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100   $a20140722d2014      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aNumerical Methods and Optimization $eA Consumer Guide /$fby Éric Walter
205   $a1st ed. 2014.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2014.
215   $a1 online resource (485 p.)
300   $aDescription based upon print version of record.
311   $a3-319-07670-1 
320   $aIncludes bibliographical references at the end of each chapters and index.
327   $aFrom Calculus to Computation -- Notation and Norms -- Solving Systems of Linear Equations -- Solving Other Problems in Linear Algebra -- Interpolation and Extrapolation -- Integrating and Differentiating Functions -- Solving Systems of Nonlinear Equations -- Introduction to Optimization -- Optimizing Without Constraint -- Optimizing Under Constraints -- Combinatorial Optimization -- Solving Ordinary Differential Equations -- Solving Partial Differential Equations -- Assessing Numerical Errors -- WEB Resources to go Further -- Problems.
330   $aInitial training in pure and applied sciences tends to present problem-solving as the process of elaborating explicit closed-form solutions from basic principles, and then using these solutions in numerical applications. This approach is only applicable to very limited classes of problems that are simple enough for such closed-form solutions to exist. Unfortunately, most real-life problems are too complex to be amenable to this type of treatment. Numerical Methods and Optimization ? A Consumer Guide presents methods for dealing with them. Shifting the paradigm from formal calculus to numerical computation, the text makes it possible for the reader to ·         discover how to escape the dictatorship of those particular cases that are simple enough to receive a closed-form solution, and thus gain the ability to solve complex, real-life problems; ·         understand the principles behind recognized algorithms used in state-of-the-art numerical software; <·         learn the advantages and limitations of these algorithms, to facilitate the choice of which pre-existing bricks to assemble for solving a given problem; and ·         acquire methods that allow a critical assessment of numerical results. Numerical Methods and Optimization ? A Consumer Guide will be of interest to engineers and researchers who solve problems numerically with computers or supervise people doing so, and to students of both engineering and applied math ematics.  .
606   $aApplied mathematics
606   $aEngineering mathematics
606   $aComputer science?Mathematics
606   $aCalculus of variations
606   $aNumerical analysis
606   $aMathematical and Computational Engineering$3https://scigraph.springernature.com/ontologies/product-market-codes/T11006
606   $aMath Applications in Computer Science$3https://scigraph.springernature.com/ontologies/product-market-codes/I17044
606   $aCalculus of Variations and Optimal Control; Optimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26016
606   $aNumerical Analysis$3https://scigraph.springernature.com/ontologies/product-market-codes/M14050
615  0$aApplied mathematics.
615  0$aEngineering mathematics.
615  0$aComputer science?Mathematics.
615  0$aCalculus of variations.
615  0$aNumerical analysis.
615 14$aMathematical and Computational Engineering.
615 24$aMath Applications in Computer Science.
615 24$aCalculus of Variations and Optimal Control; Optimization.
615 24$aNumerical Analysis.
676   $a004.0151
676   $a501.511
676   $a515.64
676   $a518
700   $aWalter$b Éric$4aut$4http://id.loc.gov/vocabulary/relators/aut$0338773
906   $aBOOK
912   $a9910299739803321
996   $aNumerical Methods and Optimization$91954335
997   $aUNINA