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4th International conference on Numerical Computations: Theory and Algorithms, NUMTA 2023

ISBN: (纸本)9783031812460

The proceedings contain 105 papers. The special focus in this conference is on Numerical Computations: Theory and Algorithms. The topics include: Resource Allocation via Bayesian Optimization: an Efficient Alternative to Semi-Bandit Feedback;multi-Objective and Multiple Information Source Optimization for Fair & Green Machine Learning;extended Optimal control Problem for Practical Application;explainable process Deviance Discovery with data-Efficient Deep Learning;line Search Stochastic Gradient Algorithm with A-priori Rule for Monitoring the control of the Variance;a Machine Learning Approach to Speed up the Solution of the Distributor’s Pallet Loading Problem;combined First- and Second-Order Directions for Deep Neural Networks Training;constrained Global Optimization by Smoothing;the Unreasonable Effectiveness of Optimal Transport Distance in the Design of Multi-Objective Evolutionary Optimization Algorithms;an Improved Modified Jaya Optimization Algorithm: Application to the Solution of Nonlinear Equation Systems;GPU Acceleration of the Enhanced Jaya Optimization Algorithm for Solving Large Systems of Nonlinear Equations;effective Resistance Based Community Detection in Complex Networks;a Comparison of Formulations for Aircraft Deconfliction;optimal Recombination Problem in Genetic Programming for Boolean Functions;heuristics with Local Improvements for Two-processor Scheduling Problem with Energy Constraint and Parallelization;numerical analysis of Optimal control of Assets and Liabilities by a Bank;optimal control for Stochastic Multi-agent Systems With the Use of Parallel Hybrid Genetic Algorithm;DC Optimization in Adversarial Sparse Support Vector Machine;A First-Order Optimality Condition in Nonsmooth Generalized Semi-infinite Programming (GSIP);miniaturisation of Binary Classifiers Through Sparse Neural Networks;Price Forecasting for Bitcoin: Linear Regression and SVM Approaches;inside the Box: 0–1 Linear Programming Under Interval Uncertainty;machine Learn

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Simulation modeling and analysis of the Efficiency of a Modern Hypermarket

Simulation Modeling and Analysis of the Efficiency of a Mode...

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International conference on control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Tatiana A. Grober Oleg V. Grober Department of Information Technology Don state technical University Rostov-on-Don Russia Department of Mathematics and Computer Science Don state technical University Rostov-on-Don Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

This work is devoted to the problem of investigating the effectiveness of the hypermarket of building materials. The purpose of the study is to develop and optimize, according to the efficiency criterion, a simulation model of a hypermarket of building materials as a queuing network. The GPSS programming language and the GPSS World modeling environment were used as a development tool. The simulation model has been verified and validated.

关键词： Analytical models Building materials Simulation process control Programming Mathematical models data models Energy efficiency Reliability Queueing analysis

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RaiiRED: A Node-RED-Based Framework for modeling Train control Management Systems 20

RaiIRED: A Node-RED-Based Framework for Modeling Train Contr...

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20th International conference on Wireless and Mobile Computing, Networking and Communications, WiMob 2024

作者： Rizzardi, Alessandra Corte, Raffaele Della Cevallos, Jesus F.M. Orbinato, Vittorio De Vivo, Simona Sicari, Sabrina Cotroneo, Domenico Coen-Porisini, Alberto Universita degli Studi dell'Insubria Dipartimento di Scienze Teoriche e Applicate VA Varese21100 Italy Universita degli Studi di Napoli Federico Ii Dipartimento di Ingegneria Elettrica e delle Tecnologie dell'Informazione NA Naples80125 Italy

ISBN: (纸本)9798350387445

The modeling and simulation of Internet of Things (IoT) and Industrial IoT (iioT) systems allow practitioners to obtain valuable insights into the system's behavior before their actual deployment in the field. Early designing permits the analysis of the interactions among the involved entities, evaluating the effects of modifications, and understanding the impact of failures on the system. In particular, this is exacerbated in the context of IoT/iioT, which is characterized by multiple and heterogeneous subsystems, different processing levels, and communication protocols. In such a direction, recent innovations in IT devices have enabled the rail industry to gather information from Train control and Monitoring Systems (TCMS) to check conditions constantly and prevent issues, thus improving relia-bility and safety and, in some cases, leading to cost-saving by optimizing maintenance resources. In such a scenario, this paper presents RailRED, a framework for simulating and prototyping a TCMS based on the Node-RED tool. In RaiiRED, the main TCMS subsystems are modeled using Node-RED flows, while the subsystem interconnections are performed through a low footprint and encrypted gateway based on the MQTT protocol. The proposal can also generate diagnostic data that mimic the behavior of a real-world TCMS. RailRED communication latency and its ability to generate diagnostic data have been analyzed, with the latter evaluated by using clusters of diagnostic events collected from a real-world TCMS running on a high-speed train. © 2024 IEEE.

