检索结果-内蒙古大学图书馆

Adaptive control Scheme for Clustering of Nodes Based on the Signs of Connections in Dynamical Signed Networks 19th

Adaptive Control Scheme for Clustering of Nodes Based on ...

19th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness, QShine 2023

作者： Wang, Qi Wang, Yinhe Gao, Zilin Gao, Peitao Xiong, Jianbin Cen, Jian Gao, Ying School of Automation Guangdong Polytechnic Normal University Guangzhou510665 China School of Automation Guangdong University of Technology Guangzhou510006 China College of Computer Science and Engineering Chongqing Three Gorges University Chongqing404020 China School of Electronics and Information Guangdong Polytechnic Normal University Guangzhou510665 China Guangzhou Intelligent Building Equipment Information Integration and Control Key Laboratory Guangzhou510665 China School of Computer Science and Engineering South China University of Technology Guagnzhou510641 China

ISBN: (纸本)9783031651229

The concept of clustering has garnered significant attention within the field of complex networks. Numerous clustering algorithms have been documented in the extant academic literature. However, most of them consider static signed networks, which are not suitable for dynamical networks. For dynamical signed networks, there is a class of algorithms called cluster dynamics. Nevertheless, they regard the connection to be time-invariant, which is a constraint. In this paper, for a kind of dynamical signed networks with time-varying connections, we discuss the adaptive control scheme for clustering of nodes, such that the network evolves asymptotically into a classifiable network that contains several friends’ groups with clear sign boundaries. In other words, through the careful design of the controller for the nodes and the establishment of coupling relationships between the nodes and their connections, we ensure that the connection of the dynamical signed network can approximate asymptotically the connection of a given classifiable network, as measured by the concept of uniformly ultimately bounded (UUB). Finally, the simulation is used to illustrate the validity of the method proposed in this paper. © ICST Institute for computer sciences, Social Informatics and Telecommunications engineering 2024.

关键词： Adaptive control Classifiable networks Multi-clustering

来源：评论

学校读者我要写书评

暂无评论

Allocation and Scheduling of the Colorado River System

Allocation and Scheduling of the Colorado River System

引用

作者： Ziyang Zhang Kaisheng Wang Ruifeng Zeng College of Computer Science and Software Engineering Shenzhen University College of Mechatronics and Control Engineering Shenzhen University

Generally,dams serve as reservoirs for water *** Colorado River Basin is currently in a state of continuous drought,and if the five states of AZ,CA,WY,NM and CO maintain the agreements made hundreds of years ago,there will not be enough water to supply in the near *** propose a multi-objective programming algorithm under inequality constraints,under the condition that the sum of the competition coefficients is minimized,we solve the proportion of water resources that should be cut for general water usage and hydropower production at different water scarcity *** develop some policies to deal with water *** use the univariate analysis method to rationally analyze and reconstruct our model according to three different scenarios,and finally predict different situations,like additional water supply is needed or whether there will be more water flowing to the Gulf of California.

关键词： Differential equations kinetic equations entropy method competition coefficients multiobjective programming algorithms univariate analysis

来源：评论

学校读者我要写书评

暂无评论

Design of Diesel Oxidation Catalyst Temperature control System Based on Fuzzy Adaptive PID

Design of Diesel Oxidation Catalyst Temperature Control Syst...

引用

2021 International Conference on Robotics Automation and Intelligent control, ICRAIC 2021

作者： Wang, Ning Sun, Yao Hu, Yunfeng Zhao, Jinghua Gong, Xun State Key Laboratory of Automotive Simulation and Control Jilin Changchun China College of Artificial Intelligence Jilin University Jilin Changchun China Department of Control Science and Engineering Jilin University Jilin Changchun China College of Computer Jilin Normal University Jilin Siping China

This paper presents a temperature control framework of Diesel Oxidation Catalyst (DOC) of after-treatment system (ATS) which aims to increase the control precise of DOC temperature under different exhaust flow rates. To start with, a control-oriented DOC temperature model is established. Considering the sensitivity of DOC to different exhaust flow rate, a fuzzy adaptive PID temperature control system framework under the Smith predictor is designed. Finally, the controller is verified in the Matlab/Simulink. The results show that when tracking the desired temperature, the overshoot is reduced and the response speed is faster at different exhaust flow rates compared with the traditional PID control system. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Temperature control

