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1st Scientific-Practical Workshop on Information Technologies: Algorithms, Models, systems, ITAMS 2018

作者： Avramenko, Yuriy V. Fedorov, Roman K. Matrosov Institute for System Dynamics and Control Theory SB RAS Irkutsk Russia Irkutsk Scientific Center SB RAS Irkutsk Russia

Nowadays geoportals provide some geospatial tools as services, usually implemented using the WPS standard. In this paper geoportal main principles are observed and existing methods and present technologies of classifi... 详细信息

关键词： Data handling

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Information technologies for monitoring of anthropogenic impacts to Lake Baikal 1

Information technologies for monitoring of anthropogenic imp...

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1st Scientific-Practical Workshop on Information Technologies: Algorithms, Models, systems, ITAMS 2018

作者： Fereferov, Evgeniy S. Gachenko, Andrey S. Hmelnov, Alexey E. Fedorov, Roman K. Matrosov Institute for System Dynamics and Control Theory SB RAS Irkutsk Russia Irkutsk scientific center SB RAS Irkutsk Russia

The article considers information technologies for monitoring pollution of lake systems. The authors created a geoportal that provides collection and generalization of the results of researches of anthropogenic impact on the ecology of Lake Baikal. Expanded on the geoportal Internet services, provide a comprehensive analysis of collected data and their geoprocessing. The open architecture of the developed geoportal allows expanding its functionality by addition of new services which can be deployed both locally, on the geoportal server, as well as on any other server in the Internet. The interoperability of software systems that implement the analysis and geodata processing functions is provided due to support of geoinformatics standards. One of the features of the developed geoportal is that users can independently operate structures of data and adjust launching of services of geoprocessing, including those services that use computing power of The Center of collective usage "Irkutsk supercomputer center Siberian Branch of the Russian Academy of Science". The authors carried out the initial filling of the system database with the results of research, thematic cartographic layers were constructed. A number of services was deployed on the geoportal in order to provide geodata processing. Authors constructed a coordinated digital model of land and bottom relief near Listvyanka using the original library of triangulation and the technology of morphing of digital maps. This model of relief allows solving the problems of analysis of the distribution of pollutants taking into account the landscape. © 2018 CEUR-WS. All rights reserved.

关键词： Lakes

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Three Search Algorithms for Three Nonconvex Optimization Problems

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Journal of Mathematical Sciences (United States) 2022年第4期267卷 457-464页

作者： Gornov, A. Yu. Sorokovikov, P.S. Zarodnyuk, T.S. Anikin, A.S. Matrosov Institute for System Dynamics and Control Theory of SB RAS 134 Lermontov Str. Ikrusk 664033 Russian Federation

The paper deals with three numerical approaches that allow one to construct computational technologies for solving nonconvex optimization problems. We propose to use the developed algorithms based on modifications of the tunnel search algorithm, the Luus–Yaakola method, and the expert algorithm. The presented techniques are implemented within the framework of the software package and are used for solving nonconvex optimization problems of various classes, in particular, the minimization of the potential function for the Sutton–Chen atomic-molecular cluster, the problem of parametric identification of nonlinear dynamic systems, and the nonconvex optimal control problem. © 2022, Springer Science+Business Media, LLC, part of Springer Nature.

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Optimality Conditions for Impulsive Processes with Intermediate State Constraints 15

Optimality Conditions for Impulsive Processes with Intermedi...

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15th International Conference on Stability and Oscillations of Nonlinear control systems (Pyatnitskiy's Conference), STAB 2020

作者： Samsonyuk, Olga Sorokin, Stepan Matrosov Institute for System Dynamics and Control Theory of Ras Irkutsk Russia

ISBN: (纸本)9781728167053

This paper is concerned with an optimal impulsive control problem under intermediate state constraints. The control system of this problem is bilinear with respect to states of bounded variation and impulsive controls given by vector Borel measures. We propose necessary and sufficient optimality conditions based on special functions of the Lyapunov type. These functions possess the property of strong and weak monotonicity with respect to the impulsive control system. © 2020 IEEE.

关键词： control systems

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Technique for modelling flooding zones of coastal areas in the cascade of hydroelectric power stations on the Angara river

Technique for modelling flooding zones of coastal areas in t...

