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Libros sobre el tema "Mathematical models"

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Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 8 de junio de 2024

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1

Fischer, Gerd, ed. Mathematical Models. Wiesbaden: Springer Fachmedien Wiesbaden, 2017. http://dx.doi.org/10.1007/978-3-658-18865-8.

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2

Tanguy, Jean-Michel, ed. Mathematical Models. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9781118557853.

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3

Ershov, I͡Uriĭ Leonidovich. Constructive models. New York: Consultants Bureau, 2000.

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4

R, Thompson James. Empirical model building: Data, models, and reality. 2a ed. Hoboken, N.J: John Wiley & Sons, 2011.

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5

Mayergoyz, I. D. Mathematical models of hysteresis. New York: Springer-Verlag, 1991.

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6

Keynes), Open University (Milton. Mathematical models and methods: Mathematical modelling. Milton Keynes: Open University, 1993.

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7

Torres, Pedro J. Mathematical Models with Singularities. Paris: Atlantis Press, 2015. http://dx.doi.org/10.2991/978-94-6239-106-2.

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8

Borisov, Andrey Valerievich y Anatoly Vlasovich Chigarev. Mathematical Models of Exoskeleton. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97733-7.

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9

Stamova, Ivanka y Gani Stamov. Applied Impulsive Mathematical Models. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28061-5.

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10

Mayergoyz, I. D. Mathematical Models of Hysteresis. New York, NY: Springer New York, 1991. http://dx.doi.org/10.1007/978-1-4612-3028-1.

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11

Ansorge, Rainer. Mathematical Models of Fluiddynamics. Weinheim, FRG: Wiley-VCH Verlag GmbH & Co. KGaA, 2002. http://dx.doi.org/10.1002/3527602771.

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12

Zazzu, Valeria, Maria Brigida Ferraro y Mario R. Guarracino, eds. Mathematical Models in Biology. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23497-7.

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13

Brauer, Fred, Carlos Castillo-Chavez y Zhilan Feng. Mathematical Models in Epidemiology. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9828-9.

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14

Andreev, V. K. Mathematical models of convection. Berlin: De Gruyter, 2012.

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15

Edelstein-Keshet, Leah. Mathematical models in biology. New York: Random House, 1988.

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16

Jóźwiak, Janina. Mathematical models of population. Netherlands: the Hague, 1992.

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17

Edelstein-Keshet, Leah. Mathematical models in biology. New York: McGraw-Hill, 1988.

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18

1943-, Garfunkel Solomon A., Cheyney Roland, Lege Jerry y Consortium for Mathematics and Its Applications (U.S.), eds. Mathematical models with applications. New York: W.H. Freeman, 2002.

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19

Nightingale, Peter Graham. Mathematical models for epidemics. Birmingham: University of Birmingham, 1988.

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20

Open University. Mathematical Models and Methods Course Team., ed. Mathematical models and methods. Milton Keynes: Open University, 1993.

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21

Bertelle, Ralph. Mathematical models with applications. Boston, MA: Pearson, 2016.

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22

Mayergoyz, I. D. Mathematical Models of Hysteresis. New York, NY: Springer New York, 1991.

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23

Sam, Howison, Kelly F. P y Wilmott Paul, eds. Mathematical models in finance. New York, NY: Published by Chapman & Hall for the Royal Society, 1995.

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24

Fowler, A. C. Mathematical models in the applied sciences. Cambridge: Cambridge University Press, 1997.

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25

Dym, Clive L. Principles of mathematical modeling. 2a ed. Amsterdam: Elsevier Academic Press, 2004.

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26

Murray, J. D. Mathematical biology. 2a ed. Berlin: Springer-Verlag, 1993.

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27

Murray, J. D. Mathematical biology. Berlin: Springer-Verlag, 1989.

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28

Murray, J. D. Mathematical biology. 3a ed. New York: Springer, 2002.

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29

Adams, William J. Mathematics applied: An introduction to mathematical modeling. New York, N.Y: Pace and Pace, 1990.