来源：评论

学校读者我要写书评

暂无评论

SensoryT5: Infusing Sensorimotor Norms into T5 for Enhanced Fine-grained Emotion Classification

arXiv

引用

arXiv 2024年

作者： Xia, Yuhan Zhao, Qingqing Long, Yunfei Xu, Ge Wang, Jia School of Computer Science and Electronic Engineering University of Essex United Kingdom Institute of Linguistics Chinese Academy of Social Sciences China College of Computer and Control Engineering Minjiang University China Department of Intelligent Science Xi’an Jiaotong-Liverpool University China

In traditional research approaches, sensory perception and emotion classification have traditionally been considered separate domains. Yet, the significant influence of sensory experiences on emotional responses is undeniable. The natural language processing (NLP) community has often missed the opportunity to merge sensory knowledge with emotion classification. To address this gap, we propose SensoryT5, a neuro-cognitive approach that integrates sensory information into the T5 (Text-to-Text Transfer Transformer) model, designed specifically for fine-grained emotion classification. This methodology incorporates sensory cues into the T5’s attention mechanism, enabling a harmonious balance between contextual understanding and sensory awareness. The resulting model amplifies the richness of emotional representations. In rigorous tests across various detailed emotion classification datasets, SensoryT5 showcases improved performance, surpassing both the foundational T5 model and current state-of-the-art works. Notably, SensoryT5’s success signifies a pivotal change in the NLP domain, highlighting the potential influence of neuro-cognitive data in refining machine learning models’ emotional sensitivity. © 2024, CC BY-SA.

关键词： Classification (of information)

来源：评论

学校读者我要写书评

暂无评论

An Integrated Online-Offline Hybrid Particle Swarm Optimization Framework for Medium Scale Expensive Problems*

An Integrated Online-Offline Hybrid Particle Swarm Optimizat...

引用

Data-driven Optimization of Complex Systems (DOCS), International Conference on

作者： Hanyu Hu Jian Wang Xiaodong Huang Sergey V. Ablameyko College of Computer Science and Technology China University of Petroleum (East China) Qingdao China College of science) China University of Petroleum (East China) Qingdao China College of Control Science and Engineering China University of Petroleum (East China) Qingdao China Faculty of Applied Mathematics and Computer Science Belarusian State University Minsk Belarus

ISBN: (数字)9798350377842

ISBN: (纸本)9798350377859

Real-world optimization problems often involve computationally expensive evaluations, making efficient optimization crucial. To address medium-scale expensive optimization problems, this paper proposes and investigates an Integrated Online-Offline Hybrid Particle Swarm Optimization Framework (IOOPSOF). The framework integrates concepts from active learning and ensemble learning, iteratively querying the most uncertain and highest-precision solutions to achieve efficient utilization of evaluation resources. IOOPSOF employs two distinct sample selection criteria, with offline optimization for exploration and online optimization for exploitation. The effectiveness of the proposed method is validated through experiments on a series of low to medium-dimensional benchmark functions and the operational parameter optimization of Enhanced Geothermal Systems (EGS). Results demonstrate that IOOPSOF significantly outperforms existing methods, achieving global optimum (0) on most benchmark functions and showing superior performance over single surrogate-assisted evolutionary algorithms (SAEAs) on real-world problems, thereby showcasing its exceptional potential for solving expensive optimization problems.

关键词： Decision making Benchmark testing Computational efficiency Ensemble learning Particle swarm optimization Complex systems Optimization Standards

来源：评论

学校读者我要写书评

暂无评论

Multi-hop Routing Optimization of Transmission-Line Monitoring Based on the LoRa Technology 10

Multi-hop Routing Optimization of Transmission-Line Monitori...

