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Analyzing the Influence of Measurements in Dynamical Parameter Identification Using Parametric Sensitivities

IFAC-PapersOnLine 2021年第14期54卷 7-12页

作者： M. Wiesner K. Schäfer W. Bergmann A. Berger P. Shulpyakov C. Dittert C. Büskens Optimization and Optimal Control Center for Industrial Mathematics University of Bremen 28359 Bremen Germany

In many modern applications, a central task is to model a dynamical behavior with ordinary differential equations. A common way to identify parameters within such a model is to fit its output against given measurements. Since it can be difficult to understand the connection between measurements and the parameter identification result, it is desirable to develop methods for analyzing this aspect. In this paper, we show how information from parametric sensitivity analysis can be used to gain a better insight into the impact of certain measurement regions on the identified model parameters. We parameterize the measurements by a B-spline regression and formulate the task of parameter identification using a collocation approach. In the resulting nonlinear optimization problem, we consider the B-spline coefficients as perturbation parameters. Next, we identify the model parameters and compute their parametric sensitivities with respect to these perturbations. In a final step, we evaluate a newly developed measure to characterize the desired influence. The corresponding optimization problems are solved with the nonlinear programming solver WORHP in combination with its integrated module WORHP Zen, which computes the required parametric sensitivities efficiently. We demonstrate the proposed approach by applying it to the example of parameter identification of a driving car.

关键词： Modeling Identification Identification for control Nonlinear system identification Input design Parametric sensitivity analysis Nonlinear optimization

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Forming Circle Formations of Multi-agent Systems Under Actuator Faults 5th

Forming Circle Formations of Multi-agent Systems Under Actu...

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5th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2021

作者： Liu, Jiajun Ru, Xinfeng Xia, Weiguo Wang, Chen China National Aeronautical Radio Electronic Research Institute and National Key Laboratory of Science and Technology on Avionics System Integration Shanghai China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and School of Control Science and Engineering Dalian University of Technology Dalian China National Engineering Research Center of Software Engineering and the State Key Laboratory of Turbulence and Complex Systems Intelligent Biomimetic Design Lab College of Engineering Peking University Beijing China

ISBN: (纸本)9789811939976

A distributed fault-tolerant formation control law is designed in this paper for multi-agent systems under external disturbances and actuator faults including time-varying loss of effectiveness faults. The initial position of each agent is already on a circle and the control purpose is to form a desired formation on this circle. Based on this local information, a distributed adaptive formation control law is designed by employing the congelation of variables method to deal with time-varying actuator faults. Finally, a simulation example is given to verify the effectiveness of the adaptive fault-tolerant control design method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Multi agent systems

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Direct Vehicle-to-Vehicle Energy Trading with Online Charging-Hailings: A Novel Business Model for Emergency Charging of Electric Vehicles

SSRN

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SSRN 2024年

作者： Wang, Rui Jiang, Aihua Tian, Junyang Wang, Yifeng Guangxi Key Laboratory of Power System Optimization and Energy Saving Technology Guangxi University Guangxi Province Nanning530004 China Power Dispatching Control Center of Guangxi Power Grid Guangxi Province Nanning530023 China

Amid the escalating number of Electric Vehicles (EVs), the current infrastructure of public charging stations is ill-equipped to handle the mass charging demands of these vehicles, leading to a pressing issue of range anxiety that necessitates immediate resolution within the EV industry. This paper integrates the operating model of Online Ride-Hailings with the direct Vehicle-to-Vehicle (V2V) energy trading model, introducing a novel business model with Online Charging-Hailings (OCHs). This model positions OCHs as the principal energy providers and targets EV users as the primary service recipients aiming to furnish EV users with emergency energy supply services through V2V interactions. The architecture underpinning this model is a cloud-edge-end collaborative framework designed for the operational service platform. It employs the Gale-Shapley matching game algorithm and takes user satisfaction into account to establish an order-taking mechanism. Furthermore, the model utilizes a Vehicle-to-Grid technology and a Demand Response strategy to develop a charging optimization mechanism tailored for OCHs. Under this framework, EV users can simply send a charging request via their mobile devices to reserve V2V charging services. Simulation outcomes suggest that the proposed business model effectively facilitates emergency charging for EVs, mitigates range anxiety for users, lowers charging costs for OCHs, and enhances operator profitability, making it suitable for large-scale applications. © 2024, The Authors. All rights reserved.

