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48th international Youth School Conference "Modern Problems in Mathematics and its applications", SoProMat 2017

The proceedings contain 40 papers. The topics discussed include: subgroups in groups of lie type normalized by an elementary subgroup;on the analysis of application algorithms using drivers in windows 7-10 operating systems;semirings of continuous partial real-valued functions;applications of Galois theory to optimal control;on the possibility of considering the braking of a disk in the form of an antagonistic differential game;to the simple pursuit problem;reachable set for the dubins car under asymmetric constraint on control;on the reachability problem for a nonlinear control system with integral constraints;iterative algorithms for optimal packing construction in inhomogeneous metrics;and collision avoidance algorithm with performance optimization and speed control for multi-robot autonomous system.

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An overview of the proper generalized decomposition with applications in computational rheology

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JOURNAL OF NON-NEWTONIAN FLUID MECHANICS 2011年第11期166卷 578-592页

作者： Chinesta, F. Ammar, A. Leygue, A. Keunings, R. UMR CNRS Cent Nantes EADS Corp Fdn Int Chair GEM F-44321 Nantes 3 France Arts & Metiers ParisTech F-49035 Angers 01 France Catholic Univ Louvain ICTEAM B-1348 Louvain Belgium

We review the foundations and applications of the proper generalized decomposition (PGD), a powerful model reduction technique that computes a priori by means of successive enrichment a separated representation of the unknown field. The computational complexity of the PGD scales linearly with the dimension of the space wherein the model is defined, which is in marked contrast with the exponential scaling of standard grid-based methods. First introduced in the context of computational rheology by Ammar et al. [3,4], the PGD has since been further developed and applied in a variety of applications ranging from the solution of the Schrodinger equation of quantum mechanics to the analysis of laminate composites. In this paper, we illustrate the use of the PGD in four problem categories related to computational rheology: (i) the direct solution of the Fokker-Planck equation for complex fluids in configuration spaces of high dimension, (ii) the development of very efficient non-incremental algorithms for transient problems, (iii) the fully three-dimensional solution of problems defined in degenerate plate or shell-like domains often encountered in polymer processing or composites manufacturing, and finally (iv) the solution of multidimensional parametric models obtained by introducing various sources of problem variability as additional coordinates. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Complex fluids Numerical modeling Model reduction Proper orthogonal decomposition Proper generalized decomposition Kinetic theory Parametric models optimization Inverse identification

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Recent advances on data-driven services for smart energy systems optimization and pro-active management

Recent advances on data-driven services for smart energy sys...

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IEEE international workshop on Metrology for Living Environment (MetroLivEnv)

作者： Testasecca, Tancredi Lazzaro, Marilena Sarmas, Elissaios Stamatopoulos, Stathis Univ Palermo Dipartimento Ingn Palermo Italy Engn Ingn Informat SpA Res & Innovat Dept Palermo Italy Natl Tech Univ Athens Sch Elect & Comp Engn Decis Support Syst Lab Athens Greece

ISBN: (纸本)9781665456937

optimization and proactive management of energy systems are crucial for achieving sustainability, efficiency and resilience in future smart energy networks. Data-driven approaches offer promising solutions for tackling the complex and dynamic challenges of energy systems, such as uncertainty, variability, and heterogeneity. Meanwhile, recent advances in decreasing hardware costs and improving data accessibility have allowed for the collection of high-quality data, leading to the development of more accurate and robust datadriven models of different energy systems. In this study, a comprehensive overview of current and future trends in data-driven optimization for smart energy systems is presented. After introducing the motivation and the background of this research field, the potential applications and benefits of optimization in various domains is discussed, such as electric vehicles charge, district heating networks and energy districts. Subsequently this review focuses on different methods and techniques for datadriven optimization and proactive management, ranging from scientific models to machine learning algorithms. Finally, the novel European project, DigiBUILD, is introduced, where different case studies are tested in several pilots, including electric vehicle charging management for increasing renewable energy source consumption, district heating network operative costs optimization and building energy and comfort management.

