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检索条件"任意字段=8th International Workshop on Control Engineering and Advanced Algorithms, IWCEAA 2024"

共 143 条记录，以下是51-60 订阅

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the HEFT Algorithm Based on Node Merging

The HEFT Algorithm Based on Node Merging

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Ying Huang Yuanhong Lu Jie Zhang Jingyue Zhang Haiping Guo National Energy Power Grid Technology R&D Centre Guangzhou 510663 State Key Laboratory of HVDC Electric Power Research Institute China Southern Power Grid Guangzhou 510663 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou 510663 Guangzhou China National Energy Power Grid Technology R&D Centre Guangzhou 510663 CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou 510663 Guangzhou China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

the task scheduling problem in power systems is complex, especially when communication costs exceed computation costs. this paper proposes an improved HEFT algorithm with a node merging mechanism, merging nodes through hierarchical traversal to assign high-communication-cost tasks to the same processor, reducing communication overhead. Experiments with 499-dimensional and 1614-dimensional matrices from the power system show that the improved algorithm reduces completion time by 5ms and 2ms, respectively, compared to standard HEFT.

关键词： Costs control engineering Processor scheduling Conferences Merging Power systems Standards

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advanced Water Quality Assessment through Integrated Machine Learning models for Classification 8

Advanced Water Quality Assessment through Integrated Machine...

引用

8th IEEE international Conference on Computing, Communication, control and Automation, ICCUBEA 2024

作者： Ladani, Dhruv Bhesaniya, Nency Shekhaliya, Dhyey Swain, Debabrata Bhilare, Amol Pandit Deendayal Energy University Department of Computer Science and Engineering Gandhinagar India Vishwakarma Institute of Technology Department of Computer Engineering Pune India

ISBN: (纸本)9798350391770

Water, the basic necessity of any living organisms, constitutes a fundamental human right yet remains tragically inaccessible and unsafe for millions. With nearly 2.5 million annual deaths attributed to waterborne diseases, ensuring access to pollution-free water transcends mere necessity, becoming a potent catalyst for improved global health. Freshwater scarcity is a global problem that is being exacerbated by overexploitation of freshwater sources and climate change impacts. this research delves into machine learning algorithms for analyzing and classifying safe water quality. this research study conducts a comparative analysis of water quality classification models utilizing a series of machine learning algorithms. A series of data preprocessing steps were implemented on this dataset with a view to construct a generic model. this set of steps includes balancing of data using the balancing algorithm and the feature selection. Out of all these applied learning techniques, Random Forest (RF) and XGBoost with hyper parameter (HP) tuning provides the highest accuracy equal to 94.62% and 95.39%. © 2024 IEEE.

关键词： Adversarial machine learning

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Robust Fault- Tolerant control Algorithm for Intelligent Vehicles Based on LPV Model 8

Robust Fault- Tolerant Control Algorithm for Intelligent Veh...

引用

8th CAA international Conference on Vehicular control and Intelligence, CVCI 2024

作者： Yang, Weixin Pan, Juntao Song, Yanzhen Zhang, Xueyuan Bian, Xiangyuan Gao, Xulang School of Electrical and Information Engineering North Minzu University Yinchuan China

ISBN: (纸本)9798331504892

this paper explores robust fault-tolerant control (FTC) of intelligent vehicles based on the linear parameter-varying (LPV) model. the vehicle system is a complex nonlinear system, making it challenging to design FTC algorithms. Firstly, an LPV model is developed for the vehicle system, aiding in understanding and predicting the system's behavior. Secondly, an error control system is designed for the vehicle, combining feedforward and feedback control to enhance the performance of the error tracking system. Finally, a state feedback control algorithm is designed for the vehicle system to cope with actuator failures. the algorithm is validated through high-fidelity Simulink simulations. © 2024 IEEE.

关键词： State feedback

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Secure Boot Implementation in Automotive Electronic control Unit 8

Secure Boot Implementation in Automotive Electronic Control ...

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8th IEEE international Conference on Computational System and Information Technology for Sustainable Solutions, CSITSS 2024

作者： Hallikar, Rohini S. Deshpande, Abhay Rozhnov, Aleksei Tengli, Alaska Kotagi, Akash Rv College of Engineering Dept. of Electronics and communication Bangalore India Institute of Control Sciences Moscow Russia

ISBN: (纸本)9798331505462

Estimations show that modern cars have about 100 million lines of code. By 2030, this number is expected to quadruple. To put this in perspective, an operating system for a PC can include up to 40 million lines of code, but a passenger airplane typically contains roughly 15 million lines. the exponential rise in complexity of automotive software high-lights the urgent need for improved cybersecurity solutions to reduce the danger of cyberattacks and guarantee the security of drivers and passengers. To resolve this issue there are few of the cryptographic algorithms used such as advanced Encryption Algorithm(AES) for the faster and reliable execution multiple iterations are done in the paper we will look into the process and outcomes of AES in automotive secure boot. © 2024 IEEE.