关键词： Emergency services

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Prediction of recurrent venous thromboembolism using a spatiotemporal phenomenological model and artificial neural network

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Neural Computing and Applications 2025年第15期37卷 9193-9221页

作者： Al Bannoud, Mohamad Martins, Tiago Dias de Lima Montalvão, Silmara Aparecida Annichino-Bizzacchi, Joyce Maria Filho, Rubens Maciel Maciel, Maria Regina Wolf School of Chemical Engineering Laboratory of Optimization Design and Advanced Control Universidade Estadual de Campinas São Paulo Campinas Brazil Departamento de Engenharia Química Instituto de Ciências Ambientais Químicas e Farmacêuticas Universidade Federal de São Paulo São Paulo Diadema Brazil Hematology and Hemotherapy Center University of Campinas/Hemocentro-Unicamp Instituto Nacional de Ciência E Tecnologia Do Sangue São Paulo Campinas Brazil Universidade Estadual de Campinas São Paulo Campinas Brazil

Venous thromboembolism (VTE) is a major global cause of death, with recurrence risk rising after inadequate treatment. Existing VTE recurrence prediction models often overlook the phenomenological aspects of blood clot formation. This study aimed to predict Recurrent VTE (RVTE) by combining an artificial neural network (ANN) with a phenomenological clot formation model. A spatiotemporal model of clot formation was proposed and simulated using hematological data from 235 patients. Principal component analysis (PCA) and partial least squares (PLS) regression were applied to reduce the number of significant variables, and multiple ANN structures were trained for RVTE predictions. The dataset was initially divided into training and validation subsets to avoid data leakage. No data from the validation subset was used to build the model, ensuring the model's integrity. The validation conducted in this study corroborates the model's good generalizability. The spatiotemporal model effectively differentiated patients based on clot formation characteristics. The application of PCA and PLS reduced the original variables by over 99.99%. The best-performing model achieved, for unseen observations, an area under curve of 0.9689, accuracy of 0.9149, sensitivity of 1.0000, specificity of 0.8919, and F1-score of 0.8333, aligning with established literature values. This methodology outperformed nine other machine learning models commonly used for binary classification. A significant advantage of this approach is its reliance on only six clinical variables for prediction. This study demonstrates that mathematical methods can reveal insights into the spatiotemporal evolution of blood clots, presenting a promising avenue for RVTE prediction. The model could serve as a clinical decision-support system for RVTE treatment. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Prediction models

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Who should I trust? A Visual Analytics Approach for Comparing Net Load Forecasting Models

arXiv

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arXiv 2024年

作者： Bhattacharjee, Kaustav Kundu, Soumya Chakraborty, Indrasis Dasgupta, Aritra Department of Data Science New Jersey Institute of Technology United States Optimization and Control Group Pacific Northwest National Laboratory United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory United States

Net load forecasting is crucial for energy planning and facilitating informed decision-making regarding trade and load distributions. However, evaluating forecasting models' performance against benchmark models remains challenging, thereby impeding experts' trust in the model's performance. In this context, there is a demand for technological interventions that allow scientists to compare models across various timeframes and solar penetration levels. This paper introduces a visual analytics-based application designed to compare the performance of deep-learning-based net load forecasting models with other models for probabilistic net load forecasting. This application employs carefully selected visual analytic interventions, enabling users to discern differences in model performance across different solar penetration levels, dataset resolutions, and hours of the day over multiple months. We also present observations made using our application through a case study, demonstrating the effectiveness of visualizations in aiding scientists in making informed decisions and enhancing trust in net load forecasting models. © 2024, CC BY-NC-SA.

