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15th International Conference on Optimization and Applications, OPTIMA 2024

作者： Gornov, Alexander Anikin, Anton Sorokovikov, Pavel Zarodnyuk, Tatiana Matrosov Institute for System Dynamics and Control Theory of SB RAS Lermontov Str. 134 Irkutsk664033 Russia

ISBN: (纸本)9783031791185

The article discusses a novel approach for optimizing atomic-molecular structures in extra-large clusters, focusing on reducing computational complexity and applying parallel computing techniques. A three-stage computation process is outlined, offering benefits over traditional algorithms by efficiently navigating through multi-extremal optimization challenges. The software, based on this methodology, demonstrated high efficacy in solving complex molecular dynamics problems. When comparing the outcomes with experimental data, no significant deviations from the expected patterns in potential values were detected. The developed three-stage numerical approach proved instrumental in solving optimization tasks for extra-large atomic-molecular systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Molecular dynamics

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Numerical Investigation of the Swarm Intelligence Algorithm Obtained Using ChatGPT for Univariate Global Optimization 23rd

Numerical Investigation of the Swarm Intelligence Algorithm ...

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23rd International Conference on Mathematical Optimization theory and Operations Research, MOTOR 2024

作者： Sorokovikov, Pavel Gornov, Alexander Zarodnyuk, Tatiana Matrosov Institute for System Dynamics and Control Theory of SB RAS Lermontov Str. 134 Irkutsk664033 Russia

ISBN: (纸本)9783031733642

This paper explores the possibility of designing an efficient global optimization algorithm using an artificial intelligence chatbot, ChatGPT. The main idea is to use the swarm intelligence metaheuristic method, which operates on a set of particles in a swarm, to solve non-local univariate search problems. Testing was carried out on a set of one-dimensional non-convex functions with varying numbers of local optima. The results demonstrate that this algorithm can be used to solve multi-extremal optimization problems. The paper presents the results of a numerical study on the properties of this algorithm in comparison with the Piyavsky method, the Strongin method, and a combination of the Strongin with the Parabolas methods. The performed computational experiments testify to the suitability of the obtained swarm intelligence algorithm for solving univariate non-local search problems. This approach can also be useful for solving auxiliary optimization problems and for developing multimethod computational technologies. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Optimization algorithms

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On the Qualitative Analysis of the Equations of Motion of a Rigid Body in a Magnetic Field

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Journal of Applied and Industrial Mathematics 2022年第1期16卷 58-69页

作者： Irtegov, V.D. Titorenko, T.N. Matrosov Institute for System Dynamics and Control Theory Siberian BranchRussian Academy of Sciences Irkutsk664033 Russia

Abstract: In the problem on the motion of a rigid body with a fixed point under the influence of amagnetic field generated by the Barnett–London effect as well as potential forces, the particularcases of existence of additional quadratic integrals are presented and the qualitative analysis of theequations of motion of the body is carried out in one of these cases. © 2022, Pleiades Publishing, Ltd.

关键词： Equations of motion

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How To Classify Document Segments Using Graph Based Representation and Neural Networks

How To Classify Document Segments Using Graph Based Represen...

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2024 Ivannikov Memorial Workshop, IVMEM 2024

作者： Kopylov, Daniil Mikhaylov, Andrey Matrosov Institute for System Dynamics and Control Theory of Siberian Branch of the Russian Academy of Sciences Irkutsk Russia Ivannikov Institute for System Programming of the Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9798331504663

Bottom-up segmentation approaches, where words are combined into lines, lines into paragraphs, etc., are well-known nowadays. In this work, we use this principle for classification of segments. The features of the blocks that make up a segment and their relationships can be sufficient for classification. Our approach combines a specific choice of features that increases explainability by employing the generalizing ability of neural networks. This work presents an intermediate result, but, nevertheless, the 0.793 classification accuracy on the part of PubLayNet indicates the competitive potential of the approach. It is expected that, similar to the transition from MLP to CNN for MNIST, the transition from vector representation at our stage to GCN at the planned stage will allow us to achieve good results in document classification. © 2024 IEEE.

