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2024 ieee/IFIP Network Operations and Management symposium, NOMS 2024

ISBN: (纸本)9798350327939

The proceedings contain 221 papers. The topics discussed include: improving resilience of future mobile network generations implementing zero trust paradigm;enabling big data and machine learning applications in high-stakes environments;learn to compress (LtC): efficient learning-based streaming video analytics;machine learning-based estimation of the number of competing flows at a bottleneck link;an artificial intelligence framework for dynamic selection and resource allocation for EVs in vehicular networks;ChatGPT-enabled network automation using API-based prompts;data-centric federated learning for anomaly detection in smart grids and other industrial control systems;unconsidered installations: discovering IoT deployments in the IPv6 Internet;and RPL at scale: experiences from a performance evaluation on up to 700 ieee 802.15.4 devices.

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MPPT Research for Switched Reluctance Wind Turbine based on Variable Universe Fuzzy control 8

MPPT Research for Switched Reluctance Wind Turbine based on ...

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8th International symposium on Computer Science and Intelligent control, ISCSIC 2024

作者： Chen, Hongguang Wang, Honghua HoHai University College of Artificial Intelligence and Automation Jiangsu Key Laboratory of Power Transmission and Distribution Equipment Technology Changzhou China

ISBN: (纸本)9798350380286

Taking the three-phase 6/4 switched reluctance wind turbine as an example, for the uncertainty of wind energy in the wind power generation system, it is difficult to achieve the maximum power point tracking quickly and effectively. This paper adopts the variable universe idea to optimize the traditional fuzzy controller, and adopts the current chopper control for the switched reluctance generator to regulate the speed. The simulation results show that the designed variable universe fuzzy controller has better tracking effect than the traditional fuzzy controller and can effectively reduce the system steady state error, so that the switched reluctance wind power generation system can more accurately achieve the maximum power point tracking. © 2024 ieee.

关键词： Windmill

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Comparison of optimization algorithms for installation error calibration of accelerometer arrays 23

Comparison of optimization algorithms for installation error...

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23rd ieee International symposium on computational intelligence and Informatics, CINTI 2023

作者： Pesti, Richard Sarcevic, Peter Csik, Dominik Nagy, Istvan Odry, Akos Óbuda University Doctoral School of Applied Informatics and Applied Mathematics Budapest Hungary University of Szeged Department of Mechatronics and Automation Szeged Hungary Óbuda University Bánki Donát Faculty of Mechanical and Safety Engineering Budapest Hungary

ISBN: (纸本)9798350342949

Accelerometers play a crucial role in localization problems, but their accuracy depends on the precision of the calibration process. In this paper, a comparison of optimization algorithms is presented within the scope of between sensor error calibration. The Particle Swarm optimization (PSO) and Genetic Algorithm (GA) are proposed for the problem, and tested in three different setups. Moreover, the MATLAB built-in fmincon minimization algorithm is also evaluated for calibration parameter estimation. A custom fitness function is proposed to obtain the between sensor misalignment and bias errors, for two accelerometers. The analysis highlights that the algorithms can successfully determine the between sensor error parameters. The conducted comparison shows that fmincon reached an outstanding speed in terms of convergency, but in overall PSO has produced better results compared to GA and fmincon. PSO is more suitable for the calibration problem because of its robustness and stability characteristics. © 2023 ieee.

关键词： Calibration

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Exploring EMG Signals for Prosthetic control and Gesture Recognition: Advancements, Applications, and Future Directions

Exploring EMG Signals for Prosthetic Control and Gesture Rec...

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2024 International Conference on computational intelligence and Computing Applications, ICCICA 2024

作者： Tushir, Sweety Verma, Neetu Kumar, Krishan Dcrust Department Of Computer Science And Engineering Sonepat Murthal India Jcbust Department Of Mechanical Engineering Faridabad India

ISBN: (纸本)9798350306446

EMG signals and machine learning enable the automation of gesture recognition for addressing challenges faced by amputees in daily life. This review analyses diverse approaches within EMG-based gesture recognition and hand prosthesis control. Shifting muscular intention into natural control offers numerous applications which include helping amputees regain their functioning to completely changing the way we interact with digital surroundings. It highlights advancements in this dynamic field, emphasizing its applications in human-computer interaction, prosthetics and assistive communication. The review focuses on techniques that improve accuracy and robustness which are essential for wider accessibility. Additionally, it explores the potential impact on industries beyond healthcare such as AR/VR, prosthetic hand control, human-machine interaction and sign language recognition. The performance of hybrid approaches and convolutional neural networks (CNNs) in gesture recognition tests demonstrates a high degree of accuracy. Overall, EMG-based gesture recognition offers significant promise in driving innovations that enhance quality of life and promote inclusivity. This exploration delves into the recent strides, diverse applications, and future directions of EMG-based prosthetic control and gesture recognition, offering insights into the groundbreaking research shaping this domain. © 2024 ieee.