关键词： Visual analytics

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Integrating biomarkers for hemostatic disorders into computational models of blood clot formation: A systematic review

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Mathematical Biosciences and Engineering 2024年第12期21卷 7707-7739页

作者： Bannoud, Mohamad Al Martins, Tiago Dias Montalvão, Silmara Aparecida de Lima Annichino-Bizzacchi, Joyce Maria Filho, Rubens Maciel Maciel, Maria Regina Wolf Laboratory of Optimization Design and Advanced Control School of Chemical Engineering Universidade Estadual de Campinas Campinas São Paulo Brazil Departamento de Engenharia Química Universidade Federal de São Paulo Diadema São Paulo Brazil Hematology and Hemotherapy Center Instituto Nacional de Ciência e Tecnologia do Sangue Universidade Estadual de Campinas Campinas São Paulo Brazil Centro de Doenças Tromboembólicas Centro de Hematologia e Hemoterapia Universidade Estadual de Campinas Campinas São Paulo Brazil

In the pursuit of personalized medicine, there is a growing demand for computational models with parameters that are easily obtainable to accelerate the development of potential solutions. Blood tests, owing to their affordability, accessibility, and routine use in healthcare, offer valuable biomarkers for assessing hemostatic balance in thrombotic and bleeding disorders. Incorporating these biomarkers into computational models of blood coagulation is crucial for creating patient-specific models, which allow for the analysis of the influence of these biomarkers on clot formation. This systematic review aims to examine how clinically relevant biomarkers are integrated into computational models of blood clot formation, thereby advancing discussions on integration methodologies, identifying current gaps, and recommending future research directions. A systematic review was conducted following the PRISMA protocol, focusing on ten clinically significant biomarkers associated with hemostatic disorders: D-dimer, fibrinogen, Von Willebrand factor, factor VIII, P-selectin, prothrombin time (PT), activated partial thromboplastin time (APTT), antithrombin III, protein C, and protein S. By utilizing this set of biomarkers, this review underscores their integration into computational models and emphasizes their integration in the context of venous thromboembolism and hemophilia. Eligibility criteria included mathematical models of thrombin generation, blood clotting, or fibrin formation under flow, incorporating at least one of these biomarkers. A total of 53 articles were included in this review. Results indicate that commonly used biomarkers such as D-dimer, PT, and APTT are rarely and superficially integrated into computational blood coagulation models. Additionally, the kinetic parameters governing the dynamics of blood clot formation demonstrated significant variability across studies, with discrepancies of up to 1,000-fold. This review highlights a critical gap in the avail

关键词： Coagulation

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Combining Transformer and Convolutional Neural Network for Smoke Detection 9th

Combining Transformer and Convolutional Neural Network for...

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9th International Forum on Digital Multimedia Communication, IFTC 2022

作者： Gong, Yafei Lian, Xinkang Ma, Xuanchao Xia, Zhifang Zhou, Chengxu Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Laboratory of Smart Environmental Protection Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China National Information Center Beijing China School of Electronic and Information Engineering Liaoning University of Technology Liaoning Jinzhou China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China

ISBN: (纸本)9789819908554

Smoke detection plays a crucial role in the safety production of petrochemical enterprises and fire prevention. Image-based machine learning and deep learning methods have been widely studied. Recently, many works have applied the transformer to solve problems faced by computer vision tasks (such as classification and object detection). To our knowledge, there are few studies using the transformer structure to detect smoke. In order to research the application potential and improve the performance of the transformer in the smoke detection field, we propose a model consisting of two transformer encoders and a convolutional neural network (CNN) module. The first transformer encoder can be used to establish the global relationship of an image, and the CNN structure can provide additional local information to the transformer. The fusion of global information and local information is conducive to the second transfer encoder to make better decisions. Experiments results on large-size dataset for industrial smoke detection illustrate the effectiveness of the proposed model. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Smoke

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Models of Battle Dynamics in Strategic Computer Games 16

