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Advances in Data-Driven Analytics And Intelligent Systems (ADACIS), IEEE International Conference on

作者： Hajer Chlif Dalel Kanzari Yosra Ben Said Dept. Prince Higher Institute of Computer Science and Communication Techniques of Hammam Sousse (ISITCom or Infcom) Sousse Tunisia Research Decision and Process Control Laboratory (LARODEC) Higher Institute of Management Tunisia Tunisia Tunisia Faculty of Economic Sciences and Management SFAX Tunisia

Over the past few years, there has been a notable surge in interest towards cryptocurrency, especially in the context of the crisis, where researchers have been diligently examining the influence of the coronavirus on cryptocurrency *** studies have utilized econometric and machine learning techniques to forecast cryptocurrency prices, but most of them have focused solely on the financial domain. This paper introduces a novel approach called ANFPC (Adaptive Neuro Fuzzy Prediction Cryptocurrency), which combines insights from both the financial and health domains to predict the price fluctuations of various cryptocurrencies such as bitcoin, ethereum, cardano, xpr, and dogecoin. The approach relies on the ANFIS Model, a fusion of fuzzy logic and artificial neural network (ANN).The experimental findings demonstrate that ANFPC provides accurate predictions, as measured by metrics like Mae and Mse, outperforming traditional ANN and LSTM methods. This approach proves to be a valuable decision support tool for data analysts in the realm of cryptocurrency prediction.

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An optimization-based algorithm for simultaneous shaping of poles and zeros for non-collocated vibration suppression

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IFAC-PapersOnLine 2022年第16期55卷 394-399页

作者： Adrian Saldanha Haik Silm Wim Michiels Tomáš Vyhlídal Department of Computer Science KU Leuven Celestijnenlaan 200A 3001 Leuven Belgium Dept. Instrumentation and Control Engineering Faculty of Mechanical Engineering and Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6 Czechia

This article presents a control design method for simultaneous shaping of the poles and zeros of linear time-invariant systems, motivated by the application of non-collocated vibration suppression to flexible multi-body systems. An entire suppression of vibrations at a target mass for a given excitation frequencies can be recast into the problem of assigning zeros of the transfer function from the excitation force to the target mass' position. The design requirement of achieving sufficient damping in the closed loop system combined with suppressing vibrations at the target, leads to the minimization of the spectral abscissa function of the closed loop system as a function of the controller parameters, subject to zero location constraints. These constraints exhibit polynomial dependence on the controller parameters. We present two approaches to solve the optimization problem which are both based on constraint elimination followed by application of an algorithm for non-smooth unconstrained optimization. The design approach is applicable to delay-free models as well as time-delay models of retarded and neutral type. Simulations results illustrate its applicability to a spring-mass-damper system.

关键词： vibration suppression zero placement time-delay systems spectral optimization

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MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects

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computer Methods and Programs in Biomedicine Update 2025年 7卷

作者： Lofù, Domenico Sorino, Paolo Colafiglio, Tommaso Bonfiglio, Caterina Donghia, Rossella Giannelli, Gianluigi Lombardi, Angela Di Noia, Tommaso Di Sciascio, Eugenio Narducci, Fedelucio Dept. of Electrical and Information Engineering (DEI) Politecnico di Bari BA Bari 70125 Italy Dept. of Computer Automatic and Management Engineering (DIAG) Sapienza Università di Roma RM Roma 00185 Italy Unit of Data Science National Institute of Gastroenterology ”Saverio de Bellis” IRCCS Hospital BA Castellana Grotte 70013 Italy Scientific Direction National Institute of Gastroenterology ”Saverio de Bellis” IRCCS Hospital BA Castellana Grotte 70013 Italy

