Libros sobre el tema "Predictive simulation model"

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1

1962-, Bordons C., ed. Model predictive control. Berlin: Springer, 1999.

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2

Camacho, E. F. Model predictive control. London: Springer, 2003.

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3

Camacho, E. F. Model predictive control. 2a ed. New York: Springer, 2004.

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4

Richards, Thomas. A predictive model of Aboriginal archaeological site distribution in the Otway Range. [Melbourne]: Aboriginal Affairs Victoria, 1998.

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5

Bousfield, Wayne E. Application of predictive model to forecast Douglas-fir tussock moth defoliation. Missoula, Mont: USDA Forest Service, Northern Region, 1986.

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6

McMillan, Gregory K. Models unleashed: Virtual plant and model predictive control applications : a pocket guide. Research Triangle Park, NC: ISA, 2004.

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7

Bradley, John E. An archaeological survey and predictive model of selected areas of Utah's Cisco Desert. Salt Lake City, Utah: Bureau of Land Management, Utah State Office, 1986.

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8

Black, Kevin D. The Castle Valley archaeological project: An inventory and predictive model of selected tracts. Salt Lake City, Utah: Utah State Office, Bureau of Land Management, 1986.

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9

Black, Kevin D. The Castle Valley archaeological project: An inventory and predictive model of selected tracts. Salt Lake City, Utah: Utah State Office, Bureau of Land Management, 1986.

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10

Bradley, John E. An archaeological survey and predictive model of selected areas of Utah's Cisco Desert. Salt Lake City, Utah: Utah State Office, Bureau of Land Management, 1986.

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11

Bradley, John E. An archaeological survey and predictive model of selected areas of Utah's Cisco Desert. Salt Lake City, Utah: Utah State Office, Bureau of Land Management, 1986.

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12

Bradley, John E. An archaeological survey and predictive model of selected areas of Utah's Cisco Desert. Salt Lake City, Utah: Utah State Office, Bureau of Land Management, 1986.

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13

J, Hunt R., Tonkin Matthew J, Groundwater Resources Program (U.S.) y Geological Survey (U.S.), eds. Approaches to highly parameterized inversion: A guide to using PEST for model-parameter and predictive-uncertainty analysis. Reston, Va: U.S. Dept. of the Interior, U.S. Geological Survey, 2011.

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14

Christoph, Helma, ed. Predictive toxicology. Boca Raton: Taylor & Francis, 2005.

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15

Arthur, Province Michael y United States. National Telecommunications and Information Administration., eds. An automated wide area prediction model for microwave common carrier links. [Washington, D.C.?]: U.S. Dept. of Commerce, National Telecommunications and Information Administration, 1990.

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16

Preisendorfer, Rudolph W. Simulation data sets for testing MOS (model output statistics) prediction methods. Seattle, Wash: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Pacific Marine Environmental Laboratory, 1985.

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17

McKay, Michael D. Evaluating prediction uncertainty. Washington, DC: The Commission, 1995.

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18

Rangwala, Huzefa, G. Karypis y G. Karypis. Introduction to protein structure prediction: Methods and algorithms. Hoboken, N.J: Wiley, 2010.

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19

Abarbanel, Henry. Predicting the Future: Completing Models of Observed Complex Systems. New York, NY: Springer New York, 2013.

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20

Chen, Chuin-Shan. Crack growth simulation and residual strength prediction in airplane fuselages. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1999.

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21

Bierbaum, Carl R. Task analysis of the UH-60 mission and decision rules for developing a UH-60 workload prediction model. Alexandria, VA: U.S. Army Research Institute for the Behavioral and Social Sciences, 1989.

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22

El-Fadeel, Salah Ibrahim Abd. A Mathematical Model for Calculating Non-Detection Probability of a Random Tour Target. Monterey, California: Naval Postgraduate School, 1985.

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23

National Research Council. Transportation Research Board., ed. Traffic flow theory: Simulation models, macroscopic flow relationships, and flow estimation and prediction. Washington, DC: National Academy Press, 1998.

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24

Hughes, Garrett A. Key algorithms used in GR02: A computer simulation model for predicting tree and stand growth. [Broomall, Pa.]: U.S. Dept. of Agriculture, Forest Service, Northeastern Forest Experiment Station, 1985.

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25

A, Viterna Larry y Lewis Research Center, eds. ETARA PC version 3.3 user's guide: Reliability, availability, maintainability simulation model. Cleveland, Ohio: NASA Lewis Research Center, 1991.

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26

A, Viterna Larry y Lewis Research Center, eds. ETARA PC version 3.3 user's guide: Reliability, availability, maintainability simulation model. Cleveland, Ohio: NASA Lewis Research Center, 1991.

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27

A, Viterna Larry y Lewis Research Center, eds. ETARA PC version 3.3 user's guide: Reliability, availability, maintainability simulation model. Cleveland, Ohio: NASA Lewis Research Center, 1991.