Models of Battle Dynamics in Strategic Computer Games

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16th International Conference Management of Large-Scale System Development, MLSD 2023

作者： Laryushin, Ivan Dmitrievich Pashin, Dmitrii Sergeevich Koltochenko, Yaroslav Alekseevich Ereshko, Felix Ivanovich Gaponov-Grekhov Institute of Applied Physics Ras Plasma Physics Department Nizhny Novgorod Russia State University of Nizhny Novgorod Faculty of Physics National Research Lobachevsky Nizhny Novgorod Russia Moscow Institute of Physics and Technology Department of Mathematical Modeling of Complex Systems and Optimization Moscow Russia Federal Research Center 'Computer Science and Control' of the Ras Department of Information and Computing Systems Moscow Russia

ISBN: (纸本)9798350337907

A set of new models that describe the dynamics of battles in strategic computer games is presented. These models not only have descriptive functions, but also allow solving problems of optimizing army control under given conditions, as well as calculating the most efficient composition of the army for the planned operation within a computer game. © 2023 IEEE.

关键词： Computer games

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Few-Reference Image Quality Assessment with Multiple Information Measurement Fusion 9th

Few-Reference Image Quality Assessment with Multiple Inform...

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9th International Forum on Digital Multimedia Communication, IFTC 2022

作者： Shi, Shuang Wang, Simeng Liu, Yuchen Zhou, Chengxu Gu, Ke Faculty of Information Technology Beijing University of Technology Beijing China Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing China Beijing Laboratory of Smart Environmental Protection Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China Beijing Artificial Intelligence Institute Beijing China School of Electronic and Information Engineering Liaoning University of Technology Liaoning Jinzhou China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China

ISBN: (纸本)9789819908554

In the era of media information explosion, there is an urgent need for a fast and reliable image quality assessment (IQA) model to improve the actual application effect of images. To this end, we propose the multiple information measurement fusion metric (MMFM), which innovatively combines two types of information measures (IMs), i.e., local IM and global IM, using only a small number of references for IQA. First, inspired by the free energy theory, we combine 2-dimensional autoregressive model with sparse random sampling method as an inference engine on an input image to generate its associated predicted image. Second, by the inspiration of pixel-wise measurement, we obtain the local IM by calculating the information entropy of the residual error between the input image and its corresponding predicted one. Third, motivated by the histogram-based measurement, we acquire the global IM by computing the two kinds of divergences between the input image and its predicted one. Fourth, we systematically fuse three components, independently including one distance of local IM between the reference and corrupted images and two distances of global IMs between the reference and corrupted images, based on a linear function to derive the final IQA result. The results of experiment on the most popular LIVE database show that our designed algorithm with only one number used as few reference has achieved well performance as compared with several mainstream IQA models. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image enhancement

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Finite-time control for a class of hybrid systems via quantized intermittent control

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Science China(Information Sciences) 2020年第9期63卷 140-155页

作者： Xiaolin XIONG Xinsong YANG Jinde CAO Rongqiang TANG Cunjin College Guangdong Ocean University School of Mathematical Sciences Chongqing Normal University Key Laboratory of Optimization and Control Ministry of Education School of Mathematics and Research Center for Complex Systems and Network SciencesSoutheast University

This paper considers the finite-time drive-response synchronization of stochastic nonlinear systems consisting of continuous-time and discrete-time subsystems. To save communication resources and reduce control cost, quantized controllers, which only work on continuous-time intervals, are designed. Owing to the hybrid characteristics of continuous-and discrete-time subsystems, existing finite-time stability theorems are not applicable. By developing novel analytical techniques, three criteria are derived to guarantee the finite-time synchronization. Moreover, the settling time is explicitly estimated. It is shown that the settling time is dependent not only on the control gains and systems’ initial conditions, but also on the control width and uncontrolled width. Numerical examples demonstrate the effectiveness of the theoretical analysis.

关键词： hybrid system finite-time synchronization quantized intermittent control stochastic perturbation

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