الصفحة 6
الصفحة 6
Combinatorial optimization and applications ; 2nd International Conference, COCOA 2008, St. John’s, NL, Canada, August 21-24, 2008. Proceedings
This book constitutes the refereed proceedings of the Second International Conference on Combinatorial Optimization and Applications, COCOA 2008, held in St. John's, Canada, in August 2008.
Combinatorial optimization and applications ; 1st International Conference, COCOA 2007, Xi'an, China, August 14-16, 2007, Proceedings
This book presented feature original research in the areas of combinatorial optimization - both theoretical issues and and applications motivated by real-world problems thus showing convincingly the usefulness and efficiency of the algorithms discussed in a practical setting.
Combinatorial optimization and applications ; 14th International Conference, COCOA 2020, Dallas, TX, USA, December 11–13, 2020, Proceedings
This volume constitutes the proceedings of the 14th International Conference on Combinatorial Optimization and Applications, COCOA 2020, held in Dallas, TX, USA, in December 2020. The 55 full papers presented in this volume were carefully reviewed and selected from 104 submissions. The papers are grouped into the following topics: Approximation Algorithms; Scheduling; Network Optimization; Complexity and Logic; Search, Facility and Graphs; Geometric Problem; Sensors, Vehicles and Graphs; and Graph Problems.
Combinatorial image analysis ; 10th International Workshop, IWCIA 2004, Auckland, New Zealand, December 1-3, 2004, Proceedings
This volume presents the proceedings of the 10th International Workshop on Combinatorial Image Analysis,held 2004, in Auckland, New Zealand. For this workshop we received 86 submitted papers from 23 countries. We selected 55 papers for the conference. completed the program. Conference papers are presented in this volume under the following topical part titles: discrete tomography (3 papers), combinatorics and computational models (6), combinatorial algorithms (6), combinatorial mathematics (4), d- ital topology (7), digital geometry (7), approximation of digital sets by curves and surfaces (5), algebraic approaches (5), fuzzy image analysis (2), image s- mentation (6), and matching and recognition (7). These subjects are dealt with in the context of digital image analysis or computer vision.
Combinatorial and Algorithmic Aspects of Networking ; 4th Workshop, CAAN 2007, Halifax, Canada, August 14, 2007, Revised Papers
It contiants developments on all aspects of networking could be presented. It covered were diverse, with talks on strategies for searching in networks, for cleaning networks of unwanted - truders, on difierent routing strategies, and on scheduling, load balancing, probability, a concept central to network modeling and managing.
Combinatorial and Algorithmic Aspects of Networking (vol. # 4235) ; Third Workshop, CAAN 2006, Chester, UK, July 2, 2006, Revised Papers
This book constitutes the thoroughly refereed post-proceedings of the Third Workshop on Combinatorial and Algorithmic Aspects of Networking, held in Chester, UK in July 2006, co-located with the 13th Colloquium on Structural Information and Communication Complexity, SIROCCO 2006.The 10 revised full papers and one invited lecture cover a range from the Web graph to game theory to string matching, all in the context of large-scale networks.
Mathematical Methods in Time Series Analysis and Digital Image Processing
The aim of this volume is to bring together research directions in theoretical signal and imaging processing developed rather independently in electrical engineering, theoretical physics, mathematics and the computer sciences. In particular, mathematically justified algorithms and methods, the mathematical analysis of these algorithms, and methods as well as the investigation of connections between methods from time series analysis and image processing are reviewed. An interdisciplinary comparison of these methods, drawing upon common sets of test problems from medicine and geophysical/enviromental sciences, is also addressed.
Mathematical Foundations of Computer Science 2005 ; 30th International Symposium, MFCS 2005, Gdansk, Poland, August29-September 2. 2005, Proceedings
Constitutes the proceedings of the 30th International Symposium on Mathematical Foundations of Computer Science, MFCS 2005, held in Gdansk, Poland in August/September 2005. The 62 papers address various aspects in theoretical computer science, ranging from quantum computing, approximation, automata, circuits, scheduling, games, and more.
Matematica generale con il calcolatore
By introducing mathematical objects, it teaches students how to use a computer to perform numerical and symbolic calculations, define a function and calculate its values, plot and explore graphs, and execute simple algorithms. The course is rich in examples, applications, and models, drawn from economics, physics, biology, statistics, and mathematics itself. The analysis of these models constitutes, in a certain sense, the true purpose of the mathematical theory covered. Automatic calculation tools (mathematics software, spreadsheets) are used extensively to explore and illustrate concepts and properties. Mathcad® software, in particular, was used, both as a calculation tool and as a simple yet powerful programming language. Considerable space is devoted to approximation, emphasizing the distinction between numerical and symbolic calculation; to algorithms as a synthesis of the syntactic and semantic aspects of mathematical objects; and to computer simulation, interpreted as a "physical" experiment and a source of conjecture. The ability to use a calculator marks a sort of "democratization" of mathematics: even complex results, which have always required a broad background of knowledge and laborious calculations, are now quickly accessible to anyone who understands the meaning of mathematical objects and knows how to use the syntax.
Macroscopic Transport Equations for Rarefied Gas Flows : Approximation Methods in Kinetic Theory
This book discusses classical and modern methods to derive macroscopic transport equations for rarefied gases from the Boltzmann equation, for small and moderate Knudsen numbers, i.e.as well as the new order of magnitude method, which avoids the short-comings of the classical methods, but retains their benefits.
Machine learning methods for reverse engineering of defective structured surfaces
Pascal Laube presents machine learning approaches for three key problems of reverse engineering of defective structured surfaces: parametrization of curves and surfaces, geometric primitive classification and inpainting of high-resolution textures. The proposed methods aim to improve the reconstruction quality while further automating the process. The contributions demonstrate that machine learning can be a viable part of the CAD reverse engineering pipeline.
