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research on Inverted Pendulum Control Based on Cascade Fuzzy Control and Neural Network Control 2

Research on Inverted Pendulum Control Based on Cascade Fuzzy...

引用

2nd IEEE international conference on Image Processing and computer Applications, ICIPCA 2024

作者： Wang, Shengkai School of Artificial Intelligence and Computer Science Jiangnan University Wuxi China

ISBN: (纸本)9798350360240

In this paper, the problem of precise control of single-stage inverted pendulum system is deeply discussed and practiced. The dynamic modeling and simulation of the inverted pendulum system were carried out in the course of the experiment, and the whole process of the inverted pendulum control was vividly reproduced by visual means, which enhanced the intuitiveness and effectiveness of the model design and control strategy analysis. In the design of control strategy, two advanced methods of neural network control and cascade fuzzy control are combined. The neural network controller uses its powerful nonlinear mapping ability and self-learning characteristics to approximate the complex dynamic behavior of the inverted pendulum system in real time and accurately. The cascade fuzzy controller realizes the hierarchical fine control of the Angle and angular velocity of the inverted pendulum through the upper and lower two-level control system, which improves the stability and robustness of the control system. After a series of rigorous experimental testing and optimization adjustment, the control output curve and the response curve of inverted pendulum state under different control methods are obtained successfully. Through the comparative analysis of these results, the advantages of the comprehensive scheme based on cascade fuzzy control and neural network control in improving the stable equilibrium time of inverted pendulum, reducing the overthrow amplitude and enhancing the anti-disturbance ability are revealed, and the effectiveness and superiority of the control strategy are verified, providing a new idea and reference for the theoretical research and practical application of inverted pendulum control. © 2024 IEEE.

关键词： Inverted pendulum

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3GPP Evaluation on UE with 8 Receiving Antennas in 5G NR Release 18 Standardization 9

3GPP Evaluation on UE with 8 Receiving Antennas in 5G NR Rel...

引用

9th international conference on computer and Communications, ICCC 2023

作者： Wu, Jingzhou Chang, Qiqing Yang, Shan She, Xiaoming Chen, Peng China Telecom Research Institute 6G Research Centre Beijing102209 China Beijing University of Posts and Telecommunications 100876 China

ISBN: (纸本)9798350317251

The evolution from 4G LTE to 5G NR has increased the requirement for downlink data rate and data transmission reliability. Massive MIMO, as an advanced antenna technique, has been extensively deployed in 5G systems. 8Rx UE performance has never been verified for its practical network structure and typical network parameter configurations. In this paper, an evaluation of the UR 8Rx performance verification for 5G NR in terms of system modeling, antenna correlation modeling, and key algorithms is provided based on the 3GPP Release 18 new work item. The evaluation covers multi-stream transmission, CQI selection, and link adaptation. Link-level simulation results show that compared with the traditional UEs with 2/4Rx, UEs with 8Rx can provide better performance with muti-stream transmission and link adaption. © 2023 IEEE.

关键词： Standardization

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The Concept of Application of computer Technologies for the educational and research Laboratory on Theoretical Fundamentals of Electrical Engineering 6

The Concept of Application of Computer Technologies for the ...

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6th international conference on Information Technologies in Engineering education, Inforino 2022

作者： Zhokhova, M.P. Mikheev, D.V. Karpunina, M.V. Zhokhov, D.Y. National Research University MPEI Department of Theoretical Fundamentals of Electrical Engineering Moscow Russia

ISBN: (纸本)9781665405775

The article discusses the experience and concept of using computer technologies for the educational and research laboratory on Theoretical Fundamentals of Electrical Engineering (TFEE). The methodology of using various simulation and circuit modeling environments for conducting an automated (computer) experiment is successfully used in the preparation of bachelor students of the Institute of Electric Power Engineering and the Institute of Electrical Engineering and Electrification at NRU MPEI for full-time, part-time and distance learning. Examples of the implementation of basic laboratory work and specialized work using the technologies of machine calculation of electrical circuits are given. © 2022 IEEE.

关键词： Electrical engineering Analytical models computer aided instruction Computational modeling Software Power systems Integrated circuit modeling

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Mathematical Model for Determining the Geometric Location of the Environmental Pollutant Based on Sensor Data 12

Mathematical Model for Determining the Geometric Location of...

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12th IEEE international conference on Intelligent Data Acquisition and advanced Computing Systems: Technology and Applications, IDAACS 2023

作者： Khaidurov, Vladyslav Yailymov, Bohdan Shelestov, Andrii National Technical University of Ukraine 'Igor Sikorsky Kyiv Polytechnic Institute' Kyiv03056 Ukraine Space Research Institute NASU-SSAU Kyiv03187 Ukraine

ISBN: (纸本)9798350358056

The practical result of this work is the development of a generalized mathematical model for determining the position of an environmental pollutant. computer simulation was carried out in order to verify the developed mathematical model. A number of computational experiments were conducted to verify the mathematical model. In the future, the developed algorithm is proposed to be used for real ground air quality measurement stations with additional use of air quality information from satellite data and specify the location of the pollution source using the Urban Atlas. © 2023 IEEE.

