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Books on the topic 'Predictive parameters'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Evernden, J. F. Predictive model for important ground motion parameters associated with large and great earthquakes. U.S. Geological Survey, 1988.

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2

Evernden, J. F. Predictive model for important ground motion parameters associated with large and great earthquakes. U.S. G.P.O., 1988.

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3

Gross, Daniel. Data sources for parameters used in predictive modeling of fire growth and smoke spread. U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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4

Farmer, Stephen. Evaluation of some blood chemistry parameters as predictive indices of reproduction in captive Atlantic salmon (Salmo salar) brookstock. University of Prince Edward Island, 1988.

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5

Quintiere, James G. Significant parameters for predicting flame spread. U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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6

Quintiere, James G. Significant parameters for predicting flame spread. U.S. Dept. of Commerce, National Bureau of Standards, 1985.

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7

Lundholm, Steven E. Predicting antenna parameters from antenna physical dimensions. Naval Postgraduate School, 1993.

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8

Vladisavljevic, Tomislav. Predicting the T2K Neutrino Flux and Measuring Oscillation Parameters. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51174-6.

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9

Kaller, K. P. Skeletal and dentoalveolar parameters in the prediction of treatment outcome. University of Toronto, Faculty of Dentistry], 1998.

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10

Chen, S. A recursive prediction error parameter estimator for nonlinear models. University of Sheffield, Dept. of Control Engineering, 1988.

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11

John, Ferrante, and United States. National Aeronautics and Space Administration., eds. Determination of parameters of a new method for predicting alloy properties. National Aeronautics and Space Administration, 1992.

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12

1936-, Ferrante John, and United States. National Aeronautics and Space Administration., eds. Determination of parameters of a new method for predicting alloy properties. National Aeronautics and Space Administration, 1992.

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13

Center, Langley Research, ed. Comparing parameter estimation techniques for an electrical power transformer oil temperature prediction model. National Aeronautics and Space Administration, Langley Research Center, 1999.

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14

Holland, K. R. The prediction and measurement of the one-parameter behaviour of horns. University of Southampton, Institute of Sound and Vibration Research, 1990.

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15

Gerry, Donald D. Mathcad computer applications predicting antenna parameters from antenna physical dimensions and ground characteristics. Naval Postgraduate School, 1993.

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16

Quigley, Christopher Patrick. Prediction of journey parameters for the intelligent control of a hybrid electric vehicle. typescript, 1997.

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17

Amatya, Devendra. Lumped parameter models for predicting nitrogen loading from lower coastal plain watersheds. Water Resources Research Institute of the University of North Carolina, 2003.

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18

Conway, Thomas Michael. A computer programme for the prediction of hydrocyclone performance, parameters, and product-size distributions. Mintek (Ore-Dressing Division), printed and published by the Council for Mineral technology, 1985.

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19

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

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20

United States. National Aeronautics and Space Administration., ed. Effects of the cooling system parameters on heat transfer and performance of the PAFC stack during transient operation. Cleveland State University, 1992.

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21

United States. National Aeronautics and Space Administration., ed. Effects of the cooling system parameters on heat transfer and performance of the PAFC stack during transient operation. Cleveland State University, 1992.

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22

Endres, J. C. T. Scale-up and system influences on hydrodynamic and mass transfer model parameters (especially drop-side mass coefficients) for prediction of extraction column performance. UMIST, 1993.

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23

Geological Survey (U.S.), ed. Five computer programs for testing weighted residuals and calculating linear confidence and prediction intervals on results from the ground-water parameter-estimation computer program MODFLOWP. U.S. Dept. of the Interior, U.S. Geological Survey, 1994.

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24

Alvarez, Maria Jose Montes. Predictive parameters for macroangiopathy complications in insulin-dependent type diabetes mellitus. ProQuest / UMI, 2007.

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25

Alvarez, Maria Jose Montes. Predictive parameters for macroangiopathy complications in insulin-dependent type diabetes mellitus. ProQuest / UMI, 2007.

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26

Nickel, Thomas. Estimation of physical parameters in mechanical systems for predictive monitoring and diagnosis. 1999.

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27

Raalte-Drewes, van. Scaling Properties of Water: New Predictive Parameters (Water and Wastewater Process Technologies Series). IWA Publishing, 2004.

