network for feature *** the other hand,a feature selection method is proposed to select the most significant features that can boost the classification ***,the selected features were input into an optimized neural network for *** neural network is optimized using the proposed hybrid *** experimental results showed that the proposed method achieved 99.88%accuracy,outperforming the existing COVID-19 detection *** addition,a deep statistical analysis is performed to study the performance and stability of the proposed *** results confirm the effectiveness and superiority of the proposed approach.

关键词： Covid-19 feature selection dipper throated optimization particle swarm optimization deep learning

来源：评论

学校读者我要写书评

暂无评论

Forecasting-Aided Graphical Learning for Robust State Estimation of Distribution System 1

引用

8th Purple Mountain Forum on Smart Grid Protection and control, PMF 2023

作者： Di, Cao Zhao, Junbo Hu, Jiaxiang Huang, Yuehui Huang, Qi Chen, Zhe Hu, Weihao University of Electronic Science and Technology of China Chengdu China Department of Electrical and Computer Engineering University of Connecticut StorrsCT06269 United States State Key Laboratory of Operation and Control of Renewable Energy and Storage Systems China Electric Power Research Institute Beijing China Department of Energy Technology Aalborg University Pontoppidanstraede 111 Aalborg Denmark

ISBN: (数字)9789819992515

ISBN: (纸本)9789819992508

The forecasting of of pseudo-measurements play an important role in distribution system state estimation (DSSE). This paper proposes robust DSSE method based on forecasting-aided graphical learning method. The nodal power consumption models are first built to produce pseudo-measurements based on deep neural network. Then, the pseudo-measurements and real-time measurements are represented as a graph according to the topology of the distribution network, which are further processed by a graph attention network to capture the mapping relationship between the graphical measurements and the state variables based on the error modeling of pseudo-measurements. The robustness against anomalous measurements is achieved through the embedding of structural information of DN. The modeling of pseudo-measurements further enhance its robustness by guiding the formulation of edge weights of the graph neural network. Comparative tests are carried out on a IEEE 119-node system to demonstrate the effectiveness and robustness of the proposed method. © 2024, State Grid Electric Power.

关键词： Electric power distribution

来源：评论

学校读者我要写书评

暂无评论

A Novel Random Pulse Width Modulation for PMSM Drive System Based on Unified Voltage Modulation

A Novel Random Pulse Width Modulation for PMSM Drive System ...

引用

Energy, Power and Grid (ICEPG), International Conference on

作者： Jinpeng Kan Yongqing Meng Yixin Shi Fengjiao Li Wenjie Chen Changyi Li School of Electrical Engineering Xi’an Jiaotong University Xi’an China Department of Computer and Electronic Systems Engineering AVIC Xi’an Flight Automatic Control Research Institute Xi’an China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

The electromagnetic interference (EMI) problem caused by power electronic switching devices and pulse width modulation (PWM) affects the normal operation of the motor drive system. In this paper, a random PWM based on unified modulation is proposed for permanent magnet synchronous motor (PMSM) drive system. The theoretical basis of unified modulation and the implementation scheme of random modulation are analyzed. Finally, the effectiveness of the proposed random PWM is verified by simulation.

关键词： Motor drives Electromagnetic interference Voltage Switches Pulse width modulation Permanent magnet motors Power electronics Electromagnetics

来源：评论

学校读者我要写书评

暂无评论

A Novel Zero Common-Mode Voltage Modulation Strategy for Dual Three-Phase PWM Inverter Based on Unified Voltage Modulation

A Novel Zero Common-Mode Voltage Modulation Strategy for Dua...

引用

Energy, Power and Electrical engineering (EPEE), International Conference on

作者： Jinpeng Kan Yongqing Meng Changyi Li Wenjie Chen Fengjiao Li Yixin Shi School of Electrical Engineering Xi’an Jiaotong University Xi’an China Department of Computer and Electronic Systems Engineering AVIC Xi’an Flight Automatic Control Research Institute Xi’an China

ISBN: (数字)9798331518066

ISBN: (纸本)9798331518073

Power electronic switching devices and pulse width modulation (PWM) not only improves the performance of motor drive systems, but also brings about common-mode voltage (CMV) issues, that challenging the normal operation of the system. This article proposes a zero common-mode voltage modulation strategy based on unified voltage modulation for a 60° Y-connected six-phase permanent magnet synchronous motor system driven by a dual three-phase inverter. The theoretical basis and zero common-mode implementation scheme of unified modulation are analyzed, and the effectiveness of the proposed zero common-mode voltage modulation strategy is finally verified through simulation.

关键词： Pulse width modulation inverters Performance evaluation Simulation Modulation Voltage Switches Permanent magnet motors Inverters Permanent magnets Switching circuits

来源：评论

学校读者我要写书评

暂无评论

Predicting Off-Design Performance of Axial Compressors Using Multilayer Neural Network Model for Surge control

SSRN

引用

SSRN 2024年

作者： Elmelegy, Mohamed Ali Elhosseini, Mostafa A. Ali, Hesham Arafat Haikal, Amira Y. DLNG Damietta LNG Egypt College of Computer Science and Engineering Taibah University Yanbu Saudi Arabia Department of Computers and Control Systems Engineering Faculty of Engineering Mansoura University Mansoura Egypt

