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检索条件"任意字段=International Conference on Complex Systems: Control and Modeling Problems"

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control of Chaos in Fractional Computer Virus Model

Control of Chaos in Fractional Computer Virus Model

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Computational Intelligence Approaches and Applications (ICCIAA), international conference on

作者： Jamal Oudetallah Imane Zouak Wasim Audeh Adel Ouannas Amina-Aicha Khennaoui Iqbal M. Batiha Shaher Momani Department of Mathematics University of Petra Amman Jordan Department of Mathematics and Informatics University of Larbi Ben M'hidi Oum El Bouaghi Algeria NTIC Faculty University of Constantine 2 Constantine Algeria Department of Mathematics Al Zaytoonah University of Jordan Amman Jordan Nonlinear Dynamics Research Center (NDRC) Ajman University Ajman UAE Department of Mathematics University of Jordan Amman Jordan

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

This paper investigates the control of fractional discrete computer virus model. By employing fractional-order difference equations, we capture the complex dynamics and long- term memory effects inherent in virus propagation. A novel control strategy is proposed to stabilize the system and suppress virus outbreaks. The stability analysis of the controlled system is conducted. Numerical simulations are presented to validate the effectiveness of the proposed control approach. The results underscore the importance of control in managing fractional-order systems and highlight its potential applications in cyber security and other fields requiring precise regulation of complex dynamics.

关键词： Computer viruses Computational modeling Difference equations Numerical simulation Stability analysis Regulation Mathematical models Numerical models control theory Viruses (medical)

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international conference on Applied Mathematics, modeling and Computational Science, AMMCS 2019

International Conference on Applied Mathematics, Modeling an...

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international conference on Applied Mathematics, modeling and Computational Science, AMMCS 2019

ISBN: (纸本)9783030635909

The proceedings contain 68 papers. The special focus in this conference is on Applied Mathematics, modeling and Computational Science. The topics include: Covering Large complex Networks by Cliques—A Sparse Matrix Approach;comparing Regularization Techniques Applied to a Perceptron;key Performance Indicators and Individual Factors on Penalty Kicks;sparse Covariance and Precision Random Design Regression;applying Neural Networks to a Fractal Inverse Problem;solving Parameter Identification problems using the Collage Distance and Entropy;mean-Square Stability of Stochastic System with Impulse and Unbounded Delay;BOLD.R: A Software Package to Interface with BOLD Through R;analysis of Cortical Spreading Depression in Brain with Multiscale Mathematical Models;spontaneous Symmetry-Breaking in Deterministic Queueing Models with Delayed Information;impulsive Consensus of complex-Valued Multi-agent systems with Hybrid Protocols;input-to-State Stability for Delayed Hybrid systems and H∞ control;impulsive Distance-Based Formation Tracking control of Multi-agent systems;exponential Stabilization for Markov Jump Neural Networks with Additive Time-Varying Delays via Event-Triggered Impulsive control;development of a Lattice Boltzmann Model for the Solution of Partial Differential Equations, A Performance Comparison Study with that of the Finite Difference Method;Using Shooting Approaches to Generate Initial Guesses for ODE Parameter Estimation;a Computational Study for Solving Inverse problems for Mixed Variational Equations on Perforated Domains;bacoli_py—A Python Package for the Error controlled Numerical Solution of 1D Time-Dependent PDEs;solving Cardiac Bidomain problems with B-spline Adaptive Collocation;a Computational Comparison of Three Methods for Solving a 1D Boundary Value Inverse Problem;algebraic Structure of the Varikon Box;approximating Dispersive Materials with Parameter Distributions in the Lorentz Model.

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Closed-Loop Predictive control for Adaptive Optics via Neural Networks

Closed-Loop Predictive Control for Adaptive Optics via Neura...

