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检索条件"任意字段=International Conference on Intelligent Computing and Control Systems"

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Prediction and analysis of the severity of road traffic accidents at traffic signs under rainstorm conditions 4

Prediction and analysis of the severity of road traffic acci...

引用

2024 4th international conference on intelligent Traffic systems and Smart City, ITSSC 2024

作者： Ge, Yao Zhao, Heyi Liu, Tong School of Electrical and Control Engineering North China University of Technology Beijing China School of Mechanical and Materials Engineering North China University of Technology Beijing China

ISBN: (纸本)9781510686304

The road driving environment is an important factor affecting the severity of traffic accidents. In this paper, the traffic accident at traffic signs under the condition of a rainstorm is taken as the research object to explore the causes and influencing factors of the accident. Based on the traffic accident cases in the US Accidents (2016-2023) database, this paper analyzes the distribution characteristics of the accident data, uses SMOTE technology to form a balanced dataset, and then uses XGBoost machine learning method to build a traffic accident prediction model. Finally, combined with SHAP interpretable analysis, the relationship between various factors and the severity of traffic accidents is further revealed. The results show that traffic jam distance, climatic conditions (temperature, air pressure, humidity), and road conditions are the important factors that cause traffic accidents under these conditions. According to the research results, this paper puts forward some suggestions to reduce accidents from the perspective of traffic management, which provides a new perspective and information for accurate accident prevention and control. © 2025 SPIE ·

关键词： Traffic signs

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An Event-Triggered Iteration Learning control Method for a Batch Distillation Process

An Event-Triggered Iteration Learning Control Method for a B...

引用

2024 international Annual conference on Complex systems and intelligent Science, CSIS-IAC 2024

作者： Zhang, Xiumei Zhou, Kailong Li, Hui Xia, Changlei Zhang, Ze Liu, Fangda College of Electrical and Electronic Engineering Changchun University of Technology Jilin Changchun130012 China Jiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources Intl. Innovation Center for Forest Chemicals and Materials Materials Science and Engineering Nanjing Forestry University Jiangsu Nanjing210037 China

ISBN: (纸本)9798331504755

An iteration learning control (ILC) method was employed for a nonlinear distillation process control system, which is one of the most useful processes in chemistry. This paper studied the integrated control problem with parameter uncertainties to improve the performance of batch process systems. A P-type event-triggered iterative learning control scheme based on Markov parameter identification which was minimized by the tracking error and cost function. The performance index for the next iteration was obtained, while the Markov parameter matrix was continually updated and iterated, constructing an adaptive iterative learning control scheme. A novel Lyapunov Adaptive Event Triggering Mechanism (LA ET) was proposed by combining the adaptive event triggering condition with the Lyapunov function. Convergence analysis was done mathematically for the constructed adaptive iterative learning control. As a result, the simulation experiments with the distillation process showed that the proposed algorithms effectively reduced the update frequency of control inputs, which increased the operating efficiency of the batch distillation system, and saved resources. © 2024 IEEE.

关键词： adaptive iteration learning control batch distillatio event-triggered control Lyapunov function Markov parameter matrix time and iteration domains

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Security Risk Assessment System for Power Monitoring systems Based on Zero Trust Architecture 4

Security Risk Assessment System for Power Monitoring Systems...

引用

4th international conference on Computer Science, Electronic Information Engineering and intelligent control Technology, CEI 2024

作者： Wei, Feng Chen, Zhao Wang, Yin Liu, Dongqing Zhang, Xun Zhao, Zhou State Grid Gansu Electric Power Research Institute Lanzhou China

ISBN: (纸本)9798350378542

With the continuous expansion of cyberspace, power systems face increasingly severe challenges from external hacker attacks and internal risks. Traditional security models based on perimeter defense can no longer meet the high-security requirements of modern power monitoring systems. This paper proposes a security risk assessment system for power monitoring systems based on the zero trust security model, aiming to address the challenges of external hacker attacks and internal risks faced by power systems. The system collects and analyzes various data in real time, using modular processing and a comprehensive scoring mechanism, and dynamically generates security status levels. On this basis, it implements security policies. Experimental results show that the system can effectively identify and respond to security threats, significantly reducing false alarms or missed alarms caused by single data sources and providing an efficient and reliable security solution for the power monitoring field. © 2024 IEEE.

关键词： Dynamic Risk Assessment Security of Power Monitoring systems Trust Level and Risk Rating Zero Trust Model

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DC-DC Dual Input Multiport Converter for DC Microgrid 3

DC-DC Dual Input Multiport Converter for DC Microgrid

引用

3rd IEEE international conference on Power Electronics, intelligent control and Energy systems, ICPEICES 2024

作者： Neha, Kodipyaka Reddy, R. Laxith Kumar, A. Vijay Saravanan, S. B V Raju Institute of Technology Vishnupur Dept. of Electrical and Electronics Engineering Medak Narsapur India

ISBN: (纸本)9798350387193

Nowadays adaption of microgrids are creating a revolutionary change. Microgrids are decentralized. It consists of energy storage system, loads and can integrate with different renewable energy sources. This paper proposes and explain about the multiport converter for dc microgrid applications. It explains about how the renewable energies such as solar power connected for the Dual Input Multi Output (DIMO) converter for the microgrid. Solar power generation depends on the irradiance levels. Every time a photovoltaic system is used, its Maximum electricity Point is altered since the amount of power generated from the panels varies. By tracking the maximum power and minimizing ripples MPPT methods such as Ripple Correlation control (RCC) is applied. By varying the different parameters, the output results for the different irradiation values at different temperatures, the output voltage of the multiport is observed using the MATLAB simulation. © 2024 IEEE.