关键词： Machine learning

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Analyzing the Stock Volatility Spillovers in Chinese Financial and Economic Sectors

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ieee TRANSACTIONS ON computational SOCIAL SYSTEMS 2023年第1期10卷 269-284页

作者： Li, Jingyu Cheng, Lu Zheng, Xiaolong Wang, Fei-Yue Beijing Univ Technol Sch Econ & Management Beijing 100124 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100190 Peoples R China

By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.-China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literature. By considering that the stock volatility spillover may vary over distinct timescales, the spillovers are disclosed through innovatively constructing the multi-scale spillover networks, followed by connectedness computation, based on variational mode decomposition (VMD) and generalized vector autoregression (GVAR) process. Our empirical analysis first demonstrates the different levels of increases in the total sectoral volatility spillover and changes in the roles of the sectors in the system under the aforementioned crises. Besides, the increases in the sectoral spillover in the long-term are verified to negatively impact the macroeconomy and can thereby act as warning signals.

关键词： COVID-19 financial and economic system network analysis stock volatility spillover variational mode decomposition (VMD)

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Applicability Study of Model-Free Reinforcement Learning Towards an Automated Design Space Exploration Framework

Applicability Study of Model-Free Reinforcement Learning Tow...

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2023 ieee symposium Series on computational intelligence, SSCI 2023

作者： Hoffmann, Patrick Gorelik, Kirill Ivanov, Valentin Corporate Research & Advance Eng. Robert Bosch GmbH Renningen Germany Technische Universitiat Ilmenau Department of Mechanical Engineering Ilmenau Germany

ISBN: (纸本)9781665430654

Design space exploration is a crucial aspect of engineering and optimization, focused on identifying optimal design configurations for complex systems with a high degree of freedom in the actor set. It involves systematic exploration while considering various constraints and requirements. One of the key challenges in design space exploration is the need for a control strategy tailored to the particular design. In this context, reinforcement learning has emerged as a promising solution approach for automatically inferring control strategies, thereby enabling efficient comparison of different designs. However, learning the optimal policy is computationally intensive, as the agent determines the optimal policy through trial and error. The focus of this study is on learning a single strategy for a given design and scenario, enabling the evaluation of numerous architectures within a limited time frame. The study also highlights the importance of plant modeling considering different modeling approaches to effectively capture the system complexity on the example of vehicle dynamics. In addition, a careful selection of an appropriate hyperparameter set for the reinforcement learning algorithm is emphasized to improve the overall performance and optimization process. © 2023 ieee.

关键词： Electric Vehicle Intelligent control Reinforcement Learning Transportation and Vehicle Systems

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Design and Implementation of Smart Housing System for Elderly Persons

Design and Implementation of Smart Housing System for Elderl...

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2023 International Conference on Recent Advances in Electrical, Electronics, Ubiquitous Communication, and computational intelligence, RAEEUCCI 2023

作者： Madhav, P. Venu Reddy, V. Subba Jena, Biswajit Rishik, D. Ashfaque, Md. Raju, R. Chanikya Supriya, P. Pvp Siddhartha Institute of Technology Department of Electronics and Communication Engineering Vijayawada India Koneru Lakshmaiah Education Foundation Department of Electronics and Communication Engineering Guntur522302 India School of Electronics Engineering Vellore Institute of Technology Chennai India

ISBN: (纸本)9798350337426

We urgently want better management of all electrical and electronic applications. The project's suggested concepts will be very helpful in attaining this. Modern technologies incorporate several types of automation technology, such as voice recognition, Bluetooth, and Wi-Fi. Additionally, hand gesture-based automation has suffered in the instant market compared to other technologies now available in the field of automation. It has sparked a new thirst for automating systems that use gestures to turn on and off electrical equipment. There are a variety of automation systems available, each with unique capabilities. All home automation systems are used to control household equipment remotely. In this project, an automation system that may be operated by gestures is intended. © 2023 ieee.

关键词： automation

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SIGNRL: A Population-Based Reinforcement Learning Method for Continuous control

SIGNRL: A Population-Based Reinforcement Learning Method for...