关键词： environmental pollutant genetic algorithm inverse problem mathematical modeling PM2.5 smart city Urban Atlas

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research on the Teaching Quality Evaluation of Neural Network Machine Learning Algorithm

Research on the Teaching Quality Evaluation of Neural Networ...

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2022 international conference on Mathematics, modeling, and computer Science, MMCS 2022

作者： Wu, Chuan School of Business Shandong Normal University Shandong China

ISBN: (纸本)9781510664593

Nowadays, there is no scientific and reasonable evaluation method for teachers teaching evaluation in higher education in China. According to the accumulated teaching experience, in order to ensure the fairness and perfection of teacher teaching evaluation, mathematical methods will be introduced into the evaluation work, such as analytic hierarchy process, grey decision method, fuzzy evaluation method, traditional statistical analysis evaluation model. Because teacher teaching evaluation is a nonlinear problem, the mathematical method has limitations in the application period, and both the selection index and the weight value are subjective. Therefore, on the basis of understanding the neural network algorithm, this paper constructs the teacher teaching evaluation system to think about problems from the perspective of different disciplines and specialties. The final experimental results show that using BP neural network for training and testing can further improve the rationality and objectivity of teachers teaching evaluation model. © 2023 SPIE.

关键词： Machine learning

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Optimizing Network Performance in 5G Systems with Downlink and Uplink Decoupling 6

Optimizing Network Performance in 5G Systems with Downlink a...

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6th international conference on advanced Communication Technologies and Networking, CommNet 2023

作者： Bouras, Christos Chatzigeorgiou, Charalampos Kokkinos, Vasileios Gkamas, Apostolos Pouyioutas, Philippos University of Patras Computer Engineering & Informatics Dept Greece University Ecclisiastical Academy of Vella Computer Science Dept Greece University of Nicosia Computer Science Dept Cyprus

ISBN: (纸本)9798350329391

This research paper presents a comprehensive investigation into the optimization of resource allocation in 5G networks through the technique of Downlink and Uplink Decoupling (DUDe). With the growing need for accurate modeling and scenario planning in 5G systems, DUDe allows for the configuration of an additional, lower frequency signal on the uplink to complement the existing uplink signal, rebalancing the uplink/downlink difference at the cell edge and enhancing coverage and network capacity. Drawing on extensive literature and industry trends, this study explores the benefits and challenges of DUDe, considering its impact on network performance, user experience, and future developments. The paper also introduces a simulation-based methodology and experiments to evaluate the effectiveness of DUDe in improving coverage, capacity, latency, and energy efficiency. The findings contribute to the understanding of DUDe's potential in optimizing 5G networks, providing valuable insights for researchers and network operators in designing and deploying efficient resource allocation strategies for enhanced network performance in various scenarios. © 2023 IEEE.

关键词： Network performance

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Prior Knowledge Enhanced Topic Model For research Topic Evolution Analysis 12

Prior Knowledge Enhanced Topic Model For Research Topic Evol...

引用

12th international conference on advanced Cloud and Big Data, CBD 2024

作者： Kang, Zhongyuan Zhang, Lu Chen, Zheng Zhu, Haiting He, Gaofeng Tang, Mingwei School of Computer Science Nanjing Audit University Nanjing China Ministry of Education China School of Internet of Things Nanjing University of Posts and Telecommunications Nanjing China School of Engineering Audit Nanjing Audit University Nanjing China

ISBN: (纸本)9798331511074

Extracting and analyzing topics from the scientific literature is crucial for identifying the research hotspots, under-standing the developmental trajectory, and further revealing and predicting the evolutionary trends of a research field. Existing topic models like LDA and ETM can effectively extract topics from large text corpora. However, they struggle with incor-porating the domain-specific prior knowledge that is inherent and can be easily obtained in the scientific literature (e.g., the keywords in the paper), causing weekly targeted but over generic topic extraction and representation. To address this problem, we propose a Prior Attention Topic Model (PATM), which leverages inherent keywords in the scientific literature as prior knowledge for more targeted topic extracting and representation. Specifically, we first construct a prior attention weight matrix to guide the document embedding to pay more attention on the keywords, and then, a multi-view Variational Autoencoder (VAE) is utilized to separately encode different literature types, combining their unique characteristics while sharing one latent space. At last, the topic-word probability martix learned from the VAE are regarded as the topic representations. The experimental results and case study demonstrate that the proposed PATM is effective in extracting topics in the scientific literature, including papers and patents, and by analyzing these topics, we clearly reveal the thematic evolution of the research about emerging information technologies empowering auditing. © 2024 IEEE.

