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Computer science --- Discrete mathematics --- Graph algorithms --- Algorithmes de graphes --- Graph algorithms.
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Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory is a survey of some important theoretical contributions, many of which have been proposed and developed in the Foundations of Genetic Algorithms series of workshops. However, this theoretical work is still rather fragmented, and the authors believe that it is the right time to provide the field with a systematic presentation of the current state of theory in the form of a set of theoretical perspectives. The authors do this in the interest of providing students and researchers with a balanced foundational survey of some recent research on GAs. The scope of the book includes chapter-length discussions of Basic Principles, Schema Theory, "No Free Lunch", GAs and Markov Processes, Dynamical Systems Model, Statistical Mechanics Approximations, Predicting GA Performance, Landscapes and Test Problems.
Genetic algorithms --- Operations Research --- Civil & Environmental Engineering --- Engineering & Applied Sciences --- Computer science --- Artificial intelligence. Robotics. Simulation. Graphics --- GAs (Algorithms) --- Genetic searches (Algorithms) --- Algorithms --- Combinatorial optimization --- Evolutionary computation --- Genetic programming (Computer science) --- Learning classifier systems --- Genetic algorithms.
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Calendar --- Computer algorithms. --- Chronology, Historical --- Calendrier --- Algorithmes --- Chronologie historique --- Mathematics --- Conversion tables --- Early works to 1800 --- Mathématiques --- Conversion, Tables de --- Ouvrages avant 1800 --- 930.24 --- Historische chronologie --- 930.24 Historische chronologie --- Mathématiques --- Computer algorithms --- Algorithms --- Annals --- Dates (Chronology) --- Historical chronology --- History --- World history --- Computus --- Astronomy --- Chronology
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Mathematical statistics --- Basic Sciences. Statistics --- Data processing. --- Mathematical Statistics. --- Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- -Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- -681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- 681.3*G3 --- Data processing --- S-Plus. --- SPlus --- Programming --- Statistique mathématique --- Informatique
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Neural networks (Computer science) --- Fuzzy logic --- Genetic algorithms --- Information theory --- Réseaux neuronaux (Informatique) --- Logique floue --- Algorithmes génétiques --- Théorie de l'information
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Mathematical optimization --- Fuzzy logic --- Fuzzy sets --- Fuzzy algorithms --- Decision making --- Mathematical models --- Optimisation mathématique --- Ensembles flous --- Prise de décision --- Decision making. --- Fuzzy sets. --- Mathematical optimization. --- Optimization (Mathematics) --- Optimization techniques --- Optimization theory --- Systems optimization --- Sets, Fuzzy --- Deciding --- Decision (Psychology) --- Decision analysis --- Decision processes --- Making decisions --- Management --- Management decisions --- Mathematical analysis --- Maxima and minima --- Operations research --- Simulation methods --- System analysis --- Fuzzy mathematics --- Set theory --- Choice (Psychology) --- Problem solving --- Algorithms --- Cluster set theory --- Nonlinear logic --- Logic, Symbolic and mathematical --- Fuzzy systems --- Besliskunde. --- Fuzzy theorie. --- Decision theory. --- Fuzzy theory. --- Fuzzy logic. --- Fuzzy algorithms. --- Mathematical models.
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Experimental algorithmics, as its name indicates, combines algorithmic work and experimentation: algorithms are not just designed, but also implemented and tested on a variety of instances. Perhaps the most important lesson in this process is that designing an algorithm is but the first step in the process of developing robust and efficient software for applications. Based on a seminar held at Dagstuhl Castle, Germany in September 2000, this state-of-the-art survey presents a coherent survey of the work done in the area so far. The 11 carefully reviewed chapters provide complete coverage of all current topics in experimental algorithmics.
