Bhagwat Ram (48 results)

Condition: New. pp. 240.

Condition: New.

Condition: As New. Unread book in perfect condition.

Hardback. Condition: New. 2019 ed. This book discusses unconstrained optimization with R-a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.…

Condition: New.

Condition: New. 1st ed. 2019 edition NO-PA16APR2015-KAP.

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Condition: New. pp. XVI, 304 765 illus., 50 illus. in color. 1 Edition NO-PA16APR2015-KAP.

Condition: New. Discusses all major aspects of unconstrained optimization with RPresents important, basic methods with their algorithms, analysis, and proofsIncludes manually worked examples, R scripts, and real-world applicationsProvides exercises .

Hardback. Condition: New. 2019 ed. This book discusses unconstrained optimization with R-a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture.…

Condition: New.

Condition: As New. Unread book in perfect condition.

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a better clue to apply quantum derivative instead of classical derivative in the modified optimization methods, compared with the competing books which employ a number of standard derivative optimization techniques to address large-scale, unconstrained optimization issues. Essential proofs and applications of the various techniques are given in simple manner without sacrificing accuracy. New concepts are illustrated with the help of examples. This book presents the theory and application of given optimization techniques in generalized and comprehensive manner. Methods such as steepest descent, conjugate gradient and BFGS are generalized and comparative analyses will show the efficiency of the techniques.…

Hardcover. Condition: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condition: New.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book provides a better clue to apply quantum derivative instead of classical derivative in the modified optimization methods, compared with the competing books which employ a number of standard derivative optimization techniques to address large-scale, unconstrained optimization issues. Essential proofs and applications of the various techniques are given in simple manner without sacrificing accuracy. New concepts are illustrated with the help of examples. This book presents the theory and application of given optimization techniques in generalized and comprehensive manner. Methods such as steepest descent, conjugate gradient and BFGS are generalized and comparative analyses will show the efficiency of the techniques.…

Condition: New.

Condition: New.

Condition: New. 2024th edition NO-PA16APR2015-KAP.

Condition: As New. Unread book in perfect condition.

Condition: New. pp. 327.

Condition: As New. Unread book in perfect condition.

Hardcover. Condition: Brand New. 153 pages. 9.25x6.10x9.25 inches. In Stock.

Condition: New. pp. 327.

Condition: New.

Condition: New. pp. 327.

Hardcover. Condition: Brand New. 336 pages. 9.25x6.25x1.25 inches. In Stock.

Condition: New. Print on Demand pp. 240.

Condition: New. PRINT ON DEMAND pp. 240.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book discusses unconstrained optimization with R-a free, open-source computing environment, which works on several platforms, including Windows, Linux, and macOS. The book highlights methods such as the steepest descent method, Newton method, conjugate direction method, conjugate gradient methods, quasi-Newton methods, rank one correction formula, DFP method, BFGS method and their algorithms, convergence analysis, and proofs. Each method is accompanied by worked examples and R scripts. To help readers apply these methods in real-world situations, the book features a set of exercises at the end of each chapter. Primarily intended for graduate students of applied mathematics, operations research and statistics, it is also useful for students of mathematics, engineering, management, economics, and agriculture. 320 pp. Englisch.…