关键词： Graph neural networks

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Towards knowledge-based virtual assistant development with the aid of ontology transformations

Towards knowledge-based virtual assistant development with t...

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2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2022

作者： Dorodnykh, Nikita O. Nikolaychuk, Olga A. Stolbov, Aleksandr B. Yurin, Aleksandr Yu. Matrosov Institute for System Dynamics and Control Theory Irkutsk Russia

ISBN: (纸本)9781665464802

One of the challenges for the popularization of knowledge-based systems (KBS) is to be more user-friendly and involved in solving everyday tasks. A way to encourage users to apply KBSs more actively is the use of up-to-date achievements in the field of human-machine communication, in particular a special type of intelligent systems-virtual assistants. In this paper we present the roadmap ideas for proper upgradation of the Prototyping Expert systems based On Transformations (PESoT) technique for the virtual assistant facilities. This technique involves the use and transformation of conceptual models and ontologies for creating software and source codes. In this paper, we present computation-and platform-independent models (ontology of the dialog model, ontology for the Aimylogic tool) as well as correspondence examples for transformation implementation. © 2022 IEEE.

关键词： Ontology

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Software for Urban Space Researching with Public Data for Irkutsk 7th

Software for Urban Space Researching with Public Data for Ir...

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7th Computational Methods in systems and Software, CoMeSySo 2023

作者： Nikolaychuk, O.A. Kosogorov, D.E. Pestova, Yu. V. Matrosov Institute for System Dynamics and Control Theory of Siberian Branch of Russian Academy of Sciences Irkutsk Russia Irkutsk State University Irkutsk Russia

ISBN: (纸本)9783031535512

The research of urban space can help in city management by identifying patterns in the development of the city and finding the strengths and weaknesses of individual places and entire areas. The purpose of this work is to create a software (tool) for research. Data for the tool is gathered from open Internet data sources using parsing methods. After the gathering data is processed, the values are normalized, the current indicators are calculated, and reviews are analyzed with sentiment analysis methods. The processing results are provided to the user in the form of interactive dashboards that combine visualizations necessary for work. This tool can be used not only by people involved in urban space management but also by tourists to get a clear picture of which places are more popular and which ones are the best to visit based on their queries. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Attractors Data Gathering Data Normalization Data Visualization Sentiment Analysis

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Monowave Boundary Construction Method for the Non-convex Reachable Set of the controlled Dynamical system 1

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7th International Conference on Optimization, Simulation and control, COSC 2022

作者： Zarodnyuk, Tatiana Gornov, Alexander Matrosov Institute for System Dynamics and Control Theory of SB RAS Irkutsk Russia Moscow Institute of Physics and Technology Dolgoprudny Russia

ISBN: (数字)9783031412295

ISBN: (纸本)9783031412288

The paper proposes a computational technology for constructing the boundary of the reachable set of the controlled dynamical systems. The monowave method underlying it relies on the use of a given sequence of controls with a moving switching point. To construct the controls of a given structure, the time interval is divided into equal parts. Then controls are built in the form of relay functions with switching points in the nodes of the generated grid. A series of computational experiments was carried out to construct the boundaries of non-convex reachable sets. The obtained results made it possible to demonstrate the effectiveness of the proposed monowave method. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.

关键词： Dynamical systems

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Semi-supervised K-Means Clustering via DC Programming Approach 22nd

Semi-supervised K-Means Clustering via DC Programming Appro...

