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Real-Time Rail Energy Consumption Minimization: Optimal Speed Profile Planning

Real-Time Rail Energy Consumption Minimization: Optimal Spee...

引用

International symposium on Applied computational intelligence and Informatics ( SACI)

作者： László Lindenmaier Szilárd Aradi István Ferenc Lövétei Dept. of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9798350329520

ISBN: (纸本)9798350329537

In rail traffic, the timetable must be re-planned in real-time when traffic is perturbed. Methods that optimally reroute and reschedule the trains to resolve this traffic management problem already exist. These optimization models usually focus on minimizing delays. However, energy consumption is a key to economical and sustainable transportation. In this paper, we propose a method that calculates optimal speed profiles to minimize the energy consumption of the trains after solving the rerouting and rescheduling problems with a conventional model. Using a simulation environment, the proposed method is evaluated in two different rail networks. According to the experimental results, the proposed model can decrease the overall energy consumption by more than 10% on average.

关键词： Rails Energy consumption Optimization models Energy resolution Transportation Minimization Real-time systems

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Neural fidelity warping for efficient robot morphology design

Neural fidelity warping for efficient robot morphology desig...

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ieee International Conference on Robotics and automation (ICRA)

作者： Hu, Sha Yang, Zeshi Mori, Greg Simon Fraser Univ Sch Comp Sci Burnaby BC Canada

ISBN: (纸本)9781728190778

We consider the problem of optimizing a robot morphology to achieve the best performance for a target task, under computational resource limitations. The evaluation process for each morphological design involves learning a controller for the design, which can consume substantial time and computational resources. To address the challenge of expensive robot morphology evaluation, we present a continuous multi-fidelity Bayesian Optimization framework that efficiently utilizes computational resources via low-fidelity evaluations. We identify the problem of non-stationarity over fidelity space. Our proposed fidelity warping mechanism can learn representations of learning epochs and tasks to model non-stationary covariances between continuous fidelity evaluations which prove challenging for off-the-shelf stationary kernels. Various experiments demonstrate that our method can utilize the low-fidelity evaluations to efficiently search for the optimal robot morphology, outperforming state-of-the-art methods.

关键词： Conferences Morphology Process control computational efficiency Bayes methods Task analysis Kernel

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Differentiable Particle Filtering Using Optimal Placement Resampling

Differentiable Particle Filtering Using Optimal Placement Re...

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International symposium on Applied computational intelligence and Informatics ( SACI)

作者： Domonkos Csuzdi Olivér Törő Tamás Bécsi Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Budapest Hungary

ISBN: (数字)9798350329520

ISBN: (纸本)9798350329537

Particle filters are a frequent choice for inference tasks in nonlinear and non-Gaussian state-space models. They can either be used for state inference by approximating the filtering distribution or for parameter inference by approx-imating the marginal data (observation) likelihood. A good proposal distribution and a good resampling scheme are crucial to obtain low variance estimates. However, traditional methods like multinomial resampling introduce nondifferentiability in particle filter-based loss functions for parameter estimation, prohibiting gradient-based learning tasks. This work proposes a differentiable resampling scheme by deterministic sampling from an empirical cumulative distribution function. We evaluate our method on parameter inference tasks and proposal learning.

关键词： Parameter estimation Filtering Particle filters State-space methods Proposals Task analysis Informatics

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A Model Integrating Wavelet Convolution and Linear Attention Mechanism for Inventory Management in Power Warehouses

A Model Integrating Wavelet Convolution and Linear Attention...

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Information Technology,Big Data and Artificial intelligence (ICIBA), International Conference on ieee International Conference on

作者： Tao Li Zhengli Zhang Ligang Li Guozheng Du State Grid Shandong Electric Power Company Material Company Jinan China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350363609

ISBN: (纸本)9798350363616

Accurate inventory management in power warehouses is crucial for maintaining consistency between records and actual stock levels. However, the complex storage layout and the diversity of stored materials often lead to human errors during manual inventory checks, resulting in inefficiencies. To address these challenges, we collected 2,000 images from power warehouse environments and created a binary classification dataset containing images of correctly and incorrectly placed items. We propose a novel network, CWAMNet, specifically designed for visual inventory management in complex power warehouse environments. CWAMNet integrates wavelet convolution and a linear attention mechanism to overcome the limitations of traditional convolutional neural networks (CNNs) and standard attention mechanisms, achieving a balance between model capacity and computational efficiency.

