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Books on the topic 'Computer Optimization of Parameters'

Author: Grafiati
Published: 4 June 2021
Last updated: 10 February 2022

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1

Romanovich, Statnikov Alexander, ed. The parameter space investigation method toolkit. Boston: Artech House, 2011.

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2

Bock, Hans Georg. Model Based Parameter Estimation: Theory and Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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3

Nemzow, Martin A. W. Computer performance optimization. New York: McGraw-Hill, 1994.

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4

Osterhage, Wolfgang W. Computer Performance Optimization. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-29971-1.

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5

Computer performance optimization. New York: McGraw-Hill, 1994.

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6

Treiber, Marco Alexander. Optimization for Computer Vision. London: Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5283-5.

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7

FORTRAN optimization. London: Academic Press, 1985.

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8

Trosset, Michael W. Numerical optimization using computer experiments. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1997.

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9

Abidi, Mongi A., Andrei V. Gribok, and Joonki Paik. Optimization Techniques in Computer Vision. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-46364-3.

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10

Leondes, Cornelius T. Optimization techniques. San Diego: Academic Press, 1998.

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11

Moayyedian, Mehdi. Intelligent Optimization of Mold Design and Process Parameters in Injection Molding. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-03356-9.

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12

Generalized optimal control of linear systems with distributed parameters. Dordrecht: Kluwer Academic Publishers, 2002.

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13

Zakharova, A. I. Estimation of seismicity parameters using a computer. Rotterdam: Balkema, 1986.

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14

Sasao, Tsutomu. Logic Synthesis and Optimization. Boston, MA: Springer US, 1993.

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15

Nemzow, Martin A. W. LAN performance optimization. Edited by Black Uyless D. Blue Ridge Summit, Pa: Windcrest/McGraw-Hill, 1993.

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16

Perkins, Todd. Search engine optimization for Flash. Sebastopol, CA: O'Reilly Media, Inc., 2009.

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17

Website optimization. Farnham: O'Reilly, 2008.

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18

Integrated methods for optimization. New York: Springer, 2012.

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19

Kreines, David C. Oracle Initialization Parameters: Pocket Reference. Beijing: O'Reilly, 2004.

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20

Generalized filter design by computer optimization. Boston: Artech House, 1998.

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21

1941-, Rokne J., ed. New computer methods for global optimization. Chichester, West Sussex, England: Horwood, 1988.

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22

Paschos, Vangelis Th, ed. Combinatorial Optimization and Theoretical Computer Science. London, UK: ISTE, 2008. http://dx.doi.org/10.1002/9780470611098.

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23

Norman, Harrell J. Van. LAN/WAN optimization techniques. Boston: Artech House, 1992.

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24

Otar, Cemil. Heat exchanger network optimization. Houston: Gulf Pub. Co., Book Division, 1986.

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25

Edward, Whalen. Oracle performance tuning and optimization. Indianapolis, IN: Howard Sams Pub., 1996.

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26

Grappone, Jennifer. Search Engine Optimization. New York: John Wiley & Sons, Ltd., 2008.

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27

1960-, Wright Stephen J., ed. Optimization software guide. Philadelphia: Society for Industrial and Applied Mathematics, 1993.

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28

Yang, Xiaoqi. Optimization Methods and Applications. Boston, MA: Springer US, 2001.

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29

Abrash, Michael. Zen of code optimization. Scottsdale, Ariz: Coriolis Group Books, 1994.

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30

Lange, Kenneth. Optimization. 2nd ed. New York, NY: Springer New York, 2013.

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31

Khoshnevisan, Mohammad. Artificial intelligence and responsive optimization. 2nd ed. Phoenix: Xiquan, 2003.

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32

Khoshnevisan, Mohammad. Artificial intelligence and responsive optimization. Phoenix: Xiquan, 2003.

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33

Glas, Cees A. W. Modeling variability in item parameters in educational measurement. Newtown, PA: Law School Admission Council, 2006.

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34

Ansari, Nirwan. Computational Intelligence for Optimization. Boston, MA: Springer US, 1997.

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35

VSAM: Guide to optimization and design. Wellesley, Mass: QED Information Sciences, 1990.

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36

L, Crawford Isom, ed. Software optimization for high-performance computing. Upper Saddle River, N.J: Prentice Hall PTR, 2000.

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37

Irvin, Lustig, ed. The OPL optimization programming language. Cambridge, Mass: MIT Press, 1999.

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38

Kuck, Sharon McCure. Network query optimization made easy. Urbana, Ill. (1304 W. Springfield, Urbana 61801): Dept. of Computer Science, University of Illinois at Urbana-Champaign, 1985.

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39

Pardalos, P. M. (Panos M.), 1954- and SpringerLink (Online service), eds. Mathematical Aspects of Network Routing Optimization. New York, NY: Springer Science+Business Media, LLC, 2011.

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40

Nash, John C. Nonlinear Parameter Optimization Using R Tools. Wiley & Sons, Incorporated, John, 2014.

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41

Nonlinear Parameter Optimization Using R Tools. John Wiley & Sons Inc, 2014.

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42

S, Salzar Robert, and United States. National Aeronautics and Space Administration., eds. Optimization of residual stresses in MMC's through the variation of interfacial layer architectures and processing parameters. [Washington, DC]: National Aeronautics and Space Administration, 1996.

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43

S, Salzar Robert, and United States. National Aeronautics and Space Administration., eds. Optimization of residual stresses in MMC's through the variation of interfacial layer architectures and processing parameters. [Washington, DC]: National Aeronautics and Space Administration, 1996.

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44

Lee, Herbert K. H., Matthew Taddy, Robert Gramacy, and Genetha Gray. Designing and analysing a circuit device experiment using treed Gaussian processes. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.28.

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Abstract:
This article describes a new circuit device, developed in collaboration with scientists at Sandia National Laboratories, based on treed Gaussian processes (TGP). The circuit devices under study are bipolar junction transistors, which are used to amplify electrical current. To aid with the design of the device, a computer model predicts its peak output as a function of the input dosage and a number of design parameters. The methodology also involves a novel sequential design procedure to generate data to fit the emulator. Both physical and computer simulation experiments are performed, and the results show that the TGP model can be useful for spatial data and semiparametric regression in the context of a computer experiment for designing a circuit device, for sequential design of (computer) experiments, sequential robust local optimization, validation, calibration, and sensitivity analysis.
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45

Rannacher, Rolf, Willi Jäger, Hans Georg Bock, Thomas Carraro, Johannes P. Schlöder, and Stefan Körkel. Model Based Parameter Estimation: Theory and Applications. Springer, 2015.

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46

Jäger, Willi, Hans Georg Bock, and Thomas Carraro. Model Based Parameter Estimation: Theory and Applications. Springer, 2013.

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47

S, Salzar Robert, and Langley Research Center, eds. Optimization of residual stresses in MMC's through process parameter control and the use of heterogeneous compensating/complaint interfacial layers: OPTCOMP2 user's guide. Hampton, Va: National Aeronautics and Space Administration, 1996.

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48

S, Salzar Robert, and Langley Research Center, eds. Optimization of residual stresses in MMC's through process parameter control and the use of heterogeneous compensating/complaint interfacial layers: OPTCOMP2 user's guide. Hampton, Va: National Aeronautics and Space Administration, 1996.

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49

Machining Dynamics and Parameters Process Optimization. MDPI, 2021. http://dx.doi.org/10.3390/books978-3-0365-0295-3.

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50

M, Adelman Howard, Sobieski Jaroslaw, and Langley Research Center, eds. Optimization for minimum sensitivity to uncertain parameters. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1994.

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