检索结果-内蒙古大学图书馆

Multi-Head Attention Spatial-Temporal Graph Neural Networks for Traffic Forecasting

Journal of computer and Communications 2024年第3期12卷 52-67页

作者： Xiuwei Hu Enlong Yu Xiaoyu Zhao School of Computer Science and Technology Shandong University of Technology Zibo China Shandong Deyun Land Real Estate Appraisal Consulting Co. Zibo China College of Computer and Control Engineering Qiqihar University Qiqihar China

Accurate traffic prediction is crucial for an intelligent traffic system (ITS). However, the excessive non-linearity and complexity of the spatial-temporal correlation in traffic flow severely limit the prediction accuracy of most existing models, which simply stack temporal and spatial modules and fail to capture spatial-temporal features effectively. To improve the prediction accuracy, a multi-head attention spatial-temporal graph neural network (MSTNet) is proposed in this paper. First, the traffic data is decomposed into unique time spans that conform to positive rules, and valuable traffic node attributes are mined through an adaptive graph structure. Second, time and spatial features are captured using a multi-head attention spatial-temporal module. Finally, a multi-step prediction module is used to achieve future traffic condition prediction. Numerical experiments were conducted on an open-source dataset, and the results demonstrate that MSTNet performs well in spatial-temporal feature extraction and achieves more positive forecasting results than the baseline methods.

关键词： Traffic Prediction Intelligent Traffic System Multi-Head Attention Graph Neural Networks

来源：评论

学校读者我要写书评

暂无评论

Climate Downscaling Using Neural Operator: Spatiotemporal Multimodal Fusion Operator with State-Query Coupled Kernel

Climate Downscaling Using Neural Operator: Spatiotemporal Mu...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zhang, Haodi Wang, Yichi Jian, Yifan Jiang, Jiahui Bai, Zhaohai Ma, Lin College of Computer Science and Software Engineering Shenzhen University China Center for Agricultural Resources Research Institute of Genetic and Developmental Biology Chinese Academy of Sciences China State Key Laboratory of Pollution Control and Resource Reuse School of the Environment Nanjing University China

ISBN: (纸本)9798350368741

Climate downscaling is crucial for detailed small-scale analysis and for acquiring climate data in regions without weather stations. Operator learning has proven potential for this task. However, several challenges remain in operator learning, such as multimodal fusion, spatiotemporal fusion and input state and query adaptation. To address these challenges, we propose a Spatiotemporal Multimodal Fusion Operator with a State-Query Coupled Kernel (SMCK). This framework includes a latent space fusion encoder that encodes climate variables using position-wise multihead attention for multimodal fusion and integrates historical information to generate robust and precise representation. Additionally, we introduce a state-query coupled kernel that combines radial basis functions and discrete fourier encoding to enhance query location representation, while also adapting to the state to obtain the coupled kernel. Extensive experiments demonstrate that our method achieves state-ofthe-art performance and provides strong support for climate downscaling and the planning of climate-related strategies. © 2025 IEEE.

关键词： Climate downscaling Deep Learning Multimodal fusion Operator learning Time series forecasting

来源：评论

学校读者我要写书评

暂无评论

Optimized Fractional-Order PID controller for Temperature control of CSTH: A Comparative Study with PID Cascade controller

Optimized Fractional-Order PID Controller for Temperature Co...

引用

2025 International Conference on Energy, Power, Environment, control and Computing, ICEPECC 2025

作者： Alaswadi, Abdulaziz F. Alyazidi, Nezar M. AL-Aswadi, Fatima N. Ahmed, Amjed Abbas Department of Control and Instrumentation Engineering King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Interdisciplinary Center of Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Institute of Computer Science & Digital Innovation (ICSDI) UCSI University Kuala Lumpur 56000 Malaysia Faculty of Computer Science and Engineering Hodeidah University Al Hudaydah Yemen Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia Department of Computer Techniques Engineering Imam AlKadhum College (IKC) Baghdad Iraq

ISBN: (纸本)9781837243235

controlling the temperature in chemical reactors, heating furnaces, distillation columns, and reboilers for circulating heating fluids is crucial across all industries. This project is a simulation-based study where both PID-cascade and fractional order PID (FO-PID) controllers were used to control the temperature of water in the continuously stirred tank heater system. The simulation was designed by using SIMULINK. Initially, the work reproduces results from a previous study that evaluated the performance of PID cascade controller applied for controlling the temperature of continuous stirred tank heater. Building on this foundation, a novel fractional-order PID (FO-PID) controller was designed and its parameters were optimized using the Whale Optimizer Algorithm (WOA). Results showed that the FO-PID outperforms the PID-cascade controller in terms of settling time and percentage overshoot. This study demonstrates significant advancements in process innovation and optimization, supporting sustainable industrial systems. The FO-PID controller in comparison to the Cascade PID controller reduced the percentage overshoot by approximately 97%, reduced settling time by 87% and maintained comparable steady-state error. © The Institution of engineering & Technology 2025.

