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A platform approach to the organization of digital forest monitoring of the Baikal natural territory 11

A platform approach to the organization of digital forest mo...

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11th International Conference and Early Career Scientists School on Environmental Observations, Modeling and Information systems, ENVIROMIS 2020

作者： Bychkov, I.V. Ruzhnikov, G.M. Fedorov, R.K. Popova, A.K. Matrosov Institute for System Dynamics and Control Theory SB RAS 134 Lermontova Street Irkutsk664033 Russia

This paper describes a platform approach to the organization of digital environmental monitoring of the forest resources of the Baikal natural territory (BNT), some characteristics of the current state of forests in the BNT and schemes of organization of state environmental monitoring in a traditional format. Some features and problems of forest resources monitoring of the BNT that complicate decision-making are formulated. Some basic requirements for digital forest monitoring and types of digital platforms of different levels are considered. © Published under licence by IOP Publishing Ltd.

关键词： Decision making

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An approach how to automate labeling data for the training ANN models for page layout analysis 3

An approach how to automate labeling data for the training A...

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3rd Scientific-Practical Workshop Information Technologies: Algorithms, Models, systems, ITAMS 2020

作者： Mikhailov, Andrey Matrosov Institute for System Dynamics and Control Theory SB RAS 134 Lermontov st. Irkutsk Russia

Object detection and recognition is an important task in many document analysis applications. It is a difficult problem due to different page layouts and representation formats. Recently the deep learning in computer vision has significantly boosted the data-driven image-based approaches for page layout analysis. In this paper, we consider open formats of electronic documents to generate training datasets. Formats of these documents should contain markup allowing obtaining information about page layout regions. It will allow us to generate a training dataset automatically for training ANN models of page layout analysis. © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Deep learning

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K-Means Clustering via a Nonconvex Optimization Approach 20th

K-Means Clustering via a Nonconvex Optimization Approach

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20th International Conference on Mathematical Optimization theory and Operations Research, MOTOR 2021

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

ISBN: (纸本)9783030778750

Clustering is one of the basic tasks in machine learning and data mining. Euclidean minimum-sum-of-squares clustering problem is probably the most common clustering model. It consists in finding k cluster centers or representatives so as the sum of squared Euclidean distances from a set of points and their closest centers is minimized. The problem is known to be nonconvex and NP-hard even in the planner case. In this paper, we propose a new DC programming approach to the problem. First, we cast the original nonconvex problem as a continuous optimization problem with the objective function represented as a DC function. We then devise a solution algorithm, resting upon the global optimality conditions and global search scheme for DC minimization problems proposed by A.S. Strekalovsky. We implement the developed algorithm and compare it with k-means clustering algorithms on generated datasets. © 2021, Springer Nature Switzerland AG.

关键词： K-means clustering

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On a Nonconvex Distance-Based Clustering Problem 21st

On a Nonconvex Distance-Based Clustering Problem

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21st International Conference on Mathematical Optimization theory and Operations Research, MOTOR 2022

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

ISBN: (纸本)9783031096068

Clustering is one of the basic data analysis tools and an important subroutine in many machine learning tasks. Probably, the most well-known and popular clustering model is the Euclidean minimum-sum-of-squares clustering problem, also known as the k-means problem. Clustering with Bregman divergences is a generalization of the k-means problem where the distances between data items and closest cluster centers are computed according to any Bregman divergence, rather than the squared Euclidean distance. In this paper, we consider a mathematical programming problem of clustering with Bregman divergences. We propose several representations of the problem in the form of a DC (difference of convex) program and develop a DC programming approach to solve it. We provide particular DC representations and particular DC solution algorithms for several widely-known Bregman divergences. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： K-means clustering

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Configurable table structure recognition in untagged PDF documents 16

Configurable table structure recognition in untagged PDF doc...

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16th ACM Symposium on Document Engineering, DocEng 2016

作者： Shigarov, Alexey Mikhailov, Andrey Altaev, Andrey Matrosov Institute for System Dynamics and Control Theory SB RAS 134 Lermontov st. Irkutsk Russia

ISBN: (纸本)9781450344388

Today, PDF is one of the most popular document formats in the web. Many PDF documents are not images, but remain untagged. They have no tags for identifying the logical reading order, para- graphs, figures, and tables. One of the challenges with these doc- uments is how to extract tables from them. The paper discusses a new system for table structure recognition in untagged PDF doc- uments. It is formulated as a set of configurable parameters and ad-hoc heuristics for recovering table cells. We consider two dif- ferent configurations for the system and demonstrate experimental results based on the existing competition dataset for both of them.

