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Titlebook: Entropy Optimization and Mathematical Programming; S.-C. Fang,J. R. Rajasekera,H.-S. J. Tsao Book 1997 Springer Science+Business Media New

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发表于 2025-3-21 17:48:20 | 显示全部楼层 |阅读模式
书目名称Entropy Optimization and Mathematical Programming
编辑S.-C. Fang,J. R. Rajasekera,H.-S. J. Tsao
视频video
丛书名称International Series in Operations Research & Management Science
图书封面Titlebook: Entropy Optimization and Mathematical Programming;  S.-C. Fang,J. R. Rajasekera,H.-S. J. Tsao Book 1997 Springer Science+Business Media New
描述Entropy optimization is a useful combination of classicalengineering theory .(entropy). with mathematical optimization. Theresulting .entropy. .optimization models. have proved theirusefulness with successful applications in areas such as imagereconstruction, pattern recognition, statistical inference, queuingtheory, spectral analysis, statistical mechanics, transportationplanning, urban and regional planning, input-output analysis,portfolio investment, information analysis, and linear and nonlinearprogramming. .While entropy optimization has been used in different fields, a goodnumber of applicable solution methods have been loosely constructedwithout sufficient mathematical treatment. A systematic presentationwith proper mathematical treatment of this material is needed bypractitioners and researchers alike in all application areas. Thepurpose of this book is to meet this need. .Entropy Optimizationand. .Mathematical Programming. offers perspectives that meetthe needs of diverse .user communities. so that the users canapply .entropy. .optimization techniques. with completecomfort and ease. With this consideration, the authors focus on theentropy optimization problems in finite di
出版日期Book 1997
关键词Optimization Methods; Pattern Recognition; linear optimization; nonlinear optimization; optimization
版次1
doihttps://doi.org/10.1007/978-1-4615-6131-6
isbn_softcover978-1-4613-7810-5
isbn_ebook978-1-4615-6131-6Series ISSN 0884-8289 Series E-ISSN 2214-7934
issn_series 0884-8289
copyrightSpringer Science+Business Media New York 1997
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发表于 2025-3-21 23:40:01 | 显示全部楼层
Entropy Optimization Models,, those disciplines include statistical mechanics, thermodynamics, statistical parameter estimation and inference, economics, business and finance, nonlinear spectral analysis, pattern recognition, transportation, urban and regional planning, queueing theory, and linear and nonlinear programming. In
发表于 2025-3-22 03:00:11 | 显示全部楼层
Entropy Optimization Methods: Linear Case,ion of 0 ln 0 = 0, we define the quantity . to be the cross-entropy of x with respect to ., in a general sense. Note that when x and p are both probability distributions, i.e., . this quantity becomes the commonly defined cross-entropy between the two probability distributions (see Chapter 1).
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,,-Norm Perturbation Approach: A Generalization of Entropic Perturbation,ntly in developing interior-point methods [3, 17, 4, 13, 18]. However, the idea of perturbing the feasible region has not been fully explored. This chapter focuses on this idea and discusses a particular approach involving the ..-norm of a vector measure of constraint violation. Three topics will be
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Uranium - Past and Future Challengestion approach by using the entropic function, . for solving four classes of problems, namely, linear programming problems in Karmarkar’s form, linear programming programs in standard form, convex quadratic programming problems, and linear and convex quadratic semi-infinite programming problems.
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Introduction to Entropy and Entropy Optimization Principles,ussed along with references to the existing literature. The chapter consists of two sections. Section 1.1 introduces the concept of entropy, and Section 1.2 classifies different entropy optimization problems to be studied in this book.
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0884-8289 y. .optimization models. have proved theirusefulness with successful applications in areas such as imagereconstruction, pattern recognition, statistical inference, queuingtheory, spectral analysis, statistical mechanics, transportationplanning, urban and regional planning, input-output analysis,port
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