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IEEE international conference on systems, Man and Cybernetics

作者： Haining Hu Qianchong Sun Yuchen Hua Jie Tan Xiaoguang Ren Rongkai Zhang Xin Liu Academy of Military Sciences Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Wavefront sensor-less adaptive optics (WFS-less AO) systems have garnered considerable interest in recent years due to their compact architecture and extensive applicability. However, most algorithms developed for adaptive optics systems predominately rely on conventional control methodologies, which often take an unexpectedly prolonged period to converge and severely hinder the feasibility of practical applications, especially in scenarios where rapid environmental fluctuations necessitate real-time control capabilities. Therefore, we propose an efficient closed-loop wavefront reconstruction method based on a novel forward prediction paradigm. The method leverages information from the current control objective, the wavefront phase, and the previous control signals (typically the voltages applied to deformable mirrors) to predict wavefront distortions and implement anticipatory control actions accordingly. Experimental results demonstrate that, compared to most conventional techniques, our method can reduce the post-control RMS wavefront aberration by nearly one-third while exhibiting robustness to different types of turbulence and showing promising potential for complex multi-layer turbulence scenarios.

关键词： Atmospheric modeling Neural networks Optical distortion Predictive models Adaptive optics Robustness Delays Mirrors Voltage control Predictive control

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Distributed Urban Road Network Signal Coordination control Method Based on Game Theory and Multi-Agent Reinforcement Learning

Distributed Urban Road Network Signal Coordination Control M...

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Information systems and Computing Technology (ISCTech), international conference on

作者： Shuchen Liu Yaoxuan Feng Ningning Ren Shandong Institute of Commerce and Technology Jinan China Shandong University of Finance and Economics Jinan China

ISBN: (数字)9798350379860

ISBN: (纸本)9798350379877

In order to solve the problems of low efficiency and difficult practical application of the centralized method in the coordinated control of urban road network signals, this paper proposes a game-based multi-intersection cooperative control method. By constructing a distributed game model, the signal control between intersections is regarded as a game relationship, and the Nash equilibrium solution is solved by using a mixed strategy game, and the signal control strategies of each intersection are obtained. At the same time, combined with the multi-agent reinforcement learning framework, Nash Q-learning is used to update the benefit matrix to realize the learning strategy of the agent. Simulation results show that the proposed method can significantly reduce the average delay and waiting time under low traffic demand [1], and outperforms single-agent control under high traffic demand, effectively avoiding traffic congestion and reducing network delay.

关键词： Computers Q-learning Roads Simulation Computational modeling Games Nash equilibrium Delays Traffic congestion Information systems

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Representation of Power System Load control Instruments in the Unit Commitment Model with Cyclic Horizon of Forecasting 8

Representation of Power System Load Control Instruments in t...

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8th IEEE international conference on Energy Smart systems, ESS 2022

作者： Saukh, Sergii Borysenko, Andriy Pukhov Institute for Modelling in Energy Engineering Department of Mathematical and Econometric Modelling Kyiv Ukraine

ISBN: (数字)9798350334418

ISBN: (纸本)9798350399202

Well-known Unit Commitment (UC) models of loading generating units of power systems have a common feature: they are all determined on the basis of linear time, where there are past, current and future periods. UC models are 'tied' to the initial conditions and, therefore, cannot cover long-term forecasting horizon due to the excessive computational complexity of algorithms for solving model problems of large-scale integer programming. To eliminate such an insurmountable limitation in the application of UC models, the UC model of loading generating units on the cyclic forecasting horizon (UCC-model) is used. The UCC-model reproduces units loading modes on a cyclical weekly forecast horizon and does not require initial conditions, as it establishes a relationship between the states of generating units at the end and beginning of the forecast horizon. The UCC-model presents a detailed description of the operation of electricity storage systems, taking into account the placement of primary and secondary reserves. Comprehensive consideration of the maneuverability of traditional generation technologies in combination with energy storage systems and opportunities for participation of RES and consumers in load regulation significantly improve the quality of modeling modes of generating equipment in long-term development models. The use of the UCC-model in the tasks of long-term planning of generation development allows to adequately represent the modes of operation of generating equipment and the distribution of reserves in the power system. The use of the UCC-model in the tasks of short-term dispatch control of power systems allows reproducing the features of the distribution of reserves in the electricity storage systems, demand management and distributed generation. © 2022 IEEE.