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30

Kimball, Robert Lee. Mathematical models. Pearson Custom Pub, 2000.

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31

Fischer, G. Mathematical models. Vieweg, 1986.

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32

Rollett, A. P. y H. M. Cundy. Mathematical Models. Tarquin, 1997.

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33

Tanguy, Jean-Michel y Jean-Michel Tanguy. Mathematical Models. Wiley & Sons, Incorporated, John, 2012.

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34

Tanguy, Jean-Michel. Mathematical Models. Wiley & Sons, Incorporated, John, 2012.

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35

Mathematical Models. 4a ed. Pearson Custom Publishing, 2005.

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36

Tanguy, Jean-Michel. Mathematical Models. Wiley & Sons, Incorporated, John, 2013.

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37

Tanguy, Jean-Michel. Mathematical Models. Wiley & Sons, Incorporated, John, 2010.

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38

Cruickshank, Steven. Mathematical models and anaesthesia. Editado por Jonathan G. Hardman. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780199642045.003.0027.

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Resumen
The use of mathematics in medicine is not as widespread as it might be. While professional engineers are instructed in a wide variety of mathematical techniques during their training in preparation for their daily practice, tradition and the demands of other subjects mean that doctors give little attention to numerical matters in their education. A smattering of statistical concepts is typically the main mathematical field that we apply to medicine. The concept of the mathematical model is important and indeed familiar; personal finance, route planning, home decorating, and domestic projects all require the application of the basic mathematical tools we acquire at school. This utility is why we learn them. The insight that can be gained by applying mathematics to physiological and other problems within medical practice is, however, underexploited. The undoubted complexity of human biology and pathology perhaps leads us to give up too soon. There are useful and practical lessons that can be learned from the use of elementary mathematics in medicine. Anaesthetic training in particular lends itself to such learning with its emphasis on physics and clinical measurement. Much can be achieved with simple linear functions and hyperbolas. Further exploration into exponential and sinusoidal functions, although a little more challenging, is well within our scope and enables us to cope with many time-dependent and oscillatory phenomena that are important in clinical anaesthetic practice. Some fundamental physiological relationships are explained in this chapter using elementary mathematical functions. Building further on the foundation of simple models to cope with more complexity enables us to see the process, examine the predictions, and, most importantly, assess the plausibility of these models in practice. Understanding the structure of the model enables intelligent interpretation of its output. Some may be inspired to investigate some of the mathematical concepts and their applications further. The rewards can be intellectually, aesthetically, and practically fruitful. The subtle, revelatory, and quite beautiful connection between exponential and trigonometric functions through the concept of complex numbers is one example. That this connection has widespread practical importance too is most pleasing.
39

Yudin, Sergey. Mathematics and economic-mathematical models: textbook. Infra-M Academic Publishing House, 2016. http://dx.doi.org/10.12737/5676.

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40

Ershov, Yuri L. Constructive Models. Springer, 2012.

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41

Horsmon, Christine. Elementary Mathematical Models. Kendall Hunt Publishing Company, 2009.

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42

Horsmon, Christine. Elementary Mathematical Models. Kendall Hunt Publishing Company, 2010.

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43

Croon. Viability Mathematical Models. Taylor & Francis, 1994.

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44

Edwards, Dilwyn y Mike Hamson. Guide to Mathematical Modelling (Mathematical Guides). 2a ed. Palgrave Macmillan, 2001.

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45

Gatto, Riccardo. Insurance Mathematics: Stochastic Models and Mathematical Methods. Elsevier, 2019.

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46

Gatto, Riccardo. Insurance Mathematics: Stochastic Models and Mathematical Methods. Elsevier, 2019.

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47

Hassani, Sadri. Mathematical Methods using Mathematica. Springer, 2003.

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48

Serovajsky, Simon. Sequential Models of Mathematical Physics. Taylor & Francis Group, 2019.

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49

Mathematical methods and models. Milton Keynes: Open University, 2005.

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50

Tanguy, Jean-Michel. Environmental Hydraulics: Mathematical Models. Wiley & Sons, Incorporated, John, 2013.

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