关键词： DIMO multiport converter Microgrid MPPT Ripple Correlation control (RCC)

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Optimization of Field-Oriented control for BLDC Motors in Electric Vehicles Using Bio-Inspired Algorithms

Optimization of Field-Oriented Control for BLDC Motors in El...

引用

2024 IEEE international conference on Information Technology, Electronics and intelligent Communication systems, ICITEICS 2024

作者： Gopalakrishnan, R. Chandrakumar, E. Balan, Amisha Chandrasekar, T.K. Sivasankaran Pillai, B. Kumar, R. Sathees K S Rangasamy College of Technology Electrical and Electronics Engineering Tiruchengode India

ISBN: (纸本)9798350382693

Bio-Inspired Algorithm for Field-Oriented BLDC Motor control in Electric Vehicles,' indicates a research focused on the application of algorithms inspired by biological processes to control brush-less DC (BLDC) motors in electric vehicles (EVs) using a field-oriented control (FOC) strategy. This is a sophisticated and contemporary area of study that merges insights from nature (bio-inspiration) with advanced electrical engineering and control systems to enhance the efficiency, performance, and reliability of EV propulsion systems. Electric vehicles (EVs) represent a cornerstone of the transition towards more sustainable transportation systems. Among various technologies, brush-less DC (BLDC) motors are widely recognized for their high efficiency, reliability, and power-to- weight ratio, making them ideal for EV applications. However, optimizing their performance in dynamic driving conditions remains a challenge, necessitating advanced control strategies. A novel bio-inspired algorithm for the field-oriented control (FOC) of BLDC motors in EVs. Inspired by the adaptive and efficient strategies observed in biological systems, our algorithm aims to enhance the motor's performance across a wide range of operating conditions, focusing on energy efficiency, torque ripple reduction, and robustness against parameter variations and external disturbances. To develop the bio-inspired algorithm by drawing parallels between biological adaptability mechanisms and the dynamic requirements of BLDC motor control. The proposed algorithm was integrated into the FOC framework, a vector control strategy that decouples the motor's magnetic flux and torque components for precise control. The effectiveness of the algorithm was evaluated through a series of simulations and real-world tests, comparing its performance with traditional FOC methods and other bio-inspired control strategies. The bio- inspired algorithm demonstrated significant improvements in several key performance metrics. Spe

关键词： Adaptive control systems

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Medical Voice Question-Answering Interactive System Based on Speech Recognition Technology 3

Medical Voice Question-Answering Interactive System Based on...

引用

3rd international conference on intelligent computing and Human-Computer Interaction, ICHCI 2022

作者： Xin, Haihui Zhang, Shanshan Dalian University of Science and Technology Dalian China Dalian Maritime University Dalian China

ISBN: (纸本)9781510661301

The traditional medical voice question and answer interactive system can not meet the core needs of patient consultation service, and the patient's satisfaction with the system answer is low, so the research of medical voice question and answer interactive system based on speech recognition technology is proposed. In the hardware of the system, the control core of the system is the MCU module, which controls the normal operation of the whole system, realizes the conversion of the analog signal and digital signal through the audio input device, designs the serial communication device to transmit the data information to the computer, and uses the speech recognition technology to realize the software part of the system. And through the system test, the medical voice question and answer interactive system based on speech recognition technology is compared with the traditional medical question and answer interactive system. The experimental results show that the average response time of the medical voice question and answer interaction system based on speech recognition technology to the user request is far less than the traditional system, there is no number of error requests, and the performance is better than the traditional system. Therefore, it can be proved that the performance of the medical question and answer interactive system based on speech recognition technology has reached the expected standard, and can meet the basic needs of users for medical consultation services. © 2023 SPIE.

关键词： Computer control systems

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QoS Aware Resource Management in Mobile Edge computing for Emerging Artificial Intelligence (AI) Applications 19

QoS Aware Resource Management in Mobile Edge Computing for E...