关键词： Railroad transportation

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MATLAB-BASED COMBINATORIAL ISOCONVERSIONAL analysis TECHNIQUES FOR CHARACTERIZING THERMOSET CURE KINETICS

MATLAB-BASED COMBINATORIAL ISOCONVERSIONAL ANALYSIS TECHNIQU...

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SAMPE 2022 conference and Exhibition

作者： Watts, Adam Peyron, Mark Western Washington University Department of Engineering and Design Plastics and Composites Engineering Program BellinghamWA98225 United States

ISBN: (纸本)9781934551417

Isoconversional analysis (ICA) is one of the most important methods for establishing the kinetics of the complex reactions associated with curing thermosets. An often overlooked or hard to establish feature of these kinetics is estimating the uncertainties in the kinetic parameters. In the case of ICA, activation energy is measured at fixed values of reaction conversion. For thermosets the data are typically based on differential scanning calorimetry (DSC). When replicate DSC data are obtained there is no agreement how to utilize the replicates to assess repeatability in the context of ICA. The authors propose that a combinatorial approach be used to assess the variability due to i) experimental variability and ii) linear and nonlinear computations that are used to calculate values of the activation energy. A MATLAB-based analysis was developed to analyze all possible combinations of replicates and using four different ICA methods to establish a conversion map of activation energies along with statistically valid values of standard deviations. The use of these techniques is demonstrated with a benzoxazone resin. This combinatorial technique provides new insights into uncertainty associated with modeling thermoset cure kinetics. This technique may also be used to estimate the uncertainty in isothermal and nonisothermal predictions based on the DSC data and measured activation energies. The MATLAB analysis will be made freely available to other users via the author’s website. It may be applied to any thermally-stimulated process. Copyright 2022. Used by the Society of the Advancement of Material and process Engineering with permission.

关键词： Activation energy

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A Rapid and Integrated modeling Method of Aircraft Vulnerability Based on CATIA analysis Simulation Module 5th

A Rapid and Integrated Modeling Method of Aircraft Vulnerabi...

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5th China Aviation Science and Technology conference, 2021

作者： Pei, Yang Shi, Likuan Ge, Yuxue Li, Mingsuo Bai, Chunyu Zhang, Yu School of Aeronautics Northwestern Polytechnical University Xi’an710072 China Science and Technology on Electro-Optic Control Laboratory Luoyang471009 China Aviation Key Laboratory of Science and Technology on Structures Impact Dynamics Aircraft Strength Research Institute of China Xi’an710065 China

ISBN: (纸本)9789811674228

Aircraft vulnerability modeling is the basis and prerequisite for vulnerability analysis. At present, vulnerability modeling methods include combinatorial geometry, triangular patch, and tetragonal patch. However, these methods have disadvantages such as low modeling accuracy, complex modeling process, and finite element software. Under the problems of the above methods, a vulnerability modeling method is proposed based on the CATIA analysis Simulation module, in which the secondary development of the aircraft shape and the tetragonal mesh, materials, and attribute of the components data file are completed. In this method, the geometrical modeling and meshing are synchronized and integrated into the CATIA platform which shortens the vulnerability pre-modeling process. Taking the US "Scan Eagle" UAV as an example, the input model file for vulnerability analysis is generated. The effect of this method and the traditional finite element modeling method is compared in C and K kill levels, which verifies the validity and usability of the proposed method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Aircraft

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modeling of Time Series with Structural Discontinuities Based on Fuzzy Markov Chains

Modeling of Time Series with Structural Discontinuities Base...

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International conference on control Systems, Mathematical Modelling, Automation and Energy Efficiency (SUMMA)

作者： Mikhail Matveev Ekaterina Sirota Computer Science Faculty Voronezh State Univercity Voronezh Russia

ISBN: (数字)9798331532178

ISBN: (纸本)9798331532185

In this paper, multidimensional time series with structural discontinuities or disorder are considered. A structural break or disorder is understood as a change in the parameters of the process behavior model or the parameters of the distribution of a random component. The aim of the study is to build an autoregression model with variable coefficients that take into account structural gaps. modeling of such a time series is implemented on the basis of fuzzy Markov chains. The technique is based on the transformation of a numerical time series into a random sequence of categorical fuzzy states. The considered approach makes it possible to solve the general scientific problem of modeling a time series with implicit changes in properties and significantly improve the quality of the model compared to the known ones.

