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Books on the topic 'Mathematical modeols'

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Author: Grafiati

Published: 27 July 2024

Last updated: 28 July 2024

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1

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

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2

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

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3

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

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4

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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5

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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6

Williams, H. P. Model building in mathematical programming. 3rd ed. Chichester [England]: Wiley, 1990.

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7

A, Levin Simon, Hallam T. G, Gross Louis J, and Autumn Course on Mathematical Ecology (2nd : 1986 : International Centre for Theoretical Physics), eds. Applied mathematical ecology. Berlin: Springer-Verlag, 1989.

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8

T, Shaw William. Modelling financial derivatives with Mathematica: Mathematical models and benchmark algorithms. Cambridge: Cambridge University Press, 1998.

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9

Clark, Colin Whitcomb. Mathematical bioeconomics: The mathematics of conservation. 3rd ed. Hoboken, N.J: Wiley, 2010.

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10

Ian, Huntley, and James D. J. G, eds. Mathematical modelling: A source book of case studies. Oxford [England]: Oxford University Press, 1990.

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11

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

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12

1957-, Willmot G. E., ed. Insurance risk models. Schaumburg, Ill: Society of Acturaries, 1992.

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13

K, Maini Philip, and Othmer H. G. 1943-, eds. Mathematical models for biological pattern formulation: Frontiers in biological mathematics. New York: Springer, 2001.

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14

Mathematical biology. 2nd ed. Berlin: Springer-Verlag, 1993.

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15

Hrsg, Crampin Mike, ed. Mathematical models and methods: Mathematical modelling. Milton Keynes: Open University, 1993.

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16

Fred, Brauer, Van den Driessche, Pauline, 1941-, Wu Jianhong 1964-, and Allen Linda J. S, eds. Mathematical epidemiology. Berlin: Springer, 2008.

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17

Keyfitz, Nathan, and David P. Smith. Mathematical demography: Selected papers. Edited by Wachter Kenneth W. editor and Le Bras, Hervé, 1943- editor. Berlin: Springer, 2013.

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18

Hilton, Peter John. A Mathematical Tapestry: Demonstrating the Beautiful Unity of Mathematics. New York: Cambridge University Press, 2010.

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19

Jean, Pedersen, ed. A Mathematical Tapestry: Demonstrating the Beautiful Unity of Mathematics. New York: Cambridge University Press, 2010.

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20

IMACS International Conference on Mathematical Modelling and Applied Mathematics (1990 Moscow, R.S.F.S.R.). Mathematical modelling and applied mathematics: Proceedings of the IMACS International Conference on Mathematical Modelling and Applied Mathematics, Moscow, USSR, 18-23 June 1990. Amsterdam: North-Holland, 1992.

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21

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

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22

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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23

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

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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.

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24

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

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25

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

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26

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

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27

Thinking With Mathematical Models (Prentice Hall Connected Mathematics). Pearson Prentice Hall, 2000.

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28

Guarracino, Mario R., Valeria Zazzu, and Maria Brigida Ferraro. Mathematical Models in Biology: Bringing Mathematics to Life. Springer London, Limited, 2015.

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29

Ross, David, and Avner Friedman. Mathematical Models in Photographic Sciences (Mathematics in Industry). Springer, 2003.

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30

Guarracino, Mario R., Valeria Zazzu, and Maria Brigida Ferraro. Mathematical Models in Biology: Bringing Mathematics to Life. Springer, 2015.

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31

Guarracino, Mario R., Valeria Zazzu, and Maria Brigida Ferraro. Mathematical Models in Biology: Bringing Mathematics to Life. Springer, 2019.

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32

Mathematical Models in Biology (Classics in Applied Mathematics). SIAM: Society for Industrial and Applied Mathematics, 2005.

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33

Mathematical bioeconomics: The mathematics of conservation. 3rd ed. Hoboken, N.J: Wiley, 2010.

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34

Fischer, G. Mathematical models. Vieweg, 1986.

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35

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

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36

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

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37

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

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38

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

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39

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

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40

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

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41

Mathematical models. Pearson Custom Pub, 2000.

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42

Problems of computational mathematics and mathematical modelling. Moscow: Mir Publishers, 1985.

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43

Ye, Qi-Xiao. Mathematical Modelling in Educations and Culture (Mathematics & Applications). Albion/Horwood Pub, 2003.

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44

Besseling, J. F., and E. Van Der Giessen. Mathematical Modeling of Inelastic Deformation (Applied Mathematics and Mathematical Computation Series). Chapman & Hall/CRC, 1994.

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45

Boland, Lawrence A. Equilibrium concepts and critiques. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190274320.003.0006.

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This chapter explores the equilibrium concept by examining the views of two cultures: those who began talking about equilibrium models in the decades before World War II and those formal model builders promoting mathematics after that war. For the older culture, the concept of an equilibrium refers to the real properties of an actual economy in a state of equilibrium. For the newer culture, an equilibrium refers only to a property of a formal mathematical model. The main discussion of the chapter is about the various critiques provided by both sides of the cultural divide. The chapter also discusses the extent to which the distinction between a model’s exogenous vs. endogenous variables involves causality. The older culture would view causality as a necessary part of understanding an equilibrium but the newer culture would view it only as an interpretation of the mathematics of the model.

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46

Yudin, Sergey. Mathematics and economic-mathematical models: calculations on the computer. Infra-M Academic Publishing House, 2016. http://dx.doi.org/10.12737/5564.

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47

Applied Mathematical Models and Problem-Solving for College Mathematics. Pearson Education, 2016.

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48

Applied Mathematical Ecology. Springer, 2012.

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49

Hallam, Thomas G., Louis J. Gross, and Simon A. Levin. Applied Mathematical Ecology. Springer London, Limited, 2012.

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50

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

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