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检索条件"任意字段=International Conference on Process Automation, Control and Computing"

共 28200 条记录，以下是91-100 订阅

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Restaurant Ranking System using Fuzzy TOPSIS, Fuzzy AHP & Fuzzy Synthetic Evaluation Techniques 3

Restaurant Ranking System using Fuzzy TOPSIS, Fuzzy AHP & Fu...

引用

3rd international conference on automation, computing and Renewable Systems, ICACRS 2024

作者： Keerthi, M. Dhanalakshmi, G. Rao, Trupthi Kodipalli, Ashwini Dept. of AI & DS Global Academy of Technology Karnataka Bangalore India

ISBN: (纸本)9798331532420

This research aims to build an efficient and organized restaurant ranking system. The prime target is to valuate and compare the performance of fuzzy analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS) techniques in this ranking system. Another objective of this system is to elevate stability and precision in ranking. On the other hand, traditional methods like scoring model, priority-based method and some other constantly strive with instability and perspective in customer preferences. The final result exhibit better performance of the proposed system compared to various traditional methods, exhibiting enhanced robustness and precision. © 2024 IEEE.

关键词： Analytic hierarchy process

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Distributed computing architecture and data communication implementation method of distribution network auxiliary planning platform 5

Distributed computing architecture and data communication im...

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5th international conference on Artificial Intelligence and Electromechanical automation, AIEA 2024

作者： Wang, Xiaobing Ding, Wenshu Jiang, Nian Yang, Kun Wang, Yuling Shen, Wenchang Wu, Qian State Grid Taizhou Power Supply Company Taizhou225300 China Science & Technology Co. Ltd. Department of Planning Center Hangzhou310012 China Science & Technology Co. Ltd. R&d Center Beijing102206 China

ISBN: (纸本)9798350366174

With the rise of big data, the planning and management of intelligent distribution networks have ushered in new development opportunities. Through the comprehensive integration, in-depth analysis, and effective mining of a large amount of heterogeneous data in the distribution network, various problems and challenges encountered in the planning process of intelligent distribution networks can be effectively addressed. However, this process relies on powerful computing power as support. This study focuses on exploring methods for deploying distributed computing communication in cluster environments to efficiently, flexibly, and reliably perform various tasks. By analysing the calculation time of actual power grid planning data, this study verifies the effectiveness and practicality of the proposed distributed computing architecture and communication design scheme. © 2024 IEEE.

关键词： Power distribution planning

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A Comparative Analysis of Fuzzy Methods for Predicting Student Dropout Rate 3

A Comparative Analysis of Fuzzy Methods for Predicting Stude...

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3rd international conference on automation, computing and Renewable Systems, ICACRS 2024

作者： Sumukha, K. Sahana, G. Rao, Trupthi Kodipalli, Ashwini Dept. of Artificial Intelligence & Data Science Global Academy of Technology Karnataka Bangalore India

ISBN: (纸本)9798331532420

Predicting student dropout accurately is a critical issue in the education system. This study employs fuzzy approaches - Analytic Hierarchy process (AHP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), and Fuzzy Synthetic Evaluation - to forecast dropout rates. By calculating criteria weights, closeness coefficients, and fuzzy scores, we rank alternatives and identify key attributes influencing dropout rates. Our results show that admission grade, age at enrollment, previous qualification, and curricular units in the 1st semester are the most significant predictors, while scholarship holder status has relatively lower importance. © 2024 IEEE.

关键词： Analytic hierarchy process

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XI international conference on High-Performance computing Systems and Technologies in Scientific Research, automation of control and Production, HPCST 2021

XI International Conference on High-Performance Computing Sy...

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11th international conference on High-Performance computing Systems and Technologies in Scientific Research, automation of control and Production, HPCST 2021

The proceedings contain 22 papers. The topics discussed include: mathematical modeling of monochromatic acoustic wave diffraction on a system of bodies and on flat screens;processing and analysis of botanical micro-and macroobjects using computer vision technologies;implementation of automation in vibration-isolating supports of new type for engines of sea and river vessels;the expert system for assessing fire risks of electrical installations in the agrarian industrial complex based on neural networks;development of a machine vision system for recording experimental data in the study of torsional stiffness by dynamic mechanical analysis;and application of the algorithm for calculating the boundaries of built-up areas from satellite images to calculating the areas of flooded land and the environmental potential of the territories of settlements.

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Fault detection and diagnostics of complex dynamic systems using Gaussian process Models - nuclear power plant case study 27

Fault detection and diagnostics of complex dynamic systems u...

