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Decision Making Under Uncertainty: Energy and Power

Posted By: AvaxGenius

Date: 1 Mar 2024 05:50:44

Decision Making Under Uncertainty: Energy and Power by Claude Greengard, Andrzej Ruszczynski
English | PDF | 2002 | 166 Pages | ISBN : 0387954651 | 17.2 MB

In the ideal world, major decisions would be made based on complete and reliable information available to the decision maker. We live in a world of uncertainties, and decisions must be made from information which may be incomplete and may contain uncertainty. The key mathematical question addressed in this volume is "how to make decision in the presence of quantifiable uncertainty." The volume contains articles on model problems of decision making process in the energy and power industry when the available information is noisy and/or incomplete. The major tools used in studying these problems are mathematical modeling and optimization techniques; especially stochastic optimization. These articles are meant to provide an insight into this rapidly developing field, which lies in the intersection of applied statistics, probability, operations research, and economic theory. It is hoped that the present volume will provide entry to newcomers into the field, and stimulation for further research.

Stochastic Optimization Stochastic Programming Science Mathematical Modeling Science Industrial Mathematics Environmental Management

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Computational Intelligence in Pattern Recognition: Proceedings of CIPR 2019 (Repost)

Posted By: AvaxGenius

Date: 8 Oct 2022 10:56:32

Computational Intelligence in Pattern Recognition: Proceedings of CIPR 2019 (Repost)

This book presents practical development experiences in different areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.

Science Information Retrieval Big Data Analytics Mathematics Genetic fuzzy system Development Genetic Algorithms Text Mining Swarn Intelligence Stochastic Optimization Bioinformatics Fuzzy system Cryptography Programming Patterns Algorithms Engineering Optical Networks Social Network Analysis Intelligent Algorithms Pattern Recognition

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Algorithms for Reinforcement Learning

Posted By: AvaxGenius

Date: 23 Sep 2022 16:01:07

Algorithms for Reinforcement Learning by Csaba Szepesvári
English | PDF | 2010 | 103 Pages | ISBN : 1608454924 | 1.6 MB

Reinforcement learning is a learning paradigm concerned with learning to control a system so as to maximize a numerical performance measure that expresses a long-term objective. What distinguishes reinforcement learning from supervised learning is that only partial feedback is given to the learner about the learner's predictions. Further, the predictions may have long term effects through influencing the future state of the controlled system. Thus, time plays a special role. The goal in reinforcement learning is to develop efficient learning algorithms, as well as to understand the algorithms' merits and limitations. Reinforcement learning is of great interest because of the large number of practical applications that it can be used to address, ranging from problems in artificial intelligence to operations research or control engineering. In this book, we focus on those algorithms of reinforcement learning that build on the powerful theory of dynamic programming. We give a fairly comprehensive catalog of learning problems, describe the core ideas, note a large number of state of the art algorithms, followed by the discussion of their theoretical properties and limitations.

Science Markov Decision Processes Control Value Prediction Problems Reinforcement Learning Algorithms Machine Learning Artificial Intelligence Stochastic Optimization

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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

Posted By: readerXXI

Date: 26 Jun 2022 02:32:08

Statistics Stochastic Optimization Algorithms Natural Computing

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Deep Statistical Comparison for Meta-heuristic Stochastic Optimization Algorithms

Posted By: readerXXI

Date: 24 Jun 2022 04:15:07

Statistics Stochastic Optimization Algorithms Natural Computing

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Stochastic Optimization

Posted By: AvaxGenius

Date: 10 Jun 2022 07:39:16

Stochastic Optimization by Johannes Josef Schneider
English | PDF | 2006 | 550 Pages | ISBN : 3540345590 | 40.6 MB

The search for optimal solutions pervades our daily lives. From the scientific point of view, optimization procedures play an eminent role whenever exact solutions to a given problem are not at hand or a compromise has to be sought, e.g. to obtain a sufficiently accurate solution within a given amount of time. This book addresses stochastic optimization procedures in a broad manner, giving an overview of the most relevant optimization philosophies in the first part. The second part deals with benchmark problems in depth, by applying in sequence a selection of optimization procedures to them. While having primarily scientists and students from the physical and engineering sciences in mind, this book addresses the larger community of all those wishing to learn about stochastic optimization techniques and how to use them.