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2023 ieee symposium Series on computational intelligence, SSCI 2023

作者： Zambrano-Gutierrez, Daniel F. Molina-Porras, Alberto C. Ovalle-Magallanes, Emmanuel Amaya, Ivan Ortiz-Bayliss, Jose C. Avina-Cervantes, Juan G. Cruz-Duarte, Jorge M. Tecnologico de Monterrey Monterrey64849 Mexico University of Guanajuato Salamanca36885 Mexico

ISBN: (纸本)9781665430654

In engineering processes that require continuous control, it is common to face significant challenges. Addressing these challenges through explicit modeling can take much work and effort. For this reason, Reinforcement Learning (RL) has gained popularity as a feasible strategy for solving this problem. In this context, various value-based methodologies, policies, or combinations have been employed to obtain an optimal learning policy. However, problems such as convergence to local maxima and high variance in training persist. In addition, computational time and cost increase in complex environments, so more robust RL methodologies are required. This paper proposes a Swarm intelligence Guided Neural Reinforcement Learning (SIGNRL) algorithm, which uses Particle Swarm Optimization as a multi-agent parameter explorer to find the optimal policy. Numerical results obtained in the OpenAI Gym Cart-Pole environment show that SIGNRL, with its gradient-free learning, exhibits good convergence and lower variance in continuous control tasks. © 2023 ieee.

关键词： Artificial Neural Networks control Systems Particle Swarm Optimization Reinforcement Learning

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Advancing the Connectivity and automation of Smart Devices by Merging Artificial intelligence with the Internet of Things 4

Advancing the Connectivity and Automation of Smart Devices b...

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4th International Conference on Technological Advancements in computational Sciences, ICTACS 2024

作者： Pareek, Shashank Almusawi, Muntather Al-Farouni, Mohammed Kumar, Raman Kaur, Kamaljeet Dasi, Shivakrishna Chandigarh University Department of Computer Science and Engineering Mohali India College of Technical Engineering The Islamic University Department of Computers Techniques Engineering Najaf Iraq School of Mechanical Engineering Rayat Bahra University Mohali India Chandigarh Engineering College Chandigarh Group of Colleges Department of Computer Science Engineering Punjab Mohali140307 India Nims School of Computing Science and Artificial Intelligence Nims University Rajasthan Jaipur India

ISBN: (纸本)9798350387490

This paper focuses at the achievement of AI with loT to improve the communication and control of smart devices in different sectors. Therefore, different machine learning models such as DQN, SVM, Random Forest, PCA, CNNs, and LSTM networks are used to enhance the smart home automation, industrial loT, health, and smart city sector to enhance the efficiency, and accuracy rates of the consumers. In smart homes AI models control energy and light based on people's activities in their home, say researchers. In industries, more enhanced version of machine learning enhances predictive maintenance as well the improvement of processes. As for the healthcare industry, it avails itself of AI in the detection of anomalies and in recommending a patient-specific treatment plan. This is a key aspect since in the smart cities AI models perform traffic and waste management, improving their effectiveness and, at the same time, their sustain ability. Therefore, the outcomes provide the evidence of the effectiveness of integrating AI and loT in order to expand the notions of the more effective and responsible systems. Recognizing that there is still work to be done on providing structure for the application these technologies collectively under head Artificial intelligence as well as loT, at the conclusion of the paper, the author presses for more work that will endeavor to sharpen the described models as well as search for other opportunities that might exist for these technologies. © 2024 ieee.

关键词： Patient treatment

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International Standards for Cybersecurity in Smart Devices for the Power Sector

International Standards for Cybersecurity in Smart Devices f...

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2024 International Conference on computational intelligence for Green and Sustainable Technologies, ICCIGST 2024

作者： Kaliappan, P. Sudha, S. Shankar, D. Metering and Utility Automation Division Central Power Research Institute Bengaluru India

ISBN: (纸本)9798350381887

The power sector is one of the most essential infrastructures globally. Digital transformation is underway in the power sector, making it more vulnerable to cyberattacks. The power sector is experiencing an increase in cyber incidents day by day. To protect power sector infrastructure against cyber attacks, technology, procedures, and people must work together;only then can prevention be achieved. The power sector needs to adhere to standards, regulations, and guidelines available for the effective implementation of a cyber security framework. The power sector has gained more attention and focus in the last five years. Numerous standards, including the NIST Cybersecurity Framework, IEC 62443, ieee 1686, IEC 62351, and IEC 62056, tackle cybersecurity concerns within control systems. Every standard covers and focuses on different domains and parts of the overall system. This paper presents applicable international standards for cyber security in the power sector. © 2024 ieee.

关键词： Cyber attacks

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