关键词： Integer programming

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Power System Network Modelling to Predict Inter-area Low Frequency Oscillations

Power System Network Modelling to Predict Inter-area Low Fre...

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modeling, Simulation & Intelligent Computing (MoSICom), international conference on

作者： Hemang Thakkar Vengala Reddy Palleti Gomathi Bhavani Rajagopalan Energy Electrical Projects Emirates Global Aluminium Dubai United Arab Emirate Operations – Control Room Emirates Global Aluminium Dubai United Arab Emirate Department of Electrical and Electronics Engineering BITS Pilani Dubai Campus Dubai United Arab Emirate

ISBN: (数字)9798331533311

ISBN: (纸本)9798331533328

This paper highlights the importance of accurately modeling power system network elements and controls using analytical software tools to effectively predict underlying network security issues, particularly under stressed system *** major network events like faults, interconnection trips, bulk load disconnections, and large generating unit trips under normal operating conditions can be analyzed with predictable impacts on system security, occurrences like small signal stability or low frequency oscillations may get overlooked unless highly degraded network states are accurately predicted and modeled in the software. This is especially pertinent for large power systems with multiple nodes, multiple generation sources, and high-impedance interconnectors that create significant electrical distances between power system nodes. Similarly, modelling of accurate controls to be implemented as mitigation measures are crucial to ensure power system security from these undetected *** paper presents a case study using power system analysis software tool – Cyme for a large industrial power system network of an Aluminium smelter. The results of the study underscore the importance of precise network element modeling. The results indicate that using simplified data may not be able to highlight the real problems related to inter-area oscillations, while the same could be clearly detected by accurately modeling the systems representing the degraded state of network with tested control parameters. Such accurate modeling assists system operators in avoiding specific operational modes and aids control engineers in deriving optimal control parameters to meet network security requirements. Such accurate prediction of the underlying network issues immensely improves overall Security of Supply (SoS) of an industrial power system.

关键词： Analytical models Industrial power systems Accuracy Computational modeling Power system stability Predictive models Network security Software tools Oscillators Load modeling

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Dual Quaternion control of UAVs with Cable-suspended Load

Dual Quaternion Control of UAVs with Cable-suspended Load

引用

IEEE international conference on Robotics and Automation (ICRA)

作者： Yuxia Yuan Markus Ryll Autonomous Aerial Systems School of Engineering and Design Technical University of Munich Ottobrunn Germany Munich Institute of Robotics and Machine Intelligence (MIRMI) and Autonomous Aerial Systems School of Engineering and Design Technical University of Munich Ottobrunn Germany

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

modeling the kinematics and dynamics of robotics systems with suspended loads using dual quaternions has not been explored so far. This paper introduces a new innovative control strategy using dual quaternions for UAVs with cable-suspended loads, focusing on the sling load lifting and tracking problems. By utilizing the mathematical efficiency and compactness of dual quaternions, a unified representation of the UAV and its suspended load’s dynamics and kinematics is achieved, facilitating the realization of load lifting and trajectory tracking. The simulation results have tested the proposed strategy’s accuracy, efficiency, and robustness. This study makes a substantial contribution to present this novel control strategy that harnesses the benefits of dual quaternions for cargo UAVs. Our work also holds promise for inspiring future innovations in under-actuated systems control using dual quaternions.