关键词： Solid modeling Visualization Attention mechanisms Accuracy Convolution computational modeling Inventory management computational efficiency Convolutional neural networks Standards

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ieee Joint 19th International symposium on computational intelligence and Informatics and 7th International Conference on Recent Achievements in Mechatronics, automation, Computer Sciences and Robotics, CINTI-MACRo 2019 - Proceedings

IEEE Joint 19th International Symposium on Computational Int...

引用

19th ieee Joint International symposium on computational intelligence and Informatics and 7th International Conference on Recent Achievements in Mechatronics, automation, Computer Sciences and Robotics, CINTI-MACRo 2019 - Proceedings

ISBN: (纸本)9781728156255

The proceedings contain 36 papers. The topics discussed include: mixed-order Sugeno model to predict the resultant force in the milling process for honeycomb sandwich;stoichiometry control of the two gas reactive sputtering process;demand side management electric energy consumption data processing architectures within internet of things context;development of an LQ regulator for longitudinal vehicle control of an automated vehicle;parking lot exploration strategy;a semi-automated generation of entity relationship diagram based on morphosyntactic tagging from the requirements written in a Serbian natural language;data analytics for health-care risk predictions based on ensemble classifiers and subjective projection;and data analytics for health-care risk predictions based on ensemble classifiers and subjective projection.

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Mastering control: A Digital Toolkit for Understanding PID controllers

Mastering Control: A Digital Toolkit for Understanding PID C...

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International symposium on computational intelligence and Informatics

作者： Martin Ferenc Dömény Tamás Dániel Szűcs Dániel András Drexler Levente Kovács Physiological Controls Research Center Research and Innovation Center of Óbuda University Óbuda University Budapest Hungary

control engineering education plays a pivotal role in shaping the competency of future engineers. However, the traditional educational approach predominantly emphasizes theoretical knowledge, often overlooking practical real-world applications. The evolving landscape of engineering education necessitates a shift towards dynamic learning methods that can effectively captivate the interest of students and facilitate a profound comprehension of concepts. Presently, numerous academic institutions that provide instruction in control systems tend to lack practical demonstrations using real-world systems. To address this educational gap comprehensively, we have developed an innovative application designed to empower users with the capability to experiment with real-time control scenarios. Through direct interaction with the application, users can acquire an enhanced insight into the behaviors exhibited by PID controllers. This application is crafted by integrating Arduino hardware with MATLAB software, resulting in a user-friendly interface. This interface not only enables real-time adjustment of control parameters but also provides an intuitive platform for the visualization of system responses. By offering such a versatile tool, the application fills a void in control systems education, granting students the opportunity to understand fundamental principles underlying control theory, particularly those related to the PID controller. In conclusion, the integration of this application into control engineering curricula stands to improve the way students comprehend complex control concepts. By merging theory with practical experimentation, the application creates an engaging and effective learning environment that equips aspiring engineers with invaluable skills for their future careers.

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Agent-Based Integrated Intelligent Parallel Scheduling System for Station Area

Agent-Based Integrated Intelligent Parallel Scheduling Syste...

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Digital Twins and Parallel intelligence (DTPI), ieee International Conference on

作者： Yibo Mi Dewang Chen Kejie Xu Shichao Chen Fenghua Zhu Gang Xiong School of Transportation Fujian University of Technology Fuzhou China China Mobile Communication Group Sichuan Co. Ltd Chengdu China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Beijing Huairou Academy of Parallel Sensing Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

In order to improve the intelligence and integration level of railway technical operation station and enhance the optimal allocation and efficient scheduling of station resources, an intelligent scheduling system is built based on the artificial system, computational experiment, parallel execution (ACP) method. It compiles data, empirical and mechanism, and its data compilation method supports the normal operation of the intelligent scheduling system. The artificial scheduling system is constructed by introducing multi-agent modeling, and the controllable factors and random disturbance factors under different scheduling scenarios are considered in the calculation experiment. The system is managed and controlled by constructing the railway transportation operation in parallel execution. Finally, the simulation experiment of station area scheduling has been completed, and its results demonstrate that it can not only improve the overall operation efficiency of the railway technical station, but also further enhance the overall operation efficiency of the station area.

关键词： Processor scheduling computational modeling Transportation Process control Interference Rail transportation Real-time systems Digital twins Resource management Reliability

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Development of non-invasive, bioimpedance-based measuring device for primary tumor detection 21

Development of non-invasive, bioimpedance-based measuring de...