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27th international conference on Methods and Models in automation and Robotics (MMAR)

作者： Puchalski, Bartosz Gdansk Univ Technol Fac Elect & Control Engn Dept Intelligent Control & Decis Support Syst 11-12 Gabriela Narutowicza St PL-80233 Gdansk Poland

ISBN: (纸本)9798350311075

The article examines the use of Gaussian process Models to simulate the dynamic processes of a Pressurized Water nuclear Reactor for fault detection and diagnostics. The paper illustrates the potential of Gaussian process Models as a tool for monitoring and predicting various fault conditions in Pressurized Water nuclear Reactor power plants, including reactor coolant flow and temperature variations, deviations from nominal working point or faulty power measurements. The article discusses the characteristics and benefits of Gaussian process Models and how they can be utilized to improve: the reliability and accuracy of nuclear power plant anomaly detection, fault diagnosis and decision making process in states of emergency. Overall, this paper highlights the capabilities of Gaussian process Models to enhance the safety, reliability and efficiency of nuclear power plants. The results of this study are expected to provide valuable insights for engineers and researchers in the fields of control engineering and nuclear power.

关键词： fault diagnosis maintenance gaussian processes process modeling

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Geometric Optimization through CAD-Based Bayesian Optimization with unknown constraint 12

Geometric Optimization through CAD-Based Bayesian Optimizati...

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12th international conference on control Mechatronics and automation

作者： Ben Yahya, Abdelmajid De Laet, Robbe Garces, Santiago Ramos Van Oosterwyck, Nick De Boi, Ivan Cuyt, Annie Derammelaere, Stijn Univ Antwerp Dept Electromech Cosys Lab Antwerp Belgium Flanders Make AnSyMo Cosys Leuven Belgium Univ Antwerp Dept Electromech InViLab Antwerp Belgium Univ Antwerp Dept Comp Sci Antwerp Belgium Univ Stirling Div Comp Sci & Math Stirling Scotland Belgian Nucl Res Ctr SCK CEN Mol Belgium

ISBN: (纸本)9798331517519;9798331517526

Position-controlled systems that perform repetitive tasks are crucial in industrial machinery. The electric actuators used in these systems are responsible for a large share of worldwide energy use, underscoring the opportunity for substantial energy savings in this area. In this context, mechanism design optimization is gaining popularity as it enables the minimization of the system's energy requirements while maintaining the same level of performance. However, current state-of-the-art methods often require complex analytic models of the system, which are highly machine-specific and prone to errors. Additionally, to efficiently search for the optimal design, these methods often neglect constraints or rely on analytic models to quantify the design space, further limiting the widespread adoption of these techniques. To overcome these issues, this paper proposes a novel method that relies solely on the often already available Computer-Aided Design (CAD) models of the systems to optimize the design. In addition, we employ Bayesian optimization (BO) to efficiently explore the design space, which simultaneously allows for training a constraint classifier to predict feasibility. This approach facilitates the industrial application of the proposed method and enables a faster and more efficient optimization process. By applying the method to a ventilator case study, it was found that the root mean square torque of the machine could be reduced by 71% compared to the currently used design, within 344 iterations.

关键词： Dimensional synthesis Mechanical systems Motion control Gaussian process classification Bayesian optimization

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Inference of Melt Pool Visual Characteristics in Laser Additive Manufacturing Using Acoustic Signal Features and Robotic Motion Data 10

Inference of Melt Pool Visual Characteristics in Laser Addit...

引用

10th international conference on control, automation and Robotic (ICCAR)

作者： Chen, Lequn Chew, Youxiang Feng, Wenhe Moon, Seung Ki Nanyang Technol Univ NTU Adv Remfg & Technol Ctr ARTC Singapore Singapore ASTAR Adv Remfg & Technol Ctr ARTC Singapore Singapore ASTAR Singapore Inst Mfg Technol Singapore Singapore Nanyang Technol Univ NTU Sch Mech & Aerosp Engn MAE Singapore Singapore

ISBN: (纸本)9798350373172;9798350373189

Laser additive manufacturing (LAM) demands robust real-time monitoring to identify defects and ensure product quality. Traditional methods, mainly reliant on coaxial cameras, lacks placement flexibility. Further complexities arise from the inherent variability in melt pool geometries and the high computational demands of image processing, hindering effective real-time monitoring. This research proposes a novel technique to directly infer melt pool visual characteristics in LAM by synergizing acoustic signal features with robotic tool-center-point (TCP) motion data. Acoustic monitoring has shown great promise in tasks typically reliant on vision sensors. In addition, the dynamics of the LAM process and defect occurrences are spatially dependent, primarily due to heat accumulation. By combining acoustic signals with spatial data from robot TCP motion, our method tracks melt pool variations with an R-2 score above 0.7. An ablation study demonstrated that the proposed method outperforms the acoustic-only models. The findings suggest that the integration of a simple microphone sensor with robot motion information emerges as a flexible, cost-effective alternative for capturing dynamic melt pool behavior. It presents new prospects for closed-loop control in the LAM process.