Metabolic dysfunction-associated fatty liver disease (MAFLD) introduces new diagnostic criteria for fatty liver disease that are independent of alcohol consumption and viral hepatitis infection. Therefore, investigating how biochemical and anthropometric factors influence mortality in MAFLD subjects is of significant interest. In this work, we propose MORIX, an Artificial Intelligence-based framework capable of predicting fatal mortality outcomes in subjects with MAFLD. MORIX utilizes data from epidemiological datasets containing carefully selected anthropometric and biochemical information. This selection is achieved through Recursive Feature Elimination (RFE) using a Random Forest (RF) to train Machine Learning (ML) algorithms and provide a mortality risk (Yes/No) output. To provide physicians with a valuable tool, MORIX was trained and tested on a dataset of MAFLD subjects, comparing five different models: Random Forest (RF), eXtreme Gradient Boosting (XGB), Support Vector Machine (SVM), Multilayer Perceptron (MLP), and Light Gradient Boosting Model (LGBM) in a 5-fold cross-validation training strategy. Experimental results identified the RF as the best model, achieving a high accuracy for both mortality risks predicted. Additionally, an eXplainable Artificial Intelligence (XAI) analysis was conducted to clarify the diagnostic logic of the RF model and to assess the impact of each feature to the prediction. Moreover, a web application was developed to predict mortality risk and provide explanations of how the input features influenced the final prediction. In conclusion, the MORIX framework is easy to apply, and the required parameters are readily available in healthcare datasets, making it a practical tool for medical professionals. © 2025 The Authors

关键词： Epidemiology Interpretability Machine learning techniques MAFLD Mortality

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Trajectory Tracking for the Quadcopter UAV utilizing Fuzzy PID control Approach

Trajectory Tracking for the Quadcopter UAV utilizing Fuzzy P...

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2020 International Conference on computer, control, Electrical, and Electronics Engineering, ICCCEEE 2020

作者： Eltayeb, Ahmed Rahmat, Mohd Fuaad Eltoum, M. A Mohammed Ibrahim, M. H. Sanhoury Basri, Mohd Ariffanan Mohd Universiti Teknologi Malaysia School of Electrical Engineering Faculty of Engineering Skudai Johor1310 Malaysia Kfupm University Faculty of Computer Science and Engineering System Engineering Dept Dhahran31261 Saudi Arabia Alneelain University College of Engineering Dept. of Control Engineering Khartoum Sudan

ISBN: (纸本)9781728191119

Currently, the quadcopter Unmanned Aerial Vehicles (UAVs) are playing a significant role in combating the COVID-19 pandemic crisis, which induced the researchers to design robust control techniques. In this paper, a fuzzy PID controller is designed to stabilize and/or track the desired trajectory of the quadcopter UAV. The mathematical model of the quadcopter UAV has been briefly presented, where it has been divided into two portions, the position dynamic and the attitude dynamic subsystems. Subsequently, a robust fuzzy PID controller has been designed for both the inner loop and outer loop to control and stabilize the position and the attitude of the quadcopter, which adaptively manipulate the system's input based on the tracking error. The proposed controller is benchmarked with the conventional PID controller to show the robustness of the fuzzy PID controller. Fuzzy PID controller has been verified through simulation work utilizing Matlab/Simulink, where better performance is achieved compared with the conventional PID controller. It is found that the errors in the quadcopter's attitude and position have been significantly reduced through using fuzzy PID controller by 70% and 87%, respectively. © 2021 IEEE.

关键词： Simulink

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Study of the Influence of Rolling Modes on the Operation of Interconnected Electric Drives of a Rolling Mill

Study of the Influence of Rolling Modes on the Operation of ...

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Advanced Technology (KhPIWeek), IEEE KhPI Week on

作者： Valerii Tytiuk Alexey Kalinin Valeriy Druzhinin Victor Busher Oleksii Chornyi Dmytro Halushko Department of Electromechanics Kryvyi Rih National University Kryvyi Rih Ukraine Department of Informative computer systems Abylkas Saginov Karaganda Technical University NPJSC Karaganda The Republic of Kazakhstan Department of Power Engineering Karaganda Industrial University NPJSC Temirtau The Republic of Kazakhstan Dept. of Electrical Engineering and Electronics National University “Odessa Maritime Academy” Odessa Ukraine Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrogradskyi National University Kremenchuk Ukraine Dept. of Electrical Engineering Ukrainian State University of Science and Technologies Dnipro Ukraine

The paper is devoted to study of the influence of rolling modes on the performance of powerful interconnected electric drives of a hot rolling mill under the action of an electromagnetic coupling circuit between the electric drives of the roughing and finishing groups. The action of the electromagnetic coupling circuit manifests itself in the form of the influence of impact loads of synchronous electric drives on the angular velocity of direct current electric drives of the finishing group of the mill. The parameters of the electromagnetic coupling circuit are determined by the power supply scheme and equipment parameters. Values of impact loads applied to a synchronous motor depend on the rolling process parameters, in particular, the chemical composition of the rolled steel and the temperature of the ingot. The paper presents the results of calculating the rolling power for various rolling mode parameters. Using mathematical modeling in Simulink, numerical estimates of the influence of rolling modes on the magnitude of the voltage drop in the power supply unit and the drop in the angular velocity of the electric drive of the finishing group were obtained on the example of a wide-strip hot rolling mill 1700 of ArcelorMittal Temirtau JSC.

