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Articles de revues sur le sujet « Mathematical models »

Auteur : Grafiati

Publié le 4 juin 2021

Mis à jour le 25 juillet 2025

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1

Gardiner, Tony, and Gerd Fischer. "Mathematical Models." Mathematical Gazette 71, no. 455 (1987): 94. http://dx.doi.org/10.2307/3616334.

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2

Pavankumari, V. "Mathematical and Stochastic Growth Models." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (2021): 1576–82. http://dx.doi.org/10.22214/ijraset.2021.39055.

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Abstract: Many statistical and mathematical models of growth are developed in the literature and effectively applied to various conditions in the existent world that involve many research problems in the different fields of applied statistics. Nevertheless, still, there is an equally large number of conditions, which have not yet been mathematically or statistically modeled, due to the complex situations or formed models are mathematically or statistically inflexible. The present study is based on mathematical and stochastic growth models. The specification of both the growth models is depicte

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3

Kumari, V. Pavan, Venkataramana Musala, and M. Bhupathi Naidu. "Mathematical and Stochastic Growth Models." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (2022): 987–89. http://dx.doi.org/10.22214/ijraset.2022.42330.

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Abstract: Many statistical and mathematical models of growth are developed in the literature and effectively applied to various conditions in the existent world involves many research problems in the different fields of applied statistics. Nevertheless, still, there are an equally a large number of conditions, which have not yet been mathematically or statistically modeled, due to the complex situations or formed models are mathematically or statistically inflexible. The present study is based on mathematical and stochastic growth models. The specification of both the growth models is depicted

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4

Denton, Brian, Pam Denton, and Peter Lorimer. "Making Mathematical Models." Mathematical Gazette 78, no. 483 (1994): 364. http://dx.doi.org/10.2307/3620232.

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5

Suzuki, Takashi. "Mathematical models of tumor growth systems." Mathematica Bohemica 137, no. 2 (2012): 201–18. http://dx.doi.org/10.21136/mb.2012.142866.

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6

Kogalovsky, M. R. "Digital Libraries of Economic-Mathematical Models: Economic-Mathematical and Information Models." Market Economy Problems, no. 4 (2018): 89–97. http://dx.doi.org/10.33051/2500-2325-2018-4-89-97.

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7

Banasiak, J. "Kinetic models – mathematical models of everything?" Physics of Life Reviews 16 (March 2016): 140–41. http://dx.doi.org/10.1016/j.plrev.2016.01.005.

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Kleiner, Johannes. "Mathematical Models of Consciousness." Entropy 22, no. 6 (2020): 609. http://dx.doi.org/10.3390/e22060609.

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In recent years, promising mathematical models have been proposed that aim to describe conscious experience and its relation to the physical domain. Whereas the axioms and metaphysical ideas of these theories have been carefully motivated, their mathematical formalism has not. In this article, we aim to remedy this situation. We give an account of what warrants mathematical representation of phenomenal experience, derive a general mathematical framework that takes into account consciousness’ epistemic context, and study which mathematical structures some of the key characteristics of conscious

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9

Byrne, Patrick, S. D. Howison, F. P. Kelly, and P. Wilmott. "Mathematical Models in Finance." Statistician 45, no. 3 (1996): 389. http://dx.doi.org/10.2307/2988481.

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10

Kozhanov, V. S., S. O. Ustalkov, and A. O. Khudoshina. "TOW CABLES MATHEMATICAL MODELS." Mathematical Methods in Technologies and Technics, no. 5 (2022): 62–68. http://dx.doi.org/10.52348/2712-8873_mmtt_2022_5_62.

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11

Logan, J. David, Elizabeth S. Allman, and John A. Rhodes. "Mathematical Models in Biology." American Mathematical Monthly 112, no. 9 (2005): 847. http://dx.doi.org/10.2307/30037621.

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12

Zhuk, Tetyana. "Mathematical Models of Reinsurance." Mohyla Mathematical Journal 3 (January 29, 2021): 31–37. http://dx.doi.org/10.18523/2617-70803202031-37.

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Insurance provides financial security and protection of the independence of the insured person. Its principles are quite simple: insurance protects investments, life and property. You regularly pay a certain amount of money in exchange for a guarantee that in case of unforeseen circumstances (accident, illness, death, property damage) the insurance company will protect you in the form of financial compensation.Reinsurance, in turn, has a significant impact on ensuring the financial stability of the insurer. Because for each type of insurance there is a possibility of large and very large risks

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13

Schneider, B., and G. I. Marchuk. "Mathematical Models in Immunology." Biometrics 42, no. 4 (1986): 1003. http://dx.doi.org/10.2307/2530721.