关键词： Embedded Topic modeling Prior Knowledge Topic Models Variational Au-toencoder

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research on Vehicle Safety Models for Urban Roads 4

Research on Vehicle Safety Models for Urban Roads

引用

4th international conference on Electronic Information Engineering and computer Communication, EIECC 2024

作者： Zhuo, Yingying Zhang, Yongjie GuangXi Vocational Normal University Guangxi Xixiangtang District Luowen Avenue 17 Nanning China Education Department of Guangxi Zhuang Autonomous Region Guangxi China

ISBN: (纸本)9798331534622

In this paper, an efficient safety model is constructed for the safety of driverless vehicles on urban roads. By analyzing the current situation of traffic accidents, it points out that weather, geography, and human flow are uncontrollable risk sources. To this end, the model integrates vehicle-road cooperative sensing technology, fuses intelligent decision warning and collision time braking mechanism, and significantly improves road safety. Using Prescan simulation and Matlab cross-validation, the model monitors traffic flow, vehicle status, environmental conditions, and warns of potential risks in real time. Through advanced algorithmic analysis, it evaluates traffic management strategies such as signal light control and speed limit measures to optimize traffic flow and enhance safety. The model can automatically intervene at critical moments to create a safer environment for drivers and passengers, and is widely used in automotive and urban road traffic safety systems. © 2024 IEEE.

关键词： MATLAB

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LoRaWAN and Biosensor-Assisted Smart City Framework to Mitigate the Effects of Lung Diseases

LoRaWAN and Biosensor-Assisted Smart City Framework to Mitig...

引用

2024 IEEE international conference on modeling, simulation and Intelligent Computing, MoSICom 2024

作者： Abubeker, K.M. Roberts, Michaelraj Kingston Prajitha, C. Rinesh, S. Shafeena Karim, A. Jeevanandham, S. Department of Electronics and Communication Engineering Kerala India Sri Eshwar College of Engineering Centre for Advances in Signal Processing and Wireless Sensor Networks Department of Electronics and Communication Engineering Coimbatore India Karpagam Academy of Higher Education Centre for Interdisciplinary Research Department of Electronics and Communication Engineering Coimbatore India V.S.B College of Engineering Technical Campus Department of Computer Science and Engineering Coimbatore India Sri Ramakrishna Engineering College Department of Information Technology Coimbatore India

ISBN: (纸本)9798331533311

Urbanization and industrialization in cities present substantial obstacles to air quality, resulting in detrimental effects on public health, including respiratory health. This research introduces an Internet of Things (IoT) framework for a smart city environment using LoRaWAN and sensor networks. The framework utilizes the ESP32 LoRaWAN module to provide real-time monitoring of essential air quality metrics, such as carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, and humidity. Integrating biosensors enhances accuracy by identifying distinct biological indicators linked to respiratory well-being. The proposed work aims to use the framework in an urban setting within a global context, demonstrating its capacity to reduce the effects of lung disorders. The ESP32 LoRaWAN module enables effective communication within the sensor network up to 20 kilometers, guaranteeing a robust and adaptable solution for smart city applications. The developed framework provides a scalable and novel method for developing healthier and more sustainable cities, decreasing respiratory disorders as urban settings develop. © 2024 IEEE.

关键词： Lung cancer

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research on learner classroom behavior recognition based on YOLOv5 algorithm

Research on learner classroom behavior recognition based on ...

引用

2023 international conference on Information education and Artificial Intelligence, ICIEAI 2023

作者： Han, Kai Xu, Juan The School of Information Science Beijing Language and Culture University Beijing100083 China

ISBN: (纸本)9798400716157

YOLOv5 is a one-stage object detection algorithm based on deep learning that can quickly and accurately recognize images in real-time, making it of great research value in the field of computer vision. With the deepening of digital transformation in education, computer vision technology has gradually emerged in the education field. This article is based on the YOLOv5 algorithm for training and provides a reference for intelligent classroom behavior recognition, which is divided into the following modules. Firstly, frames are extracted from public teaching videos and demonstration classes to construct a suitable dataset. Secondly, the YOLOv5 algorithm is used for model training to recognize seven types of student classroom behaviors, including writing with head down, reading with head down, listening with head up, turning head, raising hand, standing, and group discussion. The research shows that the detection accuracy reaches 97.921%. Finally, it is proven that the YOLOv5 algorithm can effectively detect student classroom behaviors, which can assist teachers in judging student learning situations and making teaching decisions, providing support for the implementation of object detection technology. © 2023 ACM.

关键词： Students

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