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2020 International Online Conference on Environmental Transformation and Sustainable Development in Asian Region, EnTransAsia 2020

作者： Gachenko, A.S. Hmelnov, A.E. Matrosov Institute for System Dynamics and Control Theory SB RAS Irkutsk Russia Irkutsk Scientific Center SB RAS Irkutsk Russia

This article presents the method for modelling underwater three-dimensional topography and it's combining with terrain under conditions of incomplete source data. The technique for constructing 3D elevation model was tested within the research projects conducted in matrosov institute for system dynamics and control theory Siberian Branch of the Russian Academy of Sciences in collaboration with colleagues from other research institutes of Irkutsk Scientific Center under the comprehensive studies of Lake Baikal, the Angara River and the Bratsk Reservoir. We present an algorithm for combining underwater topography with terrain based on heterogeneous source data using the Delaunay triangulation. The combining yields a high-quality 3D elevation model. This model can be used to make forecasts of the changes in the coastlines of reservoirs, which are associated with water discharges from hydroelectric power stations. The described technique was used to solve some practical problems and showed its effectiveness. To combine the data on the terrain and underwater topography, we developed a special software using the Delaunay triangulation algorithms. For data layers, their roles were indicated during the triangulation. Layers contained the information about terrain, watermarks, contours of the coastline, and underwater topography. For underwater topography, we used the information about the marks of the water edge. Based on these data, we built an additional triangulation, from which we subsequently obtained the information about heights because contours of coastlines are confined to heights, and depths are measured relative to heights. As a result of this study, we processed some settlements and estimated possible flooding. © 2021 institute of Physics Publishing. All rights reserved.

关键词： Hydroelectric power plants

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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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Service compositions in problems of urban planning 1

Service compositions in problems of urban planning

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1st Scientific-Practical Workshop on Information Technologies: Algorithms, Models, systems, ITAMS 2018

作者： Fedorov, Roman K. Shumilov, Alexander S. Irkutsk Scientific Center SB RAS Irkutsk Russia Matrosov Institute for System Dynamics and Control Theory SB RAS Irkutsk Russia

Information technologies are being applied in almost all fields of human activities, including the urban planning. One of the common problems in urban planning is the estimation of transport and walking availability of various socially important facilities. Geoportal of ISDCT sb ras proposes to solve this problem using service compositions, defined in a form of JavaScript programs. During the composition execution, the automatic parallelization of services is performed in order to minimize the overall composition execution time. The scenario planning and execution processes are shown, as well as the ability to adapt to changes in computing environment. © 2018 CEUR-WS. All rights reserved.

关键词： Distributed computer systems

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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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Estimation of water quality parameters from space images 1

Estimation of water quality parameters from space images

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1st International Workshop on Advanced Information and Computation Technologies and systems, AICTS 2020

作者： Popova, A.K. Matrosov Institute for System Dynamics and Control Theory SB RAS 134 Lermontova Street Irkutsk664033 Russia

Water quality affects many human activities. Remote sensing is efficient and economical instrument for water monitoring. The paper investigates the problem of choosing an algorithm for Chl-a concentration determination. In this study, we made calculations for Multispectral Instrument (MSI) on Sentinel-2 for Lake Baikal by different empirical algorithms and C2RCC tool. We choose 3 band combination that have high correlation with in situ data of Chl-a. Resultant distribution map display spatial dynamics of Chl-a in the lake. Our research is intended to help environmental scientist to assess pollution level of the Lake Baikal and interpret the ecological meaning of results. © 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Water quality

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A Computational Study of the DC Minimization Global Optimality Conditions Applied to K-Means Clustering 12th

A Computational Study of the DC Minimization Global Optimali...

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12th International Conference on Optimization and Applications, OPTIMA 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)9783030910587

Clustering is traditionally one of the basic tools of data analysis widely applied in diverse fields. By now, one of the most common clustering models is the Euclidean minimum-sum-of-squares clustering problem (MSSC). Consequently, Lloyd’s algorithm, often referred to as k-means, is probably the most popular clustering algorithm. Despite its popularity, Lloyd’s algorithm is a local search heuristic for MSSC that in general converges to local optima only. In this paper, we aim at enhancing k-means by employing the global optimality conditions for MSSC represented as a problem with DC (difference of convex) functions. We then embed the k-means algorithm into the so-called global search framework for DC minimization problems where it is employed to find local optimal solutions. We tested such an improved implementation of k-means in a series of computation experiments on well-known test library of medium-size datasets and compared it with the conventional k-means and k-means++ algorithms. © 2021, Springer Nature Switzerland AG.

关键词： K-means clustering

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