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Dynamic Template Learning for Top-Level computer Management Using Bayesian Optimization

Dynamic Template Learning for Top-Level Computer Management ...

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Advancement in Electronics & Communication Engineering (AECE), International Conference on

作者： Rizgar R. Zebari Maryam Ghassan Majeed Mohammed Q. Mohammed Zahraa N. Abdulhussain Latifjon Kosimov Haider Alchilibi Computer Science Dept. Knowledge University Erbil Iraq Computer Engineer Department Al-Kunooze University College Basra Iraq Forensic sciences department Al-Esraa University College Baghdad Iraq National University of Science and Technology Dhi Qar Iraq Department of Education Quality Control Fergana Polytechnic Institute Fergana Uzbekistan Medical Laboratory Techniques Department Al-Farahidi University Baghdad Iraq

Computing system administration is a difficult undertaking, particularly in complicated and shifting situations. Classical static methods often fall short of efficiently adjusting for shifting circumstances. In this study, we offer Dynamic Template Learning (DTL), a new method for automating top-level administration of computers that makes use of Bayesian optimization. The aim is to employ continuous performance evaluation and user-defined optimizations targets to constantly alter the system's settings and utilization of resources. The DTL architecture includes a feedback process that continually gathers performance information, evaluates the condition of the entire system, and draws lessons from the past in order to make wise choices. To effectively simulate system behavior while investigating the setting space, Bayesian optimizations is used. In order to find the best layouts, DTL uses probability modelling and acquisition procedures to dynamically examine choices. We experimented on a modelled machine with various strain conditions to assess the efficacy of DTL. The findings show that DTL performs better than conventional static techniques in aspects of system sales, usage of resources, and environmental adaption. Finding near-optimal solutions and quickly scanning the set-up field are both largely dependent on the Bayesian optimizations element. Additionally, we illustrate possible uses in real-world computing settings and talk about the advantages and disadvantages of the DTL technique. DTL's flexibility and adaptability makes it appropriate for a variety of infrastructure, including dispersed systems, data centers, and cloud computing systems. Organizations may increase system effectiveness, decrease staff involvement, and improve success overall by automated managerial processes.

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Validation of a two-wheel vehicle model using Genetic Algorithm

Validation of a two-wheel vehicle model using Genetic Algori...

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International Symposium on Computational Intelligence and Informatics

作者： Attila Widner Balázs Varga Dániel Medgyesi Tamás Tettamanti Dept. of Control for Transportation and Vehicle Systems Budapest University of Technology and Economics Fac. of Transportation Engineering and Vehicle Engineering Budapest Hungary Dept. of Innovative Vehicles and Materials John von Neumann University GAMF Fac. of Engineering and Computer Science Kecskemét Hungary

ISBN: (纸本)9798350398830

Vehicle dynamics simulation is widely used in the automotive industry. The usability of each model depends on how well it can replicate the behaviour of the real vehicle. Each simulation model must go through a thorough investigation process- model validation- before use. Accordingly, the research introduces a comprehensive methodological framework for vehicle dynamics model validation using a sophisticated vehicle dynamics measurement system and a machine learning algorithm. The validation process of a two-wheel vehicle model (bicycle model) is presented where the authors’ previously proposed work is exploited as a base and further developed, i.e. by using a Genetic Algorithm (GA) the vehicle parameters (yaw inertia, axle cornering stiffness) are estimated in an automatized fashion.

关键词： Industries computer science Mechatronics Machine learning algorithms Computational modeling Vehicle dynamics Usability

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Direct data-driven LPV control of nonlinear systems: An experimental result

arXiv

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arXiv 2022年

作者： Verhoek, Chris Abbas, Hossam S. Tóth, Roland Control Systems Group Dept. of Electrical Engineering Eindhoven University of Technology Eindhoven5600MB Netherlands Institute for Electrical Engineering in Medicine Universität zu Lübeck Lübeck23558 Germany Systems and Control Lab Institute for Computer Science and Control Budapest1111 Hungary

We demonstrate that direct data-driven control of nonlinear systems can be successfully accomplished via a behavioral approach that builds on a Linear Parameter-Varying (LPV) system concept. An LPV data-driven representation is used as a surrogate LPV form of the data-driven representation of the original nonlinear system. The LPV data-driven control design that builds on this representation form uses only measurement data from the nonlinear system and a priori information on a scheduling map that can lead to an LPV embedding of the nonlinear system behavior. Efficiency of the proposed approach is demonstrated experimentally on a nonlinear unbalanced disc system showing for the first time in the literature that behavioral data-driven methods are capable to stabilize arbitrary forced equilibria of a real-world nonlinear system by the use of only 7 data points. © 2022, CC BY-NC-SA.