关键词： Technological innovation Uncertainty Trajectory tracking Quaternions Simulation Kinematics Autonomous aerial vehicles

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Fast Probabilistic Policy Reuse via Reward Function Fitting

Fast Probabilistic Policy Reuse via Reward Function Fitting

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IEEE international conference on Fuzzy systems (FUZZ-IEEE) / IEEE World Congress on Computational Intelligence (IEEE WCCI) / international Joint conference on Neural Networks (IJCNN) / IEEE Congress on Evolutionary Computation (IEEE CEC)

作者： Liu, Jinmei Wang, Zhi Chen, Chunlin Nanjing Univ Dept Control & Syst Engn Nanjing Peoples R China

ISBN: (数字)9781728186719

ISBN: (纸本)9781728186719

Transfer learning has shown great potential to accelerate reinforcement learning (RL) by utilizing prior knowledge of relevant task that has been learned in the past. Policy Reuse Q-learning (PRQL) is a general policy transfer framework, which speeds up the learning process of the target task by probabilistically reusing source policies from the policy library. In this paper, we propose an improved PRQL method to achieve more fast probabilistic policy reuse in deep reinforcement learning (DRL). First, we extend the basic PRQL algorithm to DRL, proposing a probability policy reuse algorithm that builds on DRL to solve more complex problems. Second, PRQL algorithms usually use a metric based on the average gain to measure the similarity between tasks. However, it contains very limited information and must be delayed until the end of an episode to update, which is inefficient. Instead, we propose a new metric based on fitting the reward function, which can make the agent converge to the most suitable reuse policy more quickly and accurately. We demonstrate the detection accuracy, received cumulative reward, and speed of convergence of our method in three complex Markov tasks. Experimental results show that our method can consistently achieve efficient policy transfer in these tasks.

关键词： Q-learning Fitting Neural networks Transfer learning Markov processes Gain measurement Probabilistic logic

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Revealing attributes of an object based on incomplete and inconsistent empirical data 8

Revealing attributes of an object based on incomplete and in...

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8th international conference on Information Technology and Nanotechnology, ITNT 2022

作者： Semenova, Valentina Smirnov, Sergei Laboratory for Analysis and Modeling of Complex Systems Samara Federal Research Scientific Center RAS Institute for the Control of Complex Systems RAS Samara Russia

ISBN: (数字)9781665485715

ISBN: (纸本)9781665485715

The paper considers the problem of building a semantic model of the object under study, which determines its attributes, *** composition of the properties inherent in the object. The set of these attributes is a subset of all measured (in a broad sense) properties of the object under study. Processing the results of such multidimensional measurements, observations, registration of expert opinions, etc. gives the initial empirical material in the form of generally logically many-valued assessments of judgments truth of the form 'the property x is inherent in the object g'. On the other hand, the subject may have a priori knowledge about the coexistence variants of various attributes in the object under study. For such circumstances, a method is proposed for identifying all admissible sets of object attributes, including a logical-combinatorial method for choosing the 'best' of these sets, which is taken as a semantic model of the object. The paper considers examples of applications of the developed models and methods, indicates the tasks of additional research of the problem to substantiate the proposed methodology for the semantic identification of an object based on empirical data. © 2022 IEEE.

关键词： Semantics

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Isolated zones and granulation of complex network systems 12

Isolated zones and granulation of complex network systems

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12th IEEE international conference on Electronics and Information Technologies, ELIT 2021

作者： Polishchuk, Olexandr Laboratory of Modeling and Optimization of Complex Systems Pidstryhach Institute for Applied Problems of Mechanics and Mathematics National Academy of Sciences of Ukraine Lviv Ukraine

ISBN: (纸本)9781665442961

The problem of blocking certain areas of network systems and their boundary case, which is the granulation of network to a set of isolated zones, is investigated in the article. The losses that await the system due to blocking of its separate components are determined, and method for finding alternative ways of flow motion bypassing the isolated zone of network are proposed. The granulation process of the network system is reflected as a temporal network and the losses that await the system during the deployment of such processes are calculated. © 2021 IEEE.

关键词： complex networks

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