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28

National Institute of Standards and Technology (U.S.), ed. The zone fire model JET: A model for the prediction of detector activation and gas temperature in the presence of a smoke layer. Gaithersburg, Md: U.S. Dept. of Commerce, Technology Administration, National Institute of Standards and Technology, 1999.

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29

Mass, Clifford. A next-generation land surface model for the prediction of pavement temperature. [Olympia, Wash.]: Washington State Dept. of Transportation, 2003.

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30

Wu, Helen. Evolutionary development of the Simulation by Logical Modeling System (SIBYL). [Washington, DC: National Aeronautics and Space Administration, 1995.

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31

Chen, X. Modelling and predicting textile behaviour. Cambridge: Woodhead Publishing, 2010.

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32

Brenner, Martin J. On-line robust modal stability prediction using wavelet processing. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1998.

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33

Rick, Lind y Dryden Flight Research Facility, eds. On-line robust modal stability prediction using wavelet processing. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1998.

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34

Rick, Lind y Dryden Flight Research Facility, eds. On-line robust modal stability prediction using wavelet processing. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1998.

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35

Rick, Lind y Dryden Flight Research Facility, eds. On-line robust modal stability prediction using wavelet processing. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1998.

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36

Rick, Lind y Dryden Flight Research Facility, eds. On-line robust modal stability prediction using wavelet processing. Edwards, Calif: National Aeronautics and Space Administration, Dryden Flight Research Center, 1998.

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37

Ontario. Ministry of Municipal Affairs. Lakeshore Capacity Study: Integration : a simulation model for predicting the impact of lakeshore cottages on the environment. Toronto, Ont: Ontario Ministry of Municipal Affairs, 1986.

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38

Konnie, Wescott y Brandon R. Joe 1967-, eds. Practical applications of GIS for archaeologists: A predictive modeling toolkit. London: Taylor and Francis, 2000.

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39

Murray, Dryer y Space Environment Laboratory, eds. The interplanetary shock propagation model: A model for predicting solar-flare-caused geomagnetic storms, based on the 2 1/2 D, MHD numerical simulation results from the interplanetary global model (2D IGM). Boulder, Colo: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Laboratory ; Springfield, VA, 1995.

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40

Murray, Dryer y Space Environment Laboratory, eds. The interplanetary shock propagation model: A model for predicting solar-flare-caused geomagnetic storms, based on the 2 1/2 D, MHD numerical simulation results from the interplanetary global model (2D IGM). Boulder, Colo: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Laboratory ; Springfield, VA, 1995.

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41

Murray, Dryer y Space Environment Laboratory, eds. The interplanetary shock propagation model: A model for predicting solar-flare-caused geomagnetic storms, based on the 2 1/2 D, MHD numerical simulation results from the interplanetary global model (2D IGM). Boulder, Colo: National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Space Environment Laboratory ; Springfield, VA, 1995.

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42

Rangwala, Huzefa. Introduction to protein structure prediction: Methods and algorithms. Hoboken, N.J: Wiley, 2010.

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43

Broughton, J. Simulation of the structure and predictive fouling of cellular ceramic membranes in both dead end and cross flow modes. Manchester: UMIST, 1994.

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44

Facility, Dryden Flight Research, ed. A simulation study of turbofan engine deterioration estimation using Kalman filtering techniques. Edwards, Calif: National Aeronautics and Space Administration, Ames Research Center, Dryden Flight Research Facility, 1991.

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45

Barber, M. Craig. FGETS (Food and Gill Exchange of Toxic Substances): A simulation model for predicting bioaccumulation of nonpolar organic pollutants by fish. Athens, GA: U.S. Environmental Protection Agency, Environmental Research Laboratory, 1988.

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46

Barber, M. Craig. FGETS (Food and Gill Exchange of Toxic Substances): A simulation model for predicting bioaccumulation of nonpolar organic pollutants by fish. Athens, GA: U.S. Environmental Protection Agency, Environmental Research Laboratory, 1988.

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47

Burnett, Robert D. Predictive simulation of alternatives for managing the water resources of North Fork Solomon River Valley between Kirwin Dam and Waconda Lake, north-central Kansas. Lawrence, Kan: U.S. Dept. of Interior, Geological Survey, 1985.

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48

United States. National Aeronautics and Space Administration., ed. An RL10A-3-3A rocket engine model using the rocket engine transient simulator (ROCETS) software. [Washington, D.C.]: National Aeronautics and Space Administration, 1993.

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49

Huang, Biao. Dynamic modelling and predictive control in solid oxide fuel cells: First principle and data-based approaches. Hoboken: John Wiley & Sons Inc., 2013.

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50

Baranick, Michael, Mark Abdollahian, Brian Efird y Jack Kugler. Senturion: A predictive Polititcal Simulation Model. CreateSpace Independent Publishing Platform, 2012.

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