关键词： Temperature distribution Atmospheric modeling Time series analysis Weather forecasting process control Predictive models Mathematical models data models Numerical models Random sequences

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modeling spherulitic and fibrillar crystallization kinetics in injection molding: analysis of process variables and morphological evolution

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POLYMER 2024年 312卷

作者： Speranza, Vito Liparoti, Sara Titomanlio, Giuseppe Pantani, Roberto Univ Salerno Dept Ind Engn Via Giovanni Paolo II 132 I-84084 Fisciano SA Italy

Injection molding of polypropylene was conducted using a heating device to control mold surface temperature over time. By varying the temperature and heating times, a significant effect on cavity pressures, temperatures, and morphology distribution in the resulting samples was obtained. The University of Salerno's UNISA code, a simulation model for injection molding, was used to simulate the experimental conditions. This code incorporates a crystallization kinetics model that accounts for the competing formation of spherulites and fibrils from the same amorphous material, considering the effects of temperature, pressure, and flow evolution during different stages of the process. The simulation results showed good agreement with experimental data for temperature evolutions within the mold and pressure variations at critical points during the filling, packing, and cooling stages. Additionally, the simulation consistently predicted the formation of a fibrillar layer near the mold wall. Overall, a comprehensive framework for understanding and simulating the injection molding process is provided, with relevant implications for the optimization of manufacturing conditions and improving part quality.

关键词： Injection molding

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Application of data distribution metrics for soft sensors in industrial scenarios 1

Application of data distribution metrics for soft sensors in...

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IEEE International conference on Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (IEEE MetroXRAINE)

作者： Curreri, Francesco Patane, Luca Xibilia, Maria Gabriella Univ Palermo Dept Math & Comp Sci Palermo Italy Univ Messina Dept Engn Messina Italy

ISBN: (数字)9781665485746

ISBN: (纸本)9781665485746

Industry 4.0 requires the implementation of efficient plant monitoring and control policies to improve automation, communication and self-monitoring in traditional manufacturing and industrial practices [1]. Soft Sensors (SSs) are nonlinear dynamical models, often adopted in industrial environments, to perform the prediction of process variables based on their relation with easily accessible ones [2]. SSs allow implementing real-time control and monitoring of the plants, measuring system back-up, what-if analysis, sensor validation and fault diagnosis, presenting several advantages in terms of costs and efforts. They are, for instance, necessary when some variables cannot be measured online due to the lack of ad-hoc instruments or because of hostile environments.

关键词： Measurement Statistical analysis Soft sensors Instruments Neural engineering Predictive models Metrology

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LightDiC: A Simple yet Effective Approach for Large-scale Digraph Representation Learning 50th

LightDiC: A Simple yet Effective Approach for Large-scale Di...

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50th International conference on Very Large data Bases, VLDB 2024

作者： Li, Xunkai Liao, Meihao Wu, Zhengyu Su, Daohan Zhang, Wentao Li, Rong-Hua Wang, Guoren Beijing Institute of Technology China Peking University National Engineering Laboratory for Big Data Analytics and Applications China

Most existing graph neural networks (GNNs) are limited to undirected graphs, whose restricted scope of the captured relational information hinders their expressive capabilities and deployment. Compared with undirected graphs, directed graphs (digraphs) fit the demand for modeling more complex topological systems by capturing more intricate relationships between nodes. While some directed GNNs have been introduced, their inspiration mainly comes from deep learning architectures, which lead to redundant complexity and computation, making them inapplicable to large-scale databases. To address these issues, we propose LightDiC, a scalable variant of the digraph convolution based on the magnetic Laplacian. Since topology-related computations are conducted solely during offline pre-processing, LightDiC achieves exceptional scalability, enabling downstream predictions to be trained separately without incurring recursive computational costs. Theoretical analysis shows that LightDiC achieves message passing based on the complex field, which corresponds to the proximal gradient descent process of the Dirichlet energy optimization function from the perspective of digraph signal denoising, ensuring its expressiveness. Experimental results demonstrate that LightDiC performs comparably well or even outperforms other SOTA methods in various downstream tasks, with fewer learnable parameters and higher efficiency. © 2024, VLDB Endowment. All rights reserved.

关键词： Directed graphs

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Characteristics of Grey Active Disturbance Rejection control Based System Information 41

Characteristics of Grey Active Disturbance Rejection Control...

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第41届中国控制会议

作者： Ruiqing Zhang Zhibin He Huijiao Yao Wenke Liu School of Mechanical and Electrical Engineering Hebei Agricultural University Hebei Provincial Animal Husbandry Station

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Active disturbance rejection control(ADRC) with independent model has been paid much attention in academic fields and industrial process and other ***,with the information technique development,numerable data of the concerned system has been obtained,how to use the information to get more effective performance in ADRC is hot topic in research colleges and engineering *** paper discussed the adding the information method in linear active disturbance rejection control(LADRC) for a class of motion control systems,and gives two methods of using the known modeling *** system transfer functions of loop gain and control sensitivity with known modeling information are *** proposed methods are used to a mass-spring-damper system for simulation tests and frequency domain *** results show the effectiveness of the proposed method and reduction in energy consumption,the bandwidth and stability margins of loop gain response are changed little as the plant parameter vary significantly,so is the sensitivity to input disturbance and the output *** of this indicates that Grey LADRC has a strong robustness against the large variation of parameters in the plant.

关键词： Characteristics of Gray ADRC Information utilization Transfer functions of loop gain Frequency analysis

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