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22nd International Conference on Mathematical Optimization theory and Operations Research, MOTOR 2023

作者： Gruzdeva, Tatiana V. Ushakov, Anton V. Matrosov Institute for System Dynamics and Control Theory of SB RAS 134 Lermontov str. Irkutsk664033 Russia

ISBN: (纸本)9783031353048

Though clustering is related to unsupervised machine learning and does not require any prior information on data items, in many real-life settings, there may be some expert knowledge on data labels or the properties of clusters known in advance. Obviously, such knowledge may be used to guide clustering process and improve the quality of found partitions. The clustering problems that involve some additional information on tags are called semi-supervised or constrained clustering problems. One distinguishes instance-level and cluster-level constraints usually formalized as the so-called must-link and cannot-link constraints or minimum/maximum cluster size. In this paper, we consider the constrained minimum sum-of-squares (k-means) clustering (MSSC) problem that incorporates both instance- and cluster-level constraints. As far as we know, such a semi-supervised MSSC problem has not been considered in the literature yet. We formulate this clustering problem and some of its particular cases as DC (difference of convex) optimization problems. Then, we develop a solution approach based on a special local search method. We carry out computational experiments on test problem instances demonstrating the efficiency of the proposed solution approach. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： K-means clustering

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Discrete Facility Location in Machine Learning

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Journal of Applied and Industrial Mathematics 2021年第4期15卷 686-710页

作者： Vasilyev, I.L. Ushakov, A.V. Matrosov Institute for System Dynamics and Control Theory Irkutsk664033 Russia

Abstract: Facility location problems form a broad class of optimization problems extremely popularin combinatorial optimization and operations research. In every facility location problem, one mustlocate a set of facilities in order to satisfy the demands of customers so as some certain objectivefunction be optimal. Besides numerous applications in public and private sectors, the problemsare widely used in machine learning. For example, clustering can be viewed as a facility locationproblem where we need to partition a set of customers into clusters assigned to open *** this survey we briefly look at how the ideas and approaches arisen in the field of facilitylocation led to modern, popular machine learning algorithms supported by many data mining andmachine learning software packages. We also review the state-of-the-art of exact methods andheuristics, as well as some extensions of the basic problems and algorithms in applied machinelearning tasks. Note that the main emphasis lies here on discrete facility location problems which,for example, underlie many widely used clustering algorithms (PAM, affinity propagation, etc.).Since the high computational complexity of the conventional facility location-based clusteringalgorithms hinders their application to modern large-scale real-life datasets;we also survey somemodern approaches to implementation of the algorithms for these large data collections. © 2021, Pleiades Publishing, Ltd.

关键词： Clustering algorithms

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Implicit Boolean Network for Planning Actions 45

Implicit Boolean Network for Planning Actions

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45th Jubilee International Convention on Information, Communication and Electronic Technology, MIPRO 2022

作者： Oparin, G.A. Bogdanova, V.G. Pashinin, A.A. Matrosov Institute for System Dynamics and Control Theory of Sb Ras Irkutsk Russia

ISBN: (纸本)9789532331035

It is usual to classify the automated searching of a plan as an artificial intelligence problem. In planning, the environment is defined as a set of both states and transitions between them. Planning consists in searching for a finite transitions sequence (actions) that transfers the initial state to one of the states, satisfying the objective. As a model of the planning environment, we propose to use implicit Boolean networks - binary dynamic systems, the transition function of which is defined by the implicit Boolean equation relative to the current state variables vector and some subsequent variables vectors. For this model, the forming of a plan is reduced to qualitative analysis of dynamic properties of the implicit binary dynamic system. In particular, these are reachability or cyclicity properties over a given discrete time interval. At the final stage of this method, the verification of the Boolean formula satisfiability is performed. This formula includes the equation of the dynamics of the implicit Boolean network and the specification of the dynamical property being verified. The considered approach is demonstrated on the problem of planning a river crossing and constructing a Hamiltonian cycle in a graph. A specialized parallel algorithm for solving deeply structured Boolean satisfiability problems is proposed, which provides scalability with an increase in their dimension. © 2022 Croatian Society MIPRO.

关键词： Hamiltonians

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