Science Monte Carlo Constraint Satisfaction algorithms Markov Random Numbers Simulated Annealing Stochastic Optimization genetic algorithms Computer Science Artificial Intelligence Optimization Probability Theory Computational Physics Scientific Computation Computational Science Computational Intelligence Mathematics

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Intelligent Control: A Stochastic Optimization Based Adaptive Fuzzy Approach (Repost)

Posted By: AvaxGenius

Date: 27 Apr 2021 03:48:50

Intelligent Control: A Stochastic Optimization Based Adaptive Fuzzy Approach (Repost)

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H∞ theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H∞ theory to develop such hybrid control strategies.

Development Biology Genetics Optimization Genetic fuzzy system Fuzzy system Programming IT Science Mathematics Algorithms Patterns Engineering Intelligent Control algorithms Stochastic Optimization Fuzzy Technology ePub Physics

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Stochastic Simulation: Algorithms and Analysis

Posted By: AvaxGenius

Date: 3 Jan 2021 19:50:52

Stochastic Simulation: Algorithms and Analysis by Søren Asmussen
English | PDF | 490 Pages | 2007 | ISBN : 038730679X | 10.6 MB

Sampling-based computational methods have become a fundamental part of the numerical toolset of practitioners and researchers across an enormous number of different applied domains and academic disciplines.

Gaussian process Patterns Science optimization Analysis Algorithms Lévy process Engineering Monte Carlo method algorithms Mathematics Stochastic Optimization Markov chain Technology Stochastic Differential Equations

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Data Analysis and Optimization for Engineering and Computing Problems

Posted By: AvaxGenius

Date: 8 Sep 2020 13:58:44

Data Analysis and Optimization for Engineering and Computing Problems: Proceedings of the 3rd EAI International Conference on Computer Science and Engineering and Health Services by Pandian Vasant
English | PDF,EPUB | 2020 | 279 Pages | ISBN : 3030481484 | 55.5 MB

This book presents the proceedings of The EAI International Conference on Computer Science: Applications in Engineering and Health Services (COMPSE 2019). The conference highlighted the latest research innovations and applications of algorithms designed for optimization applications within the fields of Science, Computer Science, Engineering, Information Technology, Management, Finance and Economics and Health Systems.

Development Meta-Heuristics SQL Programming Science Machine Learning Mathematics Patterns Engineering Algorithms Computer Science Databases Stochastic Optimization Technology ePub

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Relative Optimization of Continuous-Time and Continuous-State Stochastic Systems

Posted By: AvaxGenius

Date: 14 May 2020 04:28:50

This monograph applies the relative optimization approach to time nonhomogeneous continuous-time and continuous-state dynamic systems. The approach is intuitively clear and does not require deep knowledge of the mathematics of partial differential equations. The topics covered have the following distinguishing features: long-run average with no under-selectivity, non-smooth value functions with no viscosity solutions, diffusion processes with degenerate points, multi-class optimization with state classification, and optimization with no dynamic programming.

Development ePub Dynamic Programming Stochastic Control Sensitivity Analysis Programming Performance Optimization Ito–Tanaka formula Mathematics Patterns Engineering Algorithms Continuous-Time Dynamical Systems Perturbation Analysis Science Stochastic Optimization Technology Operations Research

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Computational Intelligence in Pattern Recognition: Proceedings of CIPR 2019

Posted By: AvaxGenius

Date: 4 May 2020 12:59:15

Information Retrieval Big Data Analytics Mathematics Genetic fuzzy system Development Genetic Algorithms Cryptography Fuzzy system CIPR 2019 Bioinformatics Stochastic Optimization Swarn Intelligence Text Mining Science Programming Patterns Algorithms Databases Hybrid Computing Communication Image Processing Intelligent Algorithms for Pattern Recognition Social Network Analysis Optical Networks Engineering SQL Technology ePub

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Proceedings of the Sixth International Forum on Decision Sciences

Posted By: AvaxGenius

Date: 3 May 2020 02:24:18

The proceedings focus on selected aspects of the current and upcoming trends in transportation, logistics and decision-making. In detail the included scientific papers analyze the problem of Decision Making under Uncertainty, Stochastic Optimization, Transportation, Logistics and Intelligent Business. The variety of the papers delivers added value for both scholars and practitioners. This book is the documentation of the symposium “The Sixth International Forum on Decision Sciences”, which took place in Jinan, Shandong province, China.

Logistics Transportation Business Intelligent Business Decision Making under Uncertainty Stochastic Optimization ePub

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