Incidence of surge within axial compressors profoundly influences efficacy, reliability of aero-engines. Conventional methodologies in engine design have predominantly concentrated on precise ,efficient forecasting critical characteristics during such occurrences. paper presents novel approach for predicting surge phenomenon in axial compressors. Surge is a major issue in operation axial compressors, causing reduced performance, increased wear, tear, complete machine failure. proposed approach utilizes NN model based on compressor's design data to forecast behavior of compressor's working map under off-design conditions. model is verified using real data collected over five years during compressor operation, including opening angle (IGV), important parameter often ignored or assumed to be fixed in previous studies. results show NN-based approach effectively predicts compressor's behavior under different operating conditions, providing valuable insights into onset of surge , offering real-time surge prediction ,control ,ability to predict compressor's working map enables optimizing its performance , controlling instability. model was validated by comparing its predictions with real operating conditions observed over five years across various compressor operating modes. As result, predictive model enables safe operation of axial compressors by mitigating instability risks during operation. study's findings highlight model's effectiveness, as evidenced by minimal error observed between predicted and actual data collected across various compressor operating modes. model exhibits strong performance, characterized by high regression factor of 0.92667 , low mean squared error of 3.04465 x 10^-3. numerical values underscore reliability , precision proposed approach in predicting operation of axial compressor under diverse conditions, ultimately contributing to enhanced stability , safety during compressor operations. © 2024, The Authors. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

An Embedded Low-Cost Solution for a Fog Computing Device on the Internet of Things

An Embedded Low-Cost Solution for a Fog Computing Device on ...

引用

International Conference on Fog and Mobile Edge Computing (FMEC)

作者： Pietro D’Agostino Massimo Violante Gianpaolo Macario Department of Control and Computer Engineering (DAUIN) Politecnico di Torino Torino Italy AROL Closure Systems Torino Italy

The adaptability of devices can be significant for a customer that inserts them in an industrial production line. The ability to modify an object bought along with a machine that can be personalized with its features can change how they want to do measurements for different reasons, like predictive maintenance. Fog computing local centers already exist in the market, but they are usually on-the-shelf products with no margin of change for any user. However, with the usage of Docker and containers, this can change. This paper describes a fog computing local central called Concentrator, which can not only execute its essential functions built-in by the producer but also be customized by the user to add in the elaborations on other external sensors, expanding its capabilities and usage. We wanted to improve the device already tested on a Linux PC on a Raspberry Pi and try its performance and characteristics, seeing if it could be transformed into an embedded architecture and an industrial feature.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Coco-LIC: Continuous-Time Tightly-Coupled LiDAR-Inertial-Camera Odometry using Non-Uniform B-spline

arXiv

引用

arXiv 2023年

作者： Lang, Xiaolei Chen, Chao Tang, Kai Ma, Yukai Lv, Jiajun Liu, Yong Zuo, Xingxing The Institute of Cyber-Systems and Control Zhejiang University Hangzhou China The Department of Computer Engineering Technical University of Munich Germany

In this paper, we propose an efficient continuous-time LiDAR-Inertial-Camera Odometry, utilizing non-uniform B-splines to tightly couple measurements from the LiDAR, IMU, and camera. In contrast to uniform B-spline-based continuous-time methods, our non-uniform B-spline approach offers significant advantages in terms of achieving real-time efficiency and high accuracy. This is accomplished by dynamically and adaptively placing control points, taking into account the varying dynamics of the motion. To enable efficient fusion of heterogeneous LiDAR-Inertial-Camera data within a short sliding-window optimization, we assign depth to visual pixels using corresponding map points from a global LiDAR map, and formulate frame-to-map reprojection factors for the associated pixels in the current image frame. This way circumvents the necessity for depth optimization of visual pixels, which typically entails a lengthy sliding window with numerous control points for continuous-time trajectory estimation. We conduct dedicated experiments on real-world datasets to demonstrate the advantage and efficacy of adopting non-uniform continuous-time trajectory representation. Our LiDAR-Inertial-Camera odometry system is also extensively evaluated on both challenging scenarios with sensor degenerations and large-scale scenarios, and has shown comparable or higher accuracy than the state-of-the-art methods. The codebase of this paper will also be open-sourced at https://***/APRIL-ZJU/Coco-LIC. Copyright © 2023, The Authors. All rights reserved.

关键词： Pixels

来源：评论

学校读者我要写书评

暂无评论

Prediction of Radiated Electromagnetic Interference Based on Four-module Motor Drive System

Prediction of Radiated Electromagnetic Interference Based on...

引用

Energy, Power and Grid (ICEPG), International Conference on

作者： Yixin Shi Wenjie Chen Fengjiao Li Jinpeng Kan Yongqing Meng Guang Yang School of Electrical Engineering Xi’an Jiaotong University Xi’an China Department of Computer and Electronic Systems Engineering AVIC Xi’an Flight Automatic Control Research Institute Xi’an China

ISBN: (数字)9798350377798

ISBN: (纸本)9798350377804

In recent years, wide bandgap semiconductor devices such as silicon carbide (SiC) and gallium nitride (GaN) have been increasingly applied in electric drive systems, effectively enhancing system power density. However, the high-frequency and high-speed characteristics of SiC devices exacerbate electromagnetic interference (EMI) issues within the system. Additionally, the cables in electric drive systems exhibit significant antenna effects, radiating conducted EMI into the surrounding space, thereby affecting the normal operation of other sensitive equipment. Therefore, it is essential to research motor drive system topologies that can actively suppress EMI and predict radiated interference in motor drive systems. The topology of a four-module motor paired with parallel inverters can achieve active suppression of EMI at the source. This paper conducts a simulation-based prediction of radiated interference for a parallel inverter-driven four-module motor system. It analyzes the coupling mechanisms of common mode and differential mode radiated interference and validates the radiated interference from both DC and AC cables through simulations, predicting the impact on surrounding sensitive equipment in practical systems.

关键词： Motor drives Accuracy Silicon carbide Electromagnetic interference Layout Predictive models Motors Topology Gallium nitride Cables

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：