关键词： Fault Detection Smart Building Electric Vehicles Energy Management optimization

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multilevel thresholding using ant colony optimization

Multilevel thresholding using ant colony optimization

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international Multiconference of Engineers and Computer Scientists

作者： Liang, Yun-Chia Yin, Yueh-Chuan Chen, Angela Hsiang-Ling Yuan Ze Univ Dept Ind Engn & Management 135 Yuan Tung Rd Chungli 320 Taiwan Nanya Inst Technol Dept Financial Management Chungli 320 Taiwan

ISBN: (纸本)9789889867140

Thresholding is an important technique for image segmentation. The aim of an effective segmentation is to separate objects from the background and to differentiate pixels having nearby values for improving the contrast. The Otsu's method and Kittler's method are two of the most referred exhaustive thresholding methods. Our study proposes a hybrid optimization scheme based on an Ant Colony System algorithm with the Otsu and Kittler's methods respectively to render the optimal thresholding technique more applicable and effective. The ACS-Otsu and ACS-Kittler algorithms, two non-parametric and unsupervised methods, are the extension on the applications of the Ant Colony optimization (ACO) for image segmentation. The experimental results show that ACS-Otsu algorithm outperforms ACS-Kittler algorithm in both CPU time and image quality in most level cases of test images.

关键词： ant colony system image segmentation otsu's method kittler's method multi-level thresholding

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About use of methods of convex programming for synthesis of conformal arrays with matched dual-polarized patterns 8

About use of methods of convex programming for synthesis of ...

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8th international Conference on optimization and applications, OPTIMA 2017

作者： Izhutkin, Viktor S. Sharapov, Anton A. Moscow Power Engineering Institute Krasnokazarmennaya Ulica 14 Moscow111250 Russia

The solution of a task of the analysis and collecting polarizing information can improve considerably possibilities of radars in various appendices, such as: detection, assessment and tracking of radar targets. This task for a cage antenna lattice with the standard dual-polarized patterns is formulated in terms of convex optimization. The possibilities of the solution of an objective by means of a special Matlab CVX toolbox and various classical algorithms of convex optimization are considered. Also comparison of the results of the solution of an optimizing task received in the different ways is presented. © Copyright by the paper's authors.

关键词： Convex optimization

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18th IFAC workshop on Control applications of optimization, CAO 2022 - Proceedings

18th IFAC Workshop on Control Applications of Optimization, ...

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18th IFAC workshop on Control applications of optimization, CAO 2022

The proceedings contain 72 papers. The topics discussed include: reinforcement learning with function approximation for 3-spheres swimmer;considerations on two-phase averaging of time-optimal control systems;a unified MPC envelope control formulation for Toyota guardian and chauffeur;optimal driving under traffic signal uncertainty;optimization in a traffic flow model as an inverse problem in the Wasserstein space;on the asymptotic behavior of the value function in large time optimal control problems;time minimal syntheses in the abnormal case using geometric and computational techniques;stability of solutions for controlled nonlinear systems under perturbation of state constraints;optimal control problems with non-control regions: necessary optimality conditions;nonlinearity handling in MPC for power congestion management in sub-transmission areas;and scalable optimal control allocation: linear and quadratic programming methods applied to active capacitor balancing in modular multilevel converters.

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A Hybrid Rice optimization Algorithm with Ant System for Feature Selection 11

A Hybrid Rice Optimization Algorithm with Ant System for Fea...

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11th IEEE international Conference on Intelligent Data Acquisition and Advanced Computing Systems - Technology and applications (IDAACS)

作者： Ye, Zhiwei Shu, Zhe Liu, Shiuin Xia, Xiaoyu Hubei Univ Technol Sch Comp Sci Wuhan Peoples R China

ISBN: (纸本)9781665426053

Feature selection is an important processing step of data mining and aims at selecting a subset with high quality. The feature subset is obtained by reducing the irrelevant and redundant features based on maintaining satisfactory accuracy. Many algorithms might be trapped in local optima on solving high-dimensional feature selection. Hybrid rice optimization (HRO) is a newly presented algorithm, its population is divided into three types such as the maintainer, restorer, and sterile line to simulate the breeding process of Chinese hybrid rice. Three main stages are designed to update the restorer and sterile line. However, the maintainer line is not updated in HRO, which degrades the performance of the algorithm on high-dimensional feature selection. In this paper, a hybrid model named HROAS is proposed for feature selection by combining HRO with ant system (AS). AS is embedded as an operator in HRO to update the maintainer line due to its unique updating mechanism. The performance of HROAS is evaluated on nine standard benchmark datasets and compared with several classic and novel algorithms. The experimental results demonstrate the outperformance of HROAS.