关键词： table structure recognition pdf document analysis table extraction pdf accessibility untagged pdf documents

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Automation of microservices creation for qualitative analysis of binary dynamic systems 1

Automation of microservices creation for qualitative analysi...

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1st International Workshop on Information, Computation, and control systems for Distributed Environments, ICCS-DE 2019

作者： Oparin, G.A. Bogdanova, V.G. Pashinin, A.A. Matrosov Institute for System Dynamics and Control Theory SB RAS Lermontov St. 134 Irkutsk664033 Russia

The main objective of qualitative research is to analyze the behavior of the trajectories of a dynamic system to verify whether it corresponds to the set of constraints characterizing the property. We use an approach to study binary dynamic systems on a finite time interval based on the author's method of Boolean constraints. Based on this method, the Boolean model of the properties of a binary dynamic system is written in the language of Boolean equations or Boolean formulas with quantifiers. Thus, the verification of various dynamical properties is reduced to solving the problems of Boolean constraints satisfiability or the validity of a quantified Boolean formula using efficient SAT or TQBF solvers. The high computational complexity of these problems requires the development of software and tools for their parallel and distributed solving and ensuring transparent end-user access to high-performance computing environments based on a service-oriented approach. This paper represents the architecture and functionality of a new instrumental system that automates the creation of a distributed application for solving the considered class of problems based on the microservice approach and multi-agent technology. Copyright © 2019 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Service oriented architecture (SOA)

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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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system for monitoring parameters of functioning infrastructure objects and their external environment 2

System for monitoring parameters of functioning infrastructu...

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2nd International Workshop on Information, Computation, and control systems for Distributed Environments, ICCS-DE 2020

作者： Sidorov, I.A. Kostromin, R.O. Feoktistov, A.G. Matrosov Institute for System Dynamics and Control Theory of SB RAS Lermontov St. 134 Irkutsk664033 Russia

The paper addresses relevant issues applying the concept of Industry 4.0 in related to modeling infrastructure objects at the Baikal natural territory that use environmentally friendly technologies. In particular, the use of heat pumps belongs to such technologies, since this enables us to reduce air emissions. Object models are designed on the basis of their digital twins. Digital twins are intended to reflect the structure and processes of object functioning. In addition, we plan to delegate them the decision-making in managing these objects in real-time. Such a digital twin has to become smarter over time. This virtual entity has to gain knowledge and skills to select optimal scenarios for controlling object and improving its functioning parameters. Therefore, the initial problem in its development is creating a monitoring system for the collection, unification, aggregation, storage, and transmission of subject-oriented data. Such data include information about the object operation and environmental state. The data must be promptly obtained from peripheral equipment (controlling and measuring devices). For the effective operation of a digital twin, we have to partially transfer functions of primary data processing, their intellectual analysis and decision-making to the controlling and measuring devices. To this end, we use agents that implement software on peripheral equipment. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Decision making

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The global search theory approach to the bilevel pricing problem in telecommunication networks 7th

The global search theory approach to the bilevel pricing pro...

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7th International Conference on Network Analysis, NET 2017

作者： Orlov, Andrei V. Matrosov Institute for System Dynamics and Control Theory of SB RAS Lermontov St. 134 Irkutsk664033 Russia

ISBN: (纸本)9783319962467

In this paper, we develop new methods of local and global search for finding optimistic solutions to the hierarchical problem of optimal pricing in telecommunication networks. These methods are based on the fact that a bilevel optimization problem can be equivalently represented as a nonconvex optimization problem (with the help of the Karush-Kuhn-Tucker conditions and the penalty approach). To solve the resulting nonconvex problem, we apply the Global Search theory (GST).Computational testing of the developed methods on a test problem demonstrated workability and efficiency of the approach proposed. © Springer International Publishing AG, part of Springer Nature 2018.

关键词： Optimization

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On the optimization approach to polymatrix games 13

On the optimization approach to polymatrix games

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13th International Symposium on Operational Research, SOR 2015

作者： Orlov, Andrei Matrosov Institute for System Dynamics and Control Theory SB RAS Lermontov str. 134 Irkutsk664033 Russia

The problem of numerical finding of a Nash equilibrium in a polymatrix game is considered. Such a game turns out to be equivalent to the solving a nonconvex optimization problem with a bilinear structure in the object... 详细信息

ISBN: (纸本)9789616165457

关键词： Local search (optimization)

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