关键词： FO-PID Mathematical Modeling PID-cascade Whale Optimizer Algorithm

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Tracking control Approach for a Quadrotor Transporting a Cable-Suspended Payload

An Adaptive Tracking Control Approach for a Quadrotor Transp...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Jianzhe Fu Yanmei Jia Zongyang Lv Yuhu Wu School of Control Science and Engineering Dalian University of Technology Dalian China School of Science Dalian Minzu University Dalian China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This study presents an adaptive control system for controlling the motion of a quadrotor transporting a cable-suspended payload. The technique uses adaptive updating rules to estimate the unknown disturbance operating on the pay-load. This work employs the Lyapunov method and LaSalle’s invariance theorem to examine and demonstrate that the suggested algorithm ensures the control system’s asymptotic stability. The simulation at the end of the paper validates the performance of the constructed adaptive controller.

关键词： Asymptotic stability Estimation error Automation Stability analysis Closed loop systems Adaptive control Payloads

来源：评论

学校读者我要写书评

暂无评论

A Distributed Automatic Domain-Specific Multi-Word Term Recognition Architecture using Spark Ecosystem

A Distributed Automatic Domain-Specific Multi-Word Term Reco...

引用

International Symposium on Parallel and Distributed Computing

作者： Ciprian-Octavian Truică Neculai-Ovidiu Istrate Elena-Simona Apostol Computer Science and Engineering Department Faculty of Automatic Control and Computers University Politehnica of Bucharest Bucharest Romania

Automatic Term Recognition is used to extract domain-specific terms that belong to a given domain. In order to be accurate, these corpus and language-dependent methods require large volumes of textual data that need to be processed to extract candidate terms that are afterward scored according to a given metric. To improve text preprocessing and candidate terms extraction and scoring, we propose a distributed Spark-based architecture to automatically extract domain-specific terms. The main contributions are as follows: (1) propose a novel distributed automatic domain-specific multi-word term recognition architecture built on top of the Spark ecosystem; (2) perform an in-depth analysis of our architecture in terms of accuracy and scalability; (3) design an easy-to-integrate Python implementation that enables the use of Big Data processing in fields such as Computational Linguistics and Natural Language Processing. We prove empirically the feasibility of our architecture by performing experiments on two real-world datasets.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Traditional Chinese Medicine Health Status Identification with Graph Attention Network 1

引用

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Fu, Amin Ma, Jishun Wang, Chuansheng Zhou, Changen Li, Zuoyong Teng, Shenghua College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao266590 China Department of Automatic Control Technical Polytechnic University of Catalonia Barcelona08034 Spain Research Base of Traditional Chinese Medicine Syndrome Fujian University of Traditional Chinese Medicine Fuzhou350122 China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou350121 China

ISBN: (数字)9783031200960

ISBN: (纸本)9783031200953

The Traditional Chinese Medicine Health Status Identification plays an important role in TCM diagnosis and prescription recommendation. In this paper, we propose a method of Status Identification via Graph Attention Network, named SIGAT, which captures the complex medical correlation in the symptom-syndrome graph. More specifically, we construct a symptom-syndrome graph in that symptoms are taken as nodes and the edges are connected by syndromes. And we realize automatic induction of symptom to state element classification by using the attention mechanism and perceptron classifier. Finally, we conduct experiments by using hamming loss, coverage, 0/1 error, ranking loss, average precision, macro-F1 score, and micro-F1 score as evaluation metrics. The results demonstrate that the SIGAT model outperforms comparison algorithms on Traditional Chinese Medicine Prescription Dictionary dataset. The case study results suggest that the proposed method is a valuable way to identify the state element. The application of the graph attention network classification algorithm in TCM health status identification is of high precision and methodological feasibility. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

Equilibrium-Independent control of Continuous-Time Nonlinear Systems via the LPV Framework - Extended Version

arXiv

引用

arXiv 2023年

作者： Koelewijn, Patrick J.W. Weiland, Siep Tóth, Roland The Control Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven Netherlands The Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

In this paper, we consider the analysis and control of continuous-time nonlinear systems to ensure universal shifted stability and performance, i.e., stability and performance w.r.t. each forced equilibrium point of the system. This "equilibrium-free" concept is especially beneficial for control problems that require the tracking of setpoints and rejection of persistent disturbances, such as input loads. In this paper, we show how the velocity form, i.e., the time-differentiated dynamics of the system, plays a crucial role in characterizing these properties and how the analysis of it can be solved by the application of Linear Parameter-Varying (LPV) methods in a computationally efficient manner. Furthermore, by leveraging the properties of the velocity form and the LPV framework, a novel controller synthesis method is presented which ensures closed-loop universal shifted stability and performance. The proposed controller design is verified in a simulation study and also experimentally on a real system. Additionally, we compare the proposed method to a standard LPV control design, demonstrating the improved stability and performance guarantees of the new approach. Copyright © 2023, The Authors. All rights reserved.