关键词： AES Algorithm Automotive cybersecurity crypto-graphic algorithms Secure Boot

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Revolutionizing Hearing Health: Mobile-based Audiometry Assessment Enhanced by Machine Learning Integration 8

Revolutionizing Hearing Health: Mobile-based Audiometry Asse...

引用

8th international Conference on Inventive Systems and control, ICISC 202

作者： Kanimozhi, P. Jebasanthiya, P. Kumar, T.Ananth Hussain, Mohamed Inamul Ananth, Christo Preethi, E. Ifet College of Engineering Dept of Computer Science Engineering Villupuram India Holy Cross Engineering College Dept of Computer Science Engineering Tamilnadu Thoothukudi India Samarkand State University Uzbekistan

ISBN: (纸本)9798350386578

the Mobile-Based Audiometry Test Assessment with Machine Learning Integration is a user-friendly application for convenient and accurate hearing health assessment. this innovative app incorporates advanced machine learning algorithms to enhance the precision of hearing tests, allowing for early detection of hearing impairments. Users can effortlessly create profiles, securely store their test results, and access their hearing history. the application ensures the calibration of user hardware for accurate tests, closely mirroring clinical audiometry standards with a wide range of frequencies and decibel levels. Machine learning, particularly decision tree classification, is seamlessly integrated to improve the accuracy of audiogram analysis and classification, enabling the identification of varying degrees of hearing loss. the user-centric design and educational resources encourage awareness and proactive management of hearing health. this Mobile-Based Audiometry Test Assessment with Machine Learning Integration offers an accessible, technologically advanced solution for individuals to take charge of their auditory health and make informed decisions about their well-being. © 2024 IEEE.

关键词： Audiometers

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Emergency Department Asthma Management: Harnessing Clustering algorithms for Enhanced Precision Medicine 8

Emergency Department Asthma Management: Harnessing Clusterin...

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8th IEEE international Conference on Computing, Communication, control and Automation, ICCUBEA 2024

作者： Khodke, Manjiri Prashant Mane, Pratham Deepak Laheri, Meet Anil Deshpande, Himani Thadomal Shahani Engineering College Bandra Mumbai India

ISBN: (纸本)9798350391770

Precision medicine is essentially a modern approach to understanding health. Treatment decision support systems, or TDSSs, are a crucial part of modern health care methods. they are designed to close the knowledge gap between patients' initial knowledge and the comprehensive information required to make well-informed treatment decisions. Asthma remains a significant public health concern, particularly in the Emergency Department (ED) setting, where swift and accurate management is paramount. In our research we used clustering algorithms to scrutinize clustering accuracy, clinical significance, computational efficiency, and pinpointed the optimal approach with 88.43% of K-means Algorithm and 88.28% of Density-based Algorithm of correctly categorized instances. Based on accuracy and a balanced cluster distribution, Simple K-means and Density-based algorithms achieve more effective examples for individualized decision-making that produce informative outcomes. through the application of advanced data analytics tools and precision medicine concepts, our research aims to optimize asthma management in the emergency department to streamline healthcare delivery and reduce costs. We seek to improve outcomes and reduce healthcare utilization by personalizing therapy recommendations for asthma patients by integrating clustering algorithms into treatment decision support systems (TDSS). © 2024 IEEE.

关键词： Diseases

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MCFOF: Multi-Compilation Fusion Optimization Framework using ROSE Compiler Infrastructure

MCFOF: Multi-Compilation Fusion Optimization Framework using...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Chen Wang Yuanyuan Ma Sheng Zhu Chenhan Lin Wen Ji China Electric Power Research Institute Co. Ltd Nanjing Jiangsu China STATE GRID FUJIAN ELECTRIC POWER CO. LTD Fuzhou Fujian China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

In the realm of computer science research, compiler optimization is regarded as one of the core techniques for program optimization, greatly propelling the advancement of high-performance computing. During the process of optimizing a program through compilation, it is acknowledged that while the selected compiler from a candidate set may exhibit optimal effects on overall program optimization, it may not necessarily yield the most optimized results for certain code segments within the program. To address this issue, this paper proposes and practically implements a multi-compiler fusion optimization framework (MCFOF) based on functions using ROSE compiler infrastructure. MCFOF selects the optimal compiler for each function within the program, thus integrating the strengths of multiple compilers. Experimental results demonstrate that MCFOF significantly enhances code performance compared to three selected general-purpose compilers and a polyhedral com-piler on multiple platforms. Specifically, it achieves an average performance improvement of 33.2% on the x86 64 platform and 13.4% on the ARMv8 platform. Furthermore, these results confirm the framework's platform independence.