引用

10th IEEE International Conference on Smart City and Informatization, iSCI 2022

作者： Zhao, Yimei Song, Junjie Che, Xin Anshun Power Supply Bureau China Southern Power Grid Anshun China College of Computer Science and Technology Guizhou University State Key Laboratory of Public Big Data Guiyang China College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9798350396317

As the power transmission network connects the power generation side and power consumption side, the transmission line plays a vital role in the overall stable operation of the power grid. However, because power transmission lines are often distributed in a very harsh environment, they are extremely susceptible to being interfered with by dynamic scenarios and face transmission failures. Therefore, to maintain the power transmission, it is urgent to monitor the status of transmission lines in real time. Traditional communication technologies, such as GPRS, optical fiber, ZigBee, etc. are widely used in power monitoring systems, but their limitations make it difficult to meet the remote monitoring of transmission lines. The long-range (LoRa) technology has the characteristics of wide coverage and low energy consumption, providing an opportunity to make up for the 'last-mile' gap in transmission-line monitoring. The challenges to monitoring the transmission lines are: 1) the nodes far away from the base station need to transmit the data with considerable transmission power;2) the nodes outside the communication range of the base station cannot successfully send the data to the base station. To address these problems, this paper proposed a multi-hop communication strategy to monitor the status of transmission lines. First, we use a graph to represent the LoRa nodes and transfer the 3-phase line monitoring structure to the 1-phase line monitoring. Second, we construct an energy consumption model for each LoRa node in the multi-hop scenario. Third, we develop a max-min optimization problem to compute a multi-hop scheme for minimizing the overall energy consumption for the transmission-line monitoring and maximizing the transmission range for the base station. Finally, we conduct extensive simulations to analyze the bottleneck of the energy consumption of the overall monitoring system with LoRa and the maximum range that the base station can cover. © 2022 IEEE.

关键词： Electric lines

来源：评论

学校读者我要写书评

暂无评论

Tactile-Based Object Pose Estimation Employing Extended Kalman Filter 8

Tactile-Based Object Pose Estimation Employing Extended Kalm...

引用

8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Lin, Qiguang Yan, Chaojie Li, Qiang Ling, Yonggen Zheng, Yu Lee, Wangwei Wan, Zhaoliang Huang, Bidan Liu, Xiaofeng College of IoT Engineering Hohai University Jiangsu Key Laboratory of Special Robotic Technology Jiangsu Changzhou213022 China Zhejiang University Institute of Cyber-System and Control State Key Laboratory of Industrial Control and Technology Hangzhou China Bielefeld33619 Germany Tencent Robotics X Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China

ISBN: (纸本)9798350300178

In this paper, we present a new approach to estimate the pose of an object being manipulated by a multi-fingered robotic hand. The method utilizes advanced tactile sensors with high spatial resolution to optimize the estimation of the object's pose using an Extended Kalman Filter (EKF) based approach. We defined and derived the state and measurement equations, as well as evaluated the estimation accuracy in grasping tasks. The approach is able to effectively account for the pose transition caused by tactile pushing, and the mapping from the object's pose to the contact position and normal direction as measured by the tactile sensor. The method was evaluated in multiple grasping experiments in simulation scenarios. Results show that the estimation can converge towards the ground truth in a relatively short period of time, with displacement and rotation errors remaining within acceptable levels. This new method has the potential to improve the accuracy and reliability of robotic grasping and manipulation tasks. © 2023 IEEE.

关键词： Extended Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Design and Implementation of Linear Taper Slot Antenna for Multiband Applications 3

Design and Implementation of Linear Taper Slot Antenna for M...

引用

3rd International Conference on Power, Energy, control and Transmission Systems, ICPECTS 2022

作者： Revathi, M. Ruban Thomas, D. Mohamed Abbas, A. Mohanraj, K. Tharani Chitra, U. Balaji, N. Dr. Sakunthala Engineering College Vel Tech Multi Tech Dr. Rangarajan Department of ECE Chennai India Dr. Sakunthala Engineering College Vel Tech Multi Tech Dr. Rangarajan Department of ECE India Sri Sairam Engineering College Instrumentation and Control Engineering Chennai India Sri Sairam Engineering College Computer Science Engineering Chennai India

ISBN: (纸本)9781665462754

Small, high-gain antennas have been in demand due to the proliferation of wireless technology over the past decade. For some uses, a high gain is preferable, while for others, a high return loss is required. Using multiband frequencies, a single Microstrip patch antenna can support all of these uses. For optimal performance and low return loss, a Linear Tapered Slot Antenna constructed from FR4 and fed by coaxial cable is required for this endeavor. At MmW frequencies, increasing channel capacity and decreasing inter-user interference calls for a directional antenna with a high gain. The proposed antenna is 38mm ∗ 50mm in size and has a return loss of -16.03dB at 8.77GHz, 10.86dB at 9.55GHz, 7.68dB at 11.3GHz, -24.93dB at 14.32GHz, and -20.98dB at 16.13GHz. The proposed antenna was developed and tested with HFSS software, and it operates effectively in the C-band, X-band, and Ku-band for wireless communication. The outcome demonstrates the high degree of concordance between simulation and measurement. © 2022 IEEE.

