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Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on;
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optimization has been receiving considerable attention in the past two decades. Of the two types of techniques for global optimization, stochastic;
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solving optimization problems are of deterministic or stochastic type. Of these, stochastic techniques can solve any type of optimization problems;
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Stochastic optimization is vital to making sound engineering and business decisions under uncertainty. While the limited capability;
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book also shows how to apply approximative solution techniques. Several deterministic and stochastic approximation methods are provided: Taylor;
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Stochastic Process Optimization using Aspen (R) Plus Bookshop Category: Chemical Engineering Optimization can be simply;
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. Key Features: * The book links simulation and optimization through numerical analyses and stochastic optimization techniques * Includes;
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approaches/H theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic;
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of stochastic simulation optimization for complex discrete event systems. This book will introduce two important techniques initially proposed and;
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Portfolio Optimization with Different Information Flow recalls the stochastic tools and results concerning the stochastic;
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A unique interdisciplinary foundation for real-world problem solving Stochastic search and optimization techniques are used in a vast;
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designed. Many new engineering design applications based on stochastic optimization techniques in automotive, energy, military, naval;
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Optimization techniques in production management are becoming increasingly important for efficient and competitive manufacturing. This book;
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This book examines application and methods to incorporating stochastic parameter variations into the optimization process to decrease;
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This book examines application and methods to incorporating stochastic parameter variations into the optimization process to decrease;
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Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic;
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This text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift;
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Stochastic programming is the study of procedures for decision making under the presence of uncertainties and risks. Stochastic;
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-aware optimization; stochastic modeling for systems biology; biologically inspired network design.;
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This volume attempts to exhibit current research in stochastic integration, stochastic differential equations, stochastic optimization and;
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This volume attempts to exhibit current research in stochastic integration, stochastic differential equations, stochastic optimization and;
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Advanced Mathematical Tools for Automatic Control Engineers, Volume 2: Stochastic Techniques provides comprehensive discussions on;
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Stochastic global optimization methods and applications to chemical, biochemical, pharmaceutical and environmental processes presents;
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This books covers the broad range of research in stochastic models and optimization. Applications presented include networks, financial;
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, Levenberg-Marquardt algorithms, stochastic optimization, simulated annealing and statistical optimization. It studies the multi-objective;
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principles, potential and boundaries of applicability of stochastic global optimization techniques are examined in this book. A variety of issues;
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volume of the 4th GAMM/IFIP-Workshop on Stochastic Optimization: Numerical Methods and Technical Applications held June 27-29, 2000 at the;
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