关键词： Program processors Codes control engineering Synthesizers High performance computing Conferences Propulsion Data collection Data mining Optimization

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Research of Continuous thermoplastic Coating Equipment Based on Virtual Simulation

Research of Continuous Thermoplastic Coating Equipment Based...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Lingyan Hu Haixin Xue Tianyi ChenZhuang Meng Cao Chunping Yuan Huiming Hou School of Electronic and Electrical Engineering Shanghai University of Engineering Science Shanghai China School of Information Engineering Nanchang University Nanchang Nanchang Jiangxi China National Advanced Medical Engineering Research Center China State Institute of Pharmaceutical Industry Shanghai China Department Innovation and Regulatory Scientific Development Shanghai Drug Evaluation and Verification Center Shanghai China Shanghai Engineering Research Center of Pharmaceutical Intelligent Equipment Shanghai University of Engineering Science Shanghai China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

In order to realize the industrialization of the new thermoplastic coating method for osmotic pump tablets, it is necessary to develop new continuous coating equipment for thermoplastic coating. In order to accelerate the process of equipment development and reduce the research and development cost, this paper proposed a novel simulation method with VUP and PLC to test and validate the newly designed equipment in a virtual environment. After building a 3D model of the equipment in VUP and designing the PLC control algorithm in PLC, a communication connection is established between PLC and VUP, enabling the PLC at TIA Portal V16 to send control commands to control the mechanical system at VUP and receive feedback from the mechanical system at VUP. the novel simulation method can test and validate the system design, including the program and mechanical structure, in a virtual environment, and the potential problems can be identified in advance to avoid the high costs associated with fixing these problems at the physical prototyping stage. the simulation experiment and its actual experiment results show that the designed hardware and software can realize the continuous thermoplastic coating process.

关键词： Heating systems Hands Costs Accuracy Computational modeling Virtual environments Software Coatings Mechanical systems Portals

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Impact of Reservation on the Performance of Optimal control in Electric Vehicles Fast Charging Stations 24

Impact of Reservation on the Performance of Optimal Control ...

引用

24th EEEIC international Conference on Environment and Electrical engineering and 8th I and CPS Industrial and Commercial Power Systems Europe, EEEIC/I and CPS Europe 2024

作者： De Santis, Emanuele Liberati, Francesco Di Giorgio, Alessandro Sapienza University of Rome Diag Department Rome Italy

ISBN: (纸本)9798350355185

Service stations equipped with multiple delivery points for plug-in electric vehicles fast charging are expected to gradually replace petrol-based service stations. Operators interested in managing the new stations are going to face key challenges in terms of sizing the station's point of connection to the grid so as to render the provision of the service economically viable. As connection fees depend on the plant nominal power, sustainability is expected to come from the integration in the area of local generation from renewable energy sources and an electric energy storage device. this paper presents an approach based on optimal control methodology for regulating the energy flows at the point of connection of a service station with the grid. the control goal is to optimally balance the Plug-in Electric Vehicle (PEV) recharging power through the Energy Storage System (ESS), while also taking into account an uncertain number of charging requests and local generation. the overall objective is to lower as much as possible the power flowing at the point of connection with the grid, while providing as much as possible maximum power to the single PEVs. A model predictive control (MPC) algorithm is proposed to control the ESS. the single MPC iteration is based on continuous time optimal control. the core contribution of this paper is in the study of the impact of the level of uncertainty of the charging power (i.e., the number of charging requests by the PEV owners) on the performance of the controller. Simulation results show that reservations of the charging service represent a key aspect to take into account for taking decisions on the size of service station point of connection, even with the aforementioned control architecture. © 2024 IEEE.

关键词： Charging stations

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Based on Dual-Channel Feature Selection for NOx Concentration Prediction Using Informer

Based on Dual-Channel Feature Selection for NOx Concentratio...

引用

control engineering and advanced algorithms (iwceaa), international workshop on

作者： Feng Zhao Hui Yi Yuheng Chai Lu Dong Zhilong Xu college of electrical engineering and control science Nanjing Tech University Nanjing China Jiangsu Ankong Zhihui Technology Co. Ltd Changzhou China

ISBN: (数字)9798331528881

ISBN: (纸本)9798331528898

Aiming at the problem that the large lag in the measurement of inlet NOx concentration of Selective Catalytic Reduction (SCR) in coal-fired power plants causes the delayed response of the measurement system, and the data are nonlinear and time-varying, we propose a NOx concentration prediction method based on the two-channel feature screening Informer. the model first uses the maximum information coefficient to calculate the correlation coefficient between the feature variables and the inlet NOx concentration, and screens the feature variables with a high degree of correlation, and then adopts the variational modal decomposition algorithm to decompose the inlet NOx concentration, retaining most of the local features and detailed information to reduce the influence of noise and interference on the model prediction, and the data set of the two-channel screening is reorganized to get the reconstructed data set, and finally the reconstructed data set is input into the Informer model to predict the NOx concentration. Finally, the reconstructed data set is input to the Informer model to predict the inlet NOx concentration. the DCF - Informer prediction model is validated with the historical operation data of a 600MW power boiler in a power plant. the experimental results show that the evaluation index R2 is improved by at least 6% compared with other prediction models, which verifies that the model has high prediction accuracy and better generalization effect. It provides strong support for the SCR denitrification system to realize accurate ammonia inj ection.

关键词： Ammonia Accuracy Power measurement Time series analysis Predictive models Feature extraction Prediction algorithms Data models Power generation Time-varying systems

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