关键词： controllers

来源：评论

学校读者我要写书评

暂无评论

Coarse-to-Fine Detection of Multiple Seams for Robotic Welding

arXiv

引用

arXiv 2024年

作者： Wei, Pengkun Cheng, Shuo Li, Dayou Song, Ran Zhang, Yipeng Zhang, Wei School of Control Science and Engineering Shandong University Jinan250061 China Department of Electrical and Computer Engineering University of California Los AngelesCA United States

Efficiently detecting target weld seams while ensuring sub-millimeter accuracy has always been an important challenge in autonomous welding, which has significant application in industrial practice. Previous works mostly focused on recognizing and localizing welding seams one by one, leading to inferior efficiency in modeling the workpiece. This paper proposes a novel framework capable of multiple weld seams extraction using both RGB images and 3D point clouds. The RGB image is used to obtain the region of interest by approximately localizing the weld seams, and the point cloud is used to achieve the fine-edge extraction of the weld seams within the region of interest using region growth. Our method is further accelerated by using a pre-trained deep learning model to ensure both efficiency and generalization ability. The performance of the proposed method has been comprehensively tested on various workpieces featuring both linear and curved weld seams and in physical experiment systems. The results showcase considerable potential for real-world industrial applications, emphasizing the method’s efficiency and effectiveness. Videos of the real-world experiments can be found at https://***/pq162HSP2D4. © 2024, CC BY.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Towards More Efficient EfficientDets and Real-Time Marine Debris Detection

引用

IEEE Robotics and Automation Letters 2023年第4期8卷 2134-2141页

作者： Zocco, Federico Lin, Tzu-Chieh Huang, Ching-I Wang, Hsueh-Cheng Khyam, Mohammad Omar Van, Mien Queen's University Belfast Centre for Intelligent Autonomous Manufacturing Systems School of Electronics Electrical Engineering and Computer Science Northern IrelandBT7 1NN United Kingdom Hsinchu City30010 Taiwan Institute of Electrical and Control Engineering Hsinchu City30010 Taiwan Labs Hsinchu Taiwan Central Queensland University School of Engineering and Technology Norman Gardens QLD4701 Australia

Marine debris is a problem both for the health of marine environments and for the human health since tiny pieces of plastic called 'microplastics' resulting from the debris decomposition over the time are entering the food chain at any levels. For marine debris detection and removal, autonomous underwater vehicles (AUVs) are a potential solution. In this letter, we focus on the efficiency of AUV vision for real-time marine debris detection. First, we improved the efficiency of a class of state-of-the-art object detectors, namely EfficientDets [1], by 1.5% AP on D0, 2.6% AP on D1, 1.2% AP on D2 and 1.3% AP on D3 without increasing the GPU latency (see Fig. 1). Subsequently, we created and made publicly available a dataset for the detection of in-water plastic bags and bottles and trained our improved EfficientDets on this and on two public datasets for marine debris detection. Finally, we began the testing of real-time detection performance on a simulator of marine environments. © 2016 IEEE.

关键词： Real time systems

来源：评论

学校读者我要写书评

暂无评论

Synchronization of Probabilistic Boolean Networks under State-Flipped control

Synchronization of Probabilistic Boolean Networks under Stat...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Chenyang Bian Leihao Du Zhipeng Zhang School of Control Science and Engineering Tiangong University Tianjin China School of Computer Science and Engineering Tianjin University of Technology Tianjin China School of Artificial Intelligence Tiangong University Tianjin China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This paper investigates the synchronization problem of probabilistic boolean networks (PBNs) under state-flipped control. First, by flipping some of the nodes, the entire state space is transferred to a synchronous state set. Some verification conditions for the synchronization of PBNs are proposed. Second, a Q-Learning (QL) algorithm for synchronizing PBNs in finite flip control is given, and the minimum flip set is obtained. Finally, numerical simulations are performed to verify the feasibility of the conclusions.

关键词： Q-learning Automation Aerospace electronics Probabilistic logic Numerical simulation Synchronization

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：