关键词： Microwave antennas

来源：评论

学校读者我要写书评

暂无评论

Robustness challenges in Reinforcement Learning based time-critical cloud resource scheduling: A Meta-Learning based solution

Robustness challenges in Reinforcement Learning based time-c...

引用

作者： Liu, Hongyun Chen, Peng Ouyang, Xue Gao, Hui Yan, Bing Grosso, Paola Zhao, Zhiming Informatics Institute University of Amsterdam Amsterdam1098 XH Netherlands Graduate School of Informatics University of Amsterdam Amsterdam1098 XH Netherlands School of Computer and Software Engineering Xihua University Chengdu610039 China School of Computer Science National University of Defense Technology Changsha410073 China College of Electrical and Control Engineering Shaanxi University of Science and Technology Xi'an710021 China School of Electrical and Electronic Engineering University of Adelaide Adelaide South Australia5005 Australia

Cloud computing attracts increasing attention in processing dynamic computing tasks and automating the software development and operation pipeline. In many cases, the computing tasks have strict deadlines. The cloud resource manager (e.g., orchestrator) effectively manages the resources and provides tasks Quality of Service (QoS). Cloud task scheduling is tricky due to the dynamic nature of task workload and resource availability. Reinforcement Learning (RL) has attracted lots of research attention in scheduling. However, those RL-based approaches suffer from low scheduling performance robustness when the task workload and resource availability change, particularly when handling time-critical tasks. This paper focuses on both challenges of robustness and deadline guarantee among such RL, specifically Deep RL (DRL)-based scheduling approaches. We quantify the robustness measurements as the retraining time and investigate how to improve both robustness and deadline guarantee of DRL-based scheduling. We propose MLR-TC-DRLS, a practical, robust Meta Deep Reinforcement Learning-based scheduling solution to provide time-critical tasks deadline guarantee and fast adaptation under highly dynamic situations. We comprehensively evaluate MLR-TC-DRLS performance against RL-based and RL advanced variants-based scheduling approaches using real-world and synthetic data. The evaluations validate that our proposed approach improves the scheduling performance robustness of typical DRL variants scheduling approaches with 97%–98.5% deadline guarantees and 200%–500% faster adaptation. © 2023 The Author(s)

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Traffic Pattern Classification in Smart Cities Using Deep Recurrent Neural Network

arXiv

引用

arXiv 2024年

作者： Ismaeel, Ayad Ghany Krishnadas, J. Manishankar, S. Natarajan, Yuvaraj Mahmood, Sarmad Nozad Alani, Sameer Shather, Akram H. Computer Technology Engineering College of Engineering Technology Al-Kitab University Kirkuk36001 Iraq Department of Computer Science and Engineering Sahrdaya College of Engineering and Technology Thrissur Kodakara680684 India Department of Computer Science and Engineering Sri Shakthi Institute of Engineering and Technology Coimbatore641062 India Electronic and Control Engineering Techniques Technical Engineering College Northern Technical University Kirkuk36001 Iraq Computer Center University of Anbar Ramadi55431 Iraq Department of Computer Engineering Technology Al-Kitab University Altun Kopru Kirkuk36001 Iraq

This paper examines the use of deep recurrent neural networks to classify traffic patterns in smart cities. We propose a novel approach to traffic pattern classification based on deep recurrent neural networks, which can effectively capture traffic patterns' dynamic and sequential features. The proposed model combines convolutional and recurrent layers to extract features from traffic pattern data and a SoftMax layer to classify traffic patterns. Experimental results show that the proposed model outperforms existing methods regarding accuracy, precision, recall, and F1 score. Furthermore, we provide an in-depth analysis of the results and discuss the implications of the proposed model for smart cities. The results show that the proposed model can accurately classify traffic patterns in smart cities with a precision of as high as 95%. The proposed model is evaluated on a real-world traffic pattern dataset and compared with existing classification methods. © 2024, CC BY-NC-ND.

关键词： Classification (of information)

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：