Computer algorithms. --- Data structures (Computer science) --- Application software --- Development of application software --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- Development. --- Computer science. --- Data structures (Computer science). --- Algorithms. --- Numerical analysis. --- Computer science --- Computer Science. --- Computer Science, general. --- Data Structures. --- Algorithm Analysis and Problem Complexity. --- Numeric Computing. --- Discrete Mathematics in Computer Science. --- Mathematics. --- Computer mathematics --- Discrete mathematics --- Electronic data processing --- Mathematical analysis --- Algorism --- Algebra --- Arithmetic --- File organization (Computer science) --- Abstract data types (Computer science) --- Informatics --- Science --- Mathematics --- Foundations --- Algorithms --- Computer algorithms --- Development --- Data structures (Computer scienc. --- Computer software. --- Electronic data processing. --- Computational complexity. --- Complexity, Computational --- Machine theory --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Software, Computer --- Computer systems --- Automation --- Computer science—Mathematics.
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Focusing on the computational aspects of statistics rather than the theoretical, this handbook uses a down-to-earth approach that makes statistics accessible to a wide range of users. The authors include algorithmic descriptions and MATLAB code for many of the latest methods in computational statistics. Detailed procedures are also included for readers who do not know MATLAB so they can implement the algorithms using other software packages. As a companion to the handbook, MATLAB functions are available for download that implement the techniques described in the text. This is the first book on the market to show how to use MATLAB to execute a wide variety of computational statistics methods and techniques.
Mathematical statistics --- Statistique mathématique --- Data processing. --- Informatique --- MATLAB. --- 681.3*G3 --- -519.50285 --- Mathematics --- Statistical inference --- Statistics, Mathematical --- Statistics --- Probabilities --- Sampling (Statistics) --- Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- Data processing --- Statistical methods --- MATLAB (Computer program) --- Matrix laboratory --- 681.3*G3 Probability and statistics: probabilistic algorithms (including Monte Carlo);random number generation; statistical computing; statistical software (Mathematics of computing) --- Statistique mathématique --- 519.50285 --- MATLAB (Computer file)
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This volume contains the 74 contributed papers and abstracts of 4 of the 5 invited talks presented at the 10th Annual European Symposium on Algorithms (ESA 2002), held at the University of Rome “La Sapienza”, Rome, Italy, 17-21 September, 2002. For the ?rst time, ESA had two tracks, with separate program committees, which dealt respectively with: – the design and mathematical analysis of algorithms (the “Design and An- ysis” track); – real-world applications, engineering and experimental analysis of algorithms (the “Engineering and Applications” track). Previous ESAs were held in Bad Honnef, Germany (1993); Utrecht, The Neth- lands (1994); Corfu, Greece (1995); Barcelona, Spain (1996); Graz, Austria (1997); Venice, Italy (1998); Prague, Czech Republic (1999); Saarbruc ¨ ken, Ger- ? many (2000), and Arhus, Denmark (2001). The predecessor to the Engineering and Applications track of ESA was the Annual Workshop on Algorithm En- neering (WAE). Previous WAEs were held in Venice, Italy (1997), Saarbruc ¨ ken, ? Germany (1998), London, UK (1999), Saarbru ¨cken, Germany (2000), and Arhus, Denmark (2001). The proceedings of the previous ESAs were published as Springer LNCS volumes 726, 855, 979, 1284, 1461, 1643, 1879, and 2161. The proceedings of WAEs from 1999 onwards were published as Springer LNCS volumes 1668, 1982, and 2161.
Computer algorithms --- Computer science. --- Computer programming. --- Data structures (Computer science). --- Algorithms. --- Numerical analysis. --- Computer science --- Computer graphics. --- Computer Science. --- Programming Techniques. --- Algorithm Analysis and Problem Complexity. --- Discrete Mathematics in Computer Science. --- Numeric Computing. --- Data Structures. --- Computer Graphics. --- Mathematics. --- Computer software. --- Computational complexity. --- Electronic data processing. --- Data structures (Computer scienc. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Complexity, Computational --- Electronic data processing --- Machine theory --- Software, Computer --- Computer systems --- Automatic drafting --- Graphic data processing --- Graphics, Computer --- Computer art --- Graphic arts --- Engineering graphics --- Image processing --- Informatics --- Science --- Automation --- Digital techniques --- Computer science—Mathematics. --- Information structures (Computer science) --- Structures, Data (Computer science) --- Structures, Information (Computer science) --- File organization (Computer science) --- Abstract data types (Computer science) --- Mathematical analysis --- Algorism --- Algebra --- Arithmetic --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Foundations --- Programming --- Computer algorithms - Congresses
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