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21st ieee International symposium on computational intelligence and Informatics

作者： Vizvari, Zoltan Gyorfi, Nina Mintal, Kitti Karadi, Zoltan Toth, Attila Sari, Zoltan Odry, Peter Eigner, Gyorgy Kovacs, Levente Lener, Violetta Hamori, Lilla Furedi, Andras Univ Pecs Fac Engn & Informat Technol Pecs Hungary Univ Pecs Med Sch Inst Physiol Szentagothai Res Ctr Pecs Hungary Univ Pecs Med Sch Inst Physiol Pecs Hungary Univ Dunaujvaros Dept Comp Syst & Control Engn Dunaujvaros Hungary Obuda Univ Phy Controls Res Ctr Budapest Hungary Natl Inst Oncol Dept Expt Pharmacol Budapest Hungary Res Ctr Nat Sci Inst Enzymol Budapest Hungary

ISBN: (纸本)9781665426848

Breast cancer is one of the most common causes of death in women, therefore early diagnosis of the tumor and continuous monitoring of the therapeutic response are essential for the successful treatment. Bioimpedance spectrum is a completely new oncological biomarker that could support early diagnosis, personalized cancer therapy and medical decision-making. The aim of this project is to develop a bioimpedance spectroscopy (BIS) -based diagnostic device and associated measurement protocols that can detect the emergence of primary tumors, track their growth and response to therapy with the same reproducibility and reliability as the currently used medical imaging methods like CT, MRI, US or PET. Due to the sensitivity and limitations of the BIS method were not yet fully known, the suitability of our novel measuring instrument for monitoring tumor growth was investigated using a genetically engineered mouse model of breast cancer. The following article describes the pilot experiment and its promising preliminary results examining breast cancer.

关键词： tumor detection bioimpedance spectrum non-destructive measurement pet model

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Knowledge Refinement: An Interpretable Analytics for Travel Behaviors Based on Knowledge automation

Knowledge Refinement: An Interpretable Analytics for Travel ...

引用

International Conference on Intelligent Transportation

作者： Peijun Ye Renrui Zhang Shichao Ge State Key Laboratory of Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Institute of Automation Beijing China School of Automation and Intelligence Beijing Jiaotong University Beijing China

ISBN: (数字)9798331505929

ISBN: (纸本)9798331505936

Travel behavioral analysis is crucial to the demand computation, which underpins traffic planning and optimization of transportation management and control. While traditional methods seek to descriptively learn the travel patterns through behavioral models as well as big data from multiple sources, they perform weak predictive ability of system's evolutionary features. To model and analyze the dynamics of such cyber physical social systems, this paper proposes an interpretable analytical method for travel behaviors based on knowledge automation (named as knowledge refinement). The new approach provides a feasible and reliable methodology for the analytics of heterogenous human participated systems, and is validated using one month's data of public transportation in Beijing. Results indicate that the approach not only has the state-of-the-art “reproductive” ability of actual traffic flows compare with traditional methods, but also can further reveal systemic dynamics with semantics such as the stable or divergent regions.

关键词： automation computational modeling Semantics Predictive models Big Data Data models Planning Reliability Public transportation Optimization

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A Hybrid Quadratic Programming Framework for Real-Time Embedded Safety-Critical control

A Hybrid Quadratic Programming Framework for Real-Time Embed...

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ieee International Conference on Robotics and automation (ICRA)

作者： Ryan M. Bena Sushmit Hossain Buyun Chen Wei Wu Quan Nguyen Viterbi School of Engineering University of Southern California Los Angeles CA USA

We present a new framework for implementing real-time embedded safety-critical controllers which utilizes hybrid computing to address the issue of limited computational resources, a problem that is particularly prevalent in microrobotics. In our approach, the nominal stabilizing control algorithm is implemented digitally while the safety-critical quadratic program is solved via a dedicated analog resistor array. We apply this hybrid computing architecture to a simulated collision avoidance task for a micro-aerial vehicle and show the benefit relative to a purely-digital implementation. By leveraging analog quadratic programming on the Crazyflie 2.1 micro quadrotor, a reduction in overall processing time from 8.9 ms to 0.6 ms is estimated for this computationally-limited system. We further display the viability of our proposed safety-critical control framework through real-time flight demonstrations, utilizing a novel prototype analog circuit tethered to the Crazyflie. The flight results confirm the functionality of the control structure and prototype circuit while highlighting the overall capabilities of hybrid computing.

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