关键词： feature selection hybrid rice optimization algorithm ant system

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algorithms and Architectures for Parallel Processing 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Guojin Wang Albert Zomaya Gregorio Martinez Kenli Li

ISBN: (数字)9783319271613

ISBN: (纸本)9783319271606

The program of this year consists of 6 symposiums/workshops that cover a wide range of research topics on parallel processing technology: the Sixth international workshop on Trust, Security and Privacy for Big Data, TrustData 2015; the Fifth international Symposium on Trust, Security and Privacy for Emerging applications, TSP 2015; the Third international workshop on Network optimization and Performance Evaluation, NOPE 2015; the Second international Symposium on Sensor-Cloud Systems, SCS 2015; the Second international workshop on Security and Privacy Protection in Computer and Network Systems, SPPCN 2015; and the First international Symposium on Dependability in Sensor, Cloud, and Big Data Systems and applications, DependSys 2015.

关键词： Algorithm Analysis and Problem Complexity Artificial Intelligence Software Engineering Information Systems applications (incl. Internet) Computer Communication Networks Management of Computing and Information Systems

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optimization of flows and flexible redistribution of autonomous UAV routes in multilevel airspace 15

Optimization of flows and flexible redistribution of autonom...

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15th international Conference on ICT in Education, Research and Industrial applications. Integration, Harmonization and Knowledge Transfer, ICTERI 2019

作者： Shmelova, Tetiana Sterenharz, Arnold Burlaka, Oleksandr National Aviation University Komarova av. 1 Kiev03058 Ukraine Germany National Aviation University Komarova av. 1 Kiev03058 Ukraine

The authors present a problem of the performance of Unmanned Aerial Vehicles (UAV)’s flights (group or single flight) for the decision of different target tasks in the city using information air navigation technology and methods of mathematical modeling in Artificial Intelligence (graph theory, Expert Judgment Method, methods of decision making in risk and fuzzy-logic, dynamic programming, etc.). The configuration and optimization of group flight routes for UAVs depend on the type of "target task". The algorithm of estimation performance of UAVs flights in the smart-town, an illustrative example of the optimization of UAVs flights is presented in the article. © 2019 CEUR-WS. All rights reserved.

关键词： Decision making

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Using meta-learning to initialize Bayesian optimization of hyperparameters

Using meta-learning to initialize Bayesian optimization of h...

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international workshop on Meta-Learning and Algorithm Selection, MetaSel 2014 - Co-located with 21st European Conference on Artificial Intelligence, ECAI 2014

作者： Feurer, Matthias Springenberg, Jost Tobias Hutter, Frank University of Freiburg Germany

Model selection and hyperparameter optimization is crucial in applying machine learning to a novel dataset. Recently, a subcommunity of machine learning has focused on solving this problem with Sequential Model-based Bayesian optimization (SMBO), demonstrating substantial successes in many applications. However, for expensive algorithms the computational overhead of hyperparameter optimization can still be prohibitive. In this paper we explore the possibility of speeding up SMBO by transferring knowledge from previous optimization runs on similar datasets;specifically, we propose to initialize SMBO with a small number of configurations suggested by a metalearning procedure. The resulting simple MI-SMBO technique can be trivially applied to any SMBO method, allowing us to perform experiments on two quite different SMBO methods with complementary strengths applied to optimize two machine learning frameworks on 57 classification datasets. We find that our initialization procedure mildly improves the state of the art in low-dimensional hyperparameter optimization and substantially improves the state of the art in the more complex problem of combined model selection and hyperparameter optimization.

关键词： Classification (of information)

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