引用

19th international conference on Mobility, Sensing and Networking (MSN)

作者： Ma, Zimo Zhao, Jun Nanyang Technol Univ Sch Comp Sci & Engn Singapore Singapore

ISBN: (纸本)9798350358261;9798350358278

The rapid development of intelligent machine learning and 5G/6G has led to smart terminal devices for various applications like auto-driving, AR, and smart farms. However, these applications have strict Quality of Service (QoS) requirements, exceeding the capabilities of mobile devices due to limited resources. Mobile edge computing offers a promising solution by enabling task offloading to nearby edge servers with better computing capabilities and a stable energy supply. For mobile edge systems, minimizing overall cost while ensuring QoS for mobile users is a challenging problem to solve effectively. In this paper, we first formulate the performance model for mobile edge systems with real data from deep learning scenarios. Then, we formulate the resource management in mobile edge system problem as a non-convex fractional programming problem with multiple coupled variables to minimize the latency and energy consumption while meeting QoS requirements. To solve the non-convex problem, a novel fractional programming technique is proposed to decouple the variables by considering fractional transformation to greatly reduce the complexity. Then we achieve the jointly optimal solution of the CPU frequency and offloading strategy with successive convex approximation, and Karush-Kuhn-Tucker (KKT) conditions. The experimental results show that our proposed algorithm can achieve cost-effective solutions while meeting QoS requirements over baselines.

关键词： Mobile edge computing resource allocation Quality of Service (QoS) energy efficiency deep learning

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A Dynamic Service Migration Method in Mobile Edge computing Based on Reinforcement Learning 8

A Dynamic Service Migration Method in Mobile Edge Computing ...

引用

8th international conference on Computer and Communication systems, ICCCS 2023

作者： Dong, Peiyang Duan, Zhengyu Xia, Lufeng Li, Zerui Anhui Branch of China Mobile Group Design Institute Co. Ltd. Hefei China

ISBN: (纸本)9781665456128

With the popularization and rapid development of the Internet of Vehicles and intelligent networked vehicles, the number of mobile edge computing (MEC) devices and data requests are growing rapidly. The quality of service (QoS) of intelligent connected vehicles (ICVs) under the traditional data processing mode is greatly restricted. This paper studied the dynamic service migration method of MEC node based on reinforcement learning. First, the edge migration model of urban 2-D intersection is established, and the model is described quantitatively;Secondly, aiming at the optimization indexes such as the complexity of edge migration and delay sensitivity in the network, a reinforcement learning algorithm integrating attention mechanism is proposed to optimize the dynamic migration process of edge services;Finally, a series of simulation experiments verify the performance of the proposed algorithm. © 2023 IEEE.

关键词： Reinforcement learning

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A Method for Rapid Risk Assessment of a Fog computing System with a Star-Shaped Topology 17

A Method for Rapid Risk Assessment of a Fog Computing System...

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17th international conference on Management of Large-Scale System Development, MLSD 2024

作者： Shiroky, Alexander V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Laboratory of Complex Systems Security Moscow Russia

ISBN: (纸本)9798350375718

Fog computing solutions significantly reduce communication delays in IoT-based cybersystems. They enable the development of large-scale IoT systems for transport, energy, and smart cities. Such an infrastructure must be highly secure. Therefore, risk management problems are actual there. One of the crucial features of fog computing networks is dynamic topology. Common approaches to cybersecurity do not consider topology change because many computer networks cannot be altered in this way just for security reasons. When managing the fog computing network a security specialist should know how its overall security changes with topology altering because understanding the extent and mechanism of topology's impact on fog computing system security increases the effect of security improvement costs. This study utilizes findings related to the impact of complex systems' structures on their overall risk to address enhancements in fog computing network security. It examines upper bounds of risk deviation for an approximate solution concerning the optimal placement of network nodes in a star-shaped topology and introduces a method for swift risk assessment in a fog computing network with this kind of topology. © 2024 IEEE.

关键词： Network topology

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Energy Efficiency Maximization in IRS-Assisted Wireless Powered MEC systems with NOMA

Energy Efficiency Maximization in IRS-Assisted Wireless Powe...

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2024 international conference on Cloud and Network computing, ICCNC 2024

作者： Liu, Xinying Zhang, Wenqian Huang, Mengting Zhang, Guanglin Donghua University College of Information Science and Technology Shanghai Maritime University College of Information Engineering

ISBN: (纸本)9798350367805

The integration of mobile edge computing (MEC) and wireless power transfer (WPT) effectively provides a robust solution to overcome the limitations imposed by the computational capacity and battery lifespan constraints of wireless devices (WDs). Nevertheless, the effectiveness of WPT and computation offloading cannot be guaranteed if the channels between the hybrid access point (HAP) and the WDs are obstructed. Therefore, intelligent reflecting surface (IRS) is implemented to boost system performance, complemented by the adoption of non-orthogonal multiple access (NOMA) protocol to further enhance spectral efficiency. We investigate the maximization of energy efficiency of NOMA-based IRS-Assisted WP-MEC systems while ensuring task queue stability in this article, which optimizes the reflection co-efficient matrix of IRSs during WPT and computation offloading stages, along with adjusting the CPU frequency and transmission power of WDs. A novel Lyapunov-based heterogeneous agent proximal policy optimization (LyHAPPO) algorithm is proposed to guarantee stability and exploit heterogeneous agent reinforcement learning, allowing the presence of different kinds of agents in the system to make appropriate decisions. The effectiveness of our proposed algorithm is evidenced by experimental results. © 2024 IEEE.

关键词： Computation offloading

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