关键词： laser additive manufacturing real-time process monitoring Robot Operating Systems acoustic signal processing machine learning

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Filling process Optimization Through Fully Flexible Automatic Yogurt Filling Machine Using Industry 4.0 Concepts 11

Filling Process Optimization Through Fully Flexible Automati...

引用

11th international conference on control, Mechatronics and automation (ICCMA)

作者： Salah, Bashir Khan, Razaullah Almuhaidib, Ibrahim A. King Saud Univ Ind Engn Dept Coll Engn POB 800 Riyadh Saudi Arabia Univ Engn & Appl Sci Mech Engn Dept Swat Pakistan

ISBN: (纸本)9798350315684

process optimization of an automatic yogurt filling machine involves identifying areas for improvement and implementing changes to enhance efficiency, productivity, and overall performance. Some steps that can be taken to optimize the process include analyzing the current process, setting performance goals, evaluate technology and equipment, automation and robotics, workflow optimization, sensor and control systems, data-driven decision-making, and continuous monitoring and maintenance. This article centers around the process optimization of a cutting-edge, fully automatic yogurt and flavors filling machine, built based on the principles of Industry 4.0. The machine's settings were transformed to achieve full flexibility, enabling each filling point to handle both yogurt and various flavors. To minimize the overall processing time for order execution, a mathematical model was meticulously devised. The performance of this proposed model was evaluated by comparing it with previously published models. The results indicate that the proposed model outperforms its predecessors, demonstrating superior efficiency and effectiveness.

关键词： Fully Flexible Machine Parallel Machine Scheduling Industry 4.0 Robotic Arm Yogurt Filling Machine

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Cloud Architectural Design for Image-based Vehicle Positioning in Traffic Management 28

Cloud Architectural Design for Image-based Vehicle Positioni...

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28th international conference on System Theory control and computing

作者： Beti, Iosif-Alin Herghelegiu, Paul-Corneliu Amarandei, Cristian-Mihai Caruntu, Constantin-Florin Gheorghe Asachi Tech Univ Iasi Dept Automat Control & Appl Informat Iasi Romania Gheorghe Asachi Tech Univ Iasi Dept Comp Sci & Engn Iasi Romania

ISBN: (纸本)9798350364309;9798350364293

Vehicle positioning algorithms are essential for improving traffic management and safety by accurately locating vehicles in real-time, and, thus, minimizing congestion and accidents. They also support the development of advanced driver assistance systems and autonomous vehicles, relying on precise positioning data for safe navigation. One of the solutions involves using image processing algorithms, which can have two approaches. One approach is decentralized, in which each vehicle performs its own computing steps and determines its position concerning the other nearby vehicles. The second approach, proposed in this paper, is centralized, where each vehicle sends data to a server that uses cloud computing to process all the data in real-time. As such, vehicles can create a more comprehensive view of the driving conditions in the area by using either of these two approaches, which can help them anticipate potential hazards and make more informed decisions.

关键词： computer vision traffic optimization vehicle platooning cloud computing 5G networks vehicle positioning V2V communication

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Online Self Optimizing Posicast controller Framework for Smart process control 11

Online Self Optimizing Posicast Controller Framework for Sma...

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11th international conference on control, Mechatronics and automation (ICCMA)

作者： Nwoke, Justus Viola, Jairo Chen, YangQuan Univ Calif Merced MESA Lab Merced CA 94343 USA

ISBN: (纸本)9798350315684

Posicast control is a strategy employed for overshoot compensation of lightly damped systems. Its classical approach is mainly used in a feedforward setup to compensate for the system's initial oscillation. However, if the system has a parametric uncertainty and high oscillation, the Posicast control effectiveness is reduced. This paper presents the design of a Self Optimizing Posicast controller with an online optimizing agent to effectively mitigate the oscillatory behaviour and overshoot on highly oscillatory systems. The controller comprises of a closed-loop setup regulator, a posicast filter, and an online optimizer based on the Globalized Constrained Nelder-Mead optimization algorithm to perform real-time estimation of the controller and posicast filter parameters. The proposed framework improves the system's robustness under parametric uncertainty and is validated for a flyback converter on voltage regulation tasks.

关键词： Posicast Self Optimizing control Globalized Constrained Nelder Mead Flyback Converter Smart process control Benchmark

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