关键词： Nonlinear systems

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Analysis of Heart Rate Variability during the Performance of the Wim Hof Method in Healthy Subjects

Analysis of Heart Rate Variability during the Performance of...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Beatriz F. Giraldo Giraldo David Ferré López Jordi Solà-Soler CIBER de Bioingeniería Biomateriales y Nanomedicina (CIBER-BBN) Automatic Control Dept. (ESAII) the Barcelona East School of Engineering (EEBE) Universitat Politècnica de Catalunya (UPC) Institute for Bioengineering of Catalonia (IBEC) – The Barcelona Institute of Science and Technology Barcelona Spain Barcelona East School of Engineering (EEBE) Universitat Politècnica de Catalunya (UPC) Spain

Cardiorespiratory interaction is related to the heart rate variability (HRV) synchronized with respiration. These metrics help to comprehend the autonomic nervous system (ANS) functionality in cardiovascular mechanisms. In this work, we aim to study the HRV in healthy subjects aged 18-24 years during the breathing techniques based on deep breaths followed by apnoeas, developed by Wim Hof (WHM). The attributes of all participates have been treated as a group and therefore, separated by gender. A total of 11 intervals have been distinguished: starting of basal respiration (SRI = 1), controlled deep breaths (CDB = 3), long expiratory apnoea (LEA = 3), short inspiratory apnoea (SIA = 3) and ending with basal respiration again (FRI = 1). To strengthen the HRV knowledge extraction from these scenarios, time and frequency analysis is conducted. In general, breathing and apnoea intervals presented significant statistically differences (p < 0.05), heart rate (HR) mean between SRI and FRI (p < 0.001), RR variability of LEA intervals (p < 0.01), root mean square of RR intervals during CDB (p < 0.05), maximum high frequency (HF) peak amplitude between SRI and FRI (p = 0.016), and low frequency (LF) area for LEA intervals (p < 0.001). When performing the frequency analysis, it has been observed that the sympathetic nervous system (SNS) has a higher contribution in the apnoea intervals. In conclusion, the WHM method implementation seems to involve a decrease in the HR. Specific breathing techniques could help to control the body in different *** Relevance— The WHM seems to imply a decrease on HR. Furthermore, after the implementation of the WHM, women presented higher HRV.

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Economic Equilibrium with Random Transactions 2

Economic Equilibrium with Random Transactions

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2nd International Conference on control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2020

作者： Zhukova, Aleksandra Pospelov, Igor G. Moscow Institue of Physics and Technology Federal Research Center Computer Science and Control of Ras Dept. of Mathematical Modelling of Economic Systems Dept. of Mathematical Modelling of Complex Systems and Optimization Dept of Theoretical Economics Moscow Russia

ISBN: (纸本)9781728188409

This paper presents the advances in modelling the system of agents under the conditions of random transactions between them. We face certain challenges in this project which we would like to highlight in this presentation. The agents in the modelled system are a large number of consumers, a large number of producers and the bank as the intermediary. Consumers take loans from the bank to spend on consumption goods and producers borrow to make investment at random moments of time. The moments of time the agents deal form the Poisson flow. We present the approach to agents' optimal control problems by the Lagrange method instead of dynamic programming. This enables us obtaining the expressions for the optimal feedback control which appear to be linear in state variables. The solution to the optimal control problems are obtained using asymptotic methods assuming large frequency of transactions. Using the linearity of the agents' optimal control, we may aggregate description of agents, stock-flow consistent on the average. Instead of an ensemble of independent random transactions by agents, the description of the aggregate dynamics is deterministic. The system of equations for the aggregate dynamics is reduced to one equation. There are two cases of this equation, depending on the description of the bank. The equation has a specific form, its numerical analysis is challenging. We provide numerical results and discuss further directions of research. © 2020 IEEE.

关键词： Random processes

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