| 000 | 03414nam a22005535i 4500 | ||
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| 001 | 978-981-97-2435-2 | ||
| 003 | DE-He213 | ||
| 005 | 20251030112238.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 240527s2024 si | s |||| 0|eng d | ||
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_a9789819724352 _9978-981-97-2435-2 |
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_a10.1007/978-981-97-2435-2 _2doi |
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| 050 | 4 | _aT57.6-.97 | |
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| 100 | 1 |
_aRam, Bhagwat. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _977653 |
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| 245 | 1 | 0 |
_aUnconstrained Optimization and Quantum Calculus _h[electronic resource] / _cby Bhagwat Ram, Shashi Kant Mishra, Kin Keung Lai, Predrag Rajković. |
| 250 | _a1st ed. 2024. | ||
| 264 | 1 |
_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2024. |
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| 300 |
_aXV, 138 p. 41 illus., 35 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aUncertainty and Operations Research, _x2195-9978 |
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| 505 | 0 | _aHistorical Note on Unconstrained Optimization and Quantum Calculus -- Basics of Unconstrained Optimization and Quantum Calculus -- Quantum-Steepest Descent Method with Quasi-Fejér Convergence -- Quantum- Fletcher-Reeves Conjugate Gradient Method -- Quantum-Polak-Ribière-Polyak -- Conjugate Gradient Method.-Quantum-Dai-Yuan Conjugate Gradient Method -- Quantum-Broyden-Fletcher-Goldfarb-Shanno Method -- Quantum-Limited Memory Broyden-Fletcher-Goldfarb-Shanno Method. | |
| 520 | _aThis 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. | ||
| 650 | 0 |
_aOperations research. _957943 |
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| 650 | 1 | 4 |
_aOperations Research and Decision Theory. _967143 |
| 700 | 1 |
_aMishra, Shashi Kant. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _977654 |
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| 700 | 1 |
_aLai, Kin Keung. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _977655 |
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| 700 | 1 |
_aRajković, Predrag. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _977656 |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9789819724345 |
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_iPrinted edition: _z9789819724369 |
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_iPrinted edition: _z9789819724376 |
| 830 | 0 |
_aUncertainty and Operations Research, _x2195-9978 _977657 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-981-97-2435-2 |
| 912 | _aZDB-2-BUM | ||
| 912 | _aZDB-2-SXBM | ||
| 999 |
_c60225 _d60225 |
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