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28

Martich, Daniel, and Jody Cervenak. Integration of information technology in the ICU. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0007.

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As we look to the evolving health care industry with improved care quality, health outcomes, and cost parameters, the demands of the critical care environment require a transformation. Technology, process, and people are at the centre of this transformation. The power is in the knowledge that can be achieved and the process improvements that can be made through automation. Five major areas of technology evolution include workflow automation, information exchange, clinical decision support, and predictive modelling, remote monitoring, and data analytics. If designed properly, technology can res

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29

Wick, Wolfgang, Colin Watts, and Minesh P. Mehta. Oligodendroglial tumours. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199651870.003.0004.

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Concepts of diagnosis and treatment of oligodendroglial tumours have changed through clinical and translational studies over recent years. Diagnosis is now based on histopathological and integrated molecular information. The latter includes mutations in isocitrate dehydrogenase and the co-deletion of 1p/19q in the tumour tissue. In parallel, the long-term evaluation of large randomized trials performed in Europe and North America led to the current standard of a more aggressive chemoradiation regimen with procarbazine, CCNU (lomustine), and vincristine to optimize progression-free and overall

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30

Pitt, Matthew. Results of the clinical application of SPACE in suspected disorders of the neuromuscular junction. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198754596.003.0011.

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Findings in a large cohort of children with disorders of the neuromuscular junction are presented along with those in non-primary neuromuscular junction abnormalities. From these results it is possible to derive test parameters for stimulated potential analysis using concentric needle electrodes (SPACE) including sensitivity and specificity, along with positive and negative predictive values. The differences between performing stimulation techniques to determine jitter in children and adults are highlighted as are technical aspects and the effects of the differential diagnosis on interpretatio

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31

Cheng, Russell. Finite Mixture Examples; MAPIS Details. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198505044.003.0018.

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Two detailed numerical examples are given in this chapter illustrating and comparing mainly the reversible jump Markov chain Monte Carlo (RJMCMC) and the maximum a posteriori/importance sampling (MAPIS) methods. The numerical examples are the well-known galaxy data set with sample size 82, and the Hidalgo stamp issues thickness data with sample size 485. A comparison is made of the estimates obtained by the RJMCMC and MAPIS methods for (i) the posterior k-distribution of the number of components, k, (ii) the predictive finite mixture distribution itself, and (iii) the posterior distributions o

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32

Vladisavljevic, Tomislav. Predicting the T2K Neutrino Flux and Measuring Oscillation Parameters. Springer International Publishing AG, 2021.

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33

Vladisavljevic, Tomislav. Predicting the T2K Neutrino Flux and Measuring Oscillation Parameters. Springer, 2020.

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34

Kadir, Mohammed Rafiq Abdul, Ardiyansyah Syahrom, Muhamad Noor Harun, and Amir Putra Bin Saad. Wear Prediction on Total Ankle Replacement: Effect of Design Parameters. Springer International Publishing AG, 2015.

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35

Groom, Leslie. Nondestructive detection of proportional limit and prediction of destructive parameters. 1985.

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36

Kadir, Mohammed Rafiq Abdul, Ardiyansyah Syahrom, Muhamad Noor Harun, and Amir Putra Bin Saad. Wear Prediction on Total Ankle Replacement: Effect of Design Parameters. Springer London, Limited, 2015.

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37

Ito, Yuzuru. Evaluation and application of ice segregation parameters for frost heave prediction. 1993.

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38

Heberle, David D. Performance and parameter prediction of large synchronous machines from physical dimensions. 1994.

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39

Handbook of Parameter Values for the Prediction of Radionuclide Transfer to Wildlife. International Atomic Energy Agency, 2014.

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40

National Aeronautics and Space Administration (NASA) Staff. Comparing Parameter Estimation Techniques for an Electrical Power Transformer Oil Temperature Prediction Model. Independently Published, 2018.

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41

Jansons, Ernests. Influence of Humidity, Air and Ice Temperature on Sliding Ability Characteristics of Friction Pair Stainless Steel-ice. RTU Press, 2022. http://dx.doi.org/10.7250/9789934227240.