Machine learning for risk calculations : A practitioner's view
Fundamental Approximation Methods. Machine Learning -- Deep Neural Nets -- Chebyshev Tensors -- The toolkit - plugging in approximation methods. Introduction: why is a toolkit needed -- Composition techniques -- Tensors in TT format and Tensor Extension Algorithms -- Sliding Technique -- The Jacobian projection technique -- Hybrid solutions - approximation methods and the toolkit.
Logistics Systems Analysis
It has two new sections, a new appendix, and more than half a dozen new figures. A few references have also been added, Much of the new material is based on work , The financial support of the National Science Foundation and the Volvo Foundations Center of Excellence for the Future of Urban Transportation at U. C. Berkeley is also acknowledged. The new appendix presents the logic behind the traveling salesman and vehicle routing results used in Sec. 4. 2 to describe the transportation ope- tion; Chapter 4 is more self-contained as a result. New section 5. 6 int- duces and evaluates a general method that automatically translates the c- tinuum approximation recipes of Chapters 4 and 5 into discrete system designs. This closes a gap in previous editions. Other additions include an explanation of how to develop system designs that can efficiently acc- modate real-time control strategies to manage uncertainty (new section 4. 6. 3), and extensions of the many-to-many design ideas of Chap. 6
LMI Approach to Analysis and Control of Takagi-Sugeno Fuzzy Systems with Time Delay
A fuzzy system is, in a very broad sense, any fuzzy logic-based system where fuzzy logic can be used either asthebasisfor the representation of different forms of system knowledge or the model for the interactions and relationships among the system variables. Fuzzy systems have proven to be an important tool for modeling complex systems for which, due to complexity or imprecision, classical tools are unsuccessful. There have been diverse fields of applications of fuzzy technology from medicine to management, from engineering to behavioral science, from vehicle control to computational linguistics, and so on. Fuzzy modeling is a conjunction to understand the s- tem’s behavior and build useful mathematical models. Different types of fuzzy models have been proposed in the literature, among which the Takagi-Sugeno (T-S) fuzzy model is a rule-based one suitable for the accurate approximation and identi?cation of a wide class of nonlinear systems.
Light Scattering by Optically Soft Particles: Theory and Applications
Deals with a particular class of approximation methods in the context of light scattering by small particles. This class of approximations has been termed as eikonal or soft particle approximations. The eikonal approximation was studied extensively in the potential scattering and then adopted in optical scattering problems. In this context, the eikonal and other soft particle approximations pertain to scatterers whose relative refractive index compared to surrounding medium is close to unity. The study of these approximations is very important because soft particles occur abundantly in nature. For example, the particles that occur in ocean optics, biomedical optics, atmospheric optics and in many industrial applications can be classified as soft particles. This book was written in recognition of the long-standing and current interest in the field of scattering approximations for soft particles. It should prove to be a useful addition for researchers in the field of light scattering.
Learning Classifier Systems ; International Workshops, IWLCS 2003-2005, Revised Selected Papers
The work embodied in this volume was presented across three consecutive e- tions of the International Workshop on Learning Classi?er Systems that took place in Chicago (2003), Seattle (2004), and Washington (2005). The Genetic and Evolutionary Computation Conference, the main ACM SIGEvo conference, hosted these three editions.
Learning Classifier Systems ; 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006 and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Papers
Constitutes the thoroughly refereed joint post-conference proceedings of two consecutive International Workshops on Learning Classifier Systems that took place in Seattle, WA, USA in July 2006, and in London, UK, in July 2007 - all hosted by the Genetic and Evolutionary Computation Conference, GECCO.The 14 revised full papers presented were carefully reviewed and selected from the workshop contributions. The papers are organized in topical sections on knowledge representation, analysis of the system, mechanisms, new directions, as well as applications.
Le choix bayésien: Principes et pratique
Covers the so-called Bayesian approach to statistical inference and in particular its decision-making aspects. The bases of this axiomatics (choice of the a priori, optimal decisions, tests and regions of confidence) are discussed in detail, as well as more recent openings of Bayesian analysis such as the choice of models, the use of numerical methods. Stochastic approximation (MCMC), the theory of noninformative laws (Berger-Bernardo axioms) and the relation to the classical theory of admissibility. Each chapter is completed by an extensive series of exercises of increasing difficulty and by bibliographical notes on the themes addressed. This book can be used in a Master's program in Applied Mathematics, Biometrics, Econometrics or any other program that uses quantitative information processing techniques. It only requires a basic course in probability theory and mathematical statistics as a preliminary.
Large-Scale Scientific Computing ; 6th International Conference, LSSC 2007, Sozopol, Bulgaria, June 5-9, 2007. Revised Papers
The 6th International Conference on Large-Scale Scienti?c Computations (LSSC 2007) was held in Sozopol, Bulgaria, June 5–9, 2007. The conference was organized by the Institute for Parallel Processing at the Bulgarian Academy of Sciences in cooperation with SIAM (Society for Industrial and Applied Ma- ematics). Partial support was also provided from project BIS-21++ funded by the European Commission in FP6 INCO via grant 016639/2005. The conference was devoted to the 60th anniversary of Richard E. Professor Ewing is internati- ally well known with his contributions in applied mathematics, mathematical modeling, and large-scale scientific computations.
Knowledge Processing with Interval and Soft Computing
In particular, these chapters cover computing techniques for interval linear systems of equations, interval matrix singular-value decomposition, interval function approximation, and decision making with statistical and graph-based data processing. To enable these applications, the book presents a standards-based object-oriented interval computing environment in C++.