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The influence of environmental parameters (air humidity, air and ice temperature) on the friction pair stainless steel-ice sliding ability is studied in the dissertation. Based on empirical measurements, a sliding time prediction model, depending on environmental conditions and measurement and prediction methodology, was developed. The texture and mechanical properties of the ice surface and the surface texture of steel samples were studied. The macrogeometry of the experimental samples was measured, the factors influencing the measurement accuracy in on-field experiments were analysed, and th

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42

Spee, Rene. Prediction of brushless DC drive performance considering non-sinusoidal parameter variations and asymmetrical operating conditions. 1988.

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43

Handbook of Parameter Values for the Prediction of Radionuclide Transfer in Terrestrial and Freshwater Environments. International Atomic Energy Agency, 2010.

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44

Handbook of Parameter Values for the Prediction of Radionuclide Transfer in Temperate Environments (Technical Reports (International Atomic Energy Agency)). International Atomic Energy Agency, 1994.

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45

Vaez-Zadeh, Sadegh. Introduction. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198742968.003.0001.

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An overview of permanent magnet synchronous (PMS) motors and the related control system are presented in this chapter as introductory materials for the rest of the book. The interconnections of the control system to the power electronic inverter and the motor are emphasized. In addition, the major parts of the system are overviewed. Pulse width-modulated voltage source inverter, as the most commonly used power converter in PMS motor drives, is briefly discussed. PMS motors configurations and operating principles are also presented after considering characteristics of permanent magnet materials

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46

Wikle, Christopher K. Spatial Statistics. Oxford University Press, 2018. http://dx.doi.org/10.1093/acrefore/9780190228620.013.710.

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The climate system consists of interactions between physical, biological, chemical, and human processes across a wide range of spatial and temporal scales. Characterizing the behavior of components of this system is crucial for scientists and decision makers. There is substantial uncertainty associated with observations of this system as well as our understanding of various system components and their interaction. Thus, inference and prediction in climate science should accommodate uncertainty in order to facilitate the decision-making process. Statistical science is designed to provide the to

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47

Boddice, Rob. Sympathetic Selection: Eugenics. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252040580.003.0006.

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Chapter 5 returns to the blueprint for the evolution of sympathy in Darwin’s Descent, picking up at the point where Darwin introduces a paradoxical prediction of degeneration, caused by the same force that inspired social cohesion and moral progress. This chapter analyses the birth of the eugenics movement as a department of statistics, arising directly from a concern for the common good of civilised society – the central tenet of highly evolved sympathy. Unlike most studies of eugenics, this chapter focuses largely on the period before 1900, when the parameters of eugenic thought were being h

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48

FitzGerald, Brian. Introduction. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198808244.003.0001.

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The Introduction offers an overview of recent scholarship on medieval prophecy and provides the book’s interpretative framework. The book differs from much previous scholarship by examining how prophecy had a multiplicity of meanings besides prediction in the Middle Ages and by showing the significance of debates over those meanings. The chapter then explains the chronological parameters of the book, beginning in the twelfth century when prophecy became a subject of controversy and ending in the early fourteenth century when humanist intellectuals and poets began challenging the authority of s

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49

Cardot, Hervé, and Pascal Sarda. Functional Linear Regression. Edited by Frédéric Ferraty and Yves Romain. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199568444.013.2.

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This article presents a selected bibliography on functional linear regression (FLR) and highlights the key contributions from both applied and theoretical points of view. It first defines FLR in the case of a scalar response and shows how its modelization can also be extended to the case of a functional response. It then considers two kinds of estimation procedures for this slope parameter: projection-based estimators in which regularization is performed through dimension reduction, such as functional principal component regression, and penalized least squares estimators that take into account

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50

McCleary, Richard, David McDowall, and Bradley J. Bartos. Internal Validity. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780190661557.003.0007.

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Chapter 7 begins with an outline and description of five threats to internal validity common to time series designs: history, maturation, instrumentation, regression, and selection. Given the fundamental role of prediction in the modern scientific method, scientific hypotheses are necessarily causal. After an outline of the evolving definition of “causality” in the social sciences, contemporary Rubin causality or counterfactual causality is introduced. Under the assumption that subjects were randomly assigned to the treatment and control groups, Rubin’s causal model allows one to estimate the

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