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Knapp, David, and Richard Bellman. "Mathematical Models in Medicine." Mathematical Gazette 70, no. 451 (1986): 79. http://dx.doi.org/10.2307/3615870.

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15

Buikis, A., J. Cepitis, H. Kalis, A. Reinfelds, A. Ancitis, and A. Salminš. "Mathematical Models of Papermaking." Nonlinear Analysis: Modelling and Control 6, no. 1 (2001): 9–19. http://dx.doi.org/10.15388/na.2001.6.1.15221.

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The mathematical model of wood drying based on detailed transport phenomena considering both heat and moisture transfer have been offered in article. The adjustment of this model to the drying process of papermaking is carried out for the range of moisture content corresponding to the period of drying in which vapour movement and bound water diffusion in the web are possible. By averaging as the desired models are obtained sequence of the initial value problems for systems of two nonlinear first order ordinary differential equations.

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16

Soong, S. J. "Mathematical models of prognosis." Melanoma Research 3, no. 1 (1993): 24. http://dx.doi.org/10.1097/00008390-199303000-00081.

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17

Dilão, Rui. "Mathematical models of morphogenesis." ITM Web of Conferences 4 (2015): 01001. http://dx.doi.org/10.1051/itmconf/20150401001.

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18

Mayergoyz, I. "Mathematical models of hysteresis." IEEE Transactions on Magnetics 22, no. 5 (1986): 603–8. http://dx.doi.org/10.1109/tmag.1986.1064347.

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19

Protter, Philip. "Mathematical models of bubbles." Quantitative Finance Letters 4, no. 1 (2016): 10–13. http://dx.doi.org/10.1080/21649502.2015.1165863.

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20

Hamblin, C. L. "Mathematical models of dialogue1." Theoria 37, no. 2 (2008): 130–55. http://dx.doi.org/10.1111/j.1755-2567.1971.tb00065.x.

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21

Jacob, C., F. Charras, X. Trosseille, J. Hamon, M. Pajon, and J. Y. Lecoz. "Mathematical models integral rating." International Journal of Crashworthiness 5, no. 4 (2000): 417–32. http://dx.doi.org/10.1533/cras.2000.0152.

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22

Naydenov, Nikolay Dmitriyevich, Vasily Igorevich Spiryagin, and Elena Nikolayevna Novokshonova. "ECONOMIC-MATHEMATICAL CLUSTER’S MODELS." Sovremennye issledovaniya sotsialnykh problem, no. 9 (November 15, 2015): 415. http://dx.doi.org/10.12731/2218-7405-2015-9-31.

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23

Pollard, John. "Mathematical Models of Population." Population Studies 47, no. 2 (1993): 369. http://dx.doi.org/10.1080/0032472031000147136.

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24

Gavaghan, David, Alan Garny, Philip K. Maini, and Peter Kohl. "Mathematical models in physiology." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 364, no. 1842 (2006): 1099–106. http://dx.doi.org/10.1098/rsta.2006.1757.

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Computational modelling of biological processes and systems has witnessed a remarkable development in recent years. The search-term ( modelling OR modeling ) yields over 58 000 entries in PubMed, with more than 34 000 since the year 2000: thus, almost two-thirds of papers appeared in the last 5–6 years, compared to only about one-third in the preceding 5–6 decades. The development is fuelled both by the continuously improving tools and techniques available for bio-mathematical modelling and by the increasing demand in quantitative assessment of element inter-relations in complex biological sys

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25

Mayergoyz, I. D. "Mathematical Models of Hysteresis." Physical Review Letters 56, no. 15 (1986): 1518–21. http://dx.doi.org/10.1103/physrevlett.56.1518.

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26

Traykov, M., and Iv Trenchev. "Mathematical models in genetics." Russian Journal of Genetics 52, no. 9 (2016): 985–92. http://dx.doi.org/10.1134/s1022795416080135.

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27

Scherer, Almut, and Angela McLean. "Mathematical models of vaccination." British Medical Bulletin 62, no. 1 (2002): 187–99. http://dx.doi.org/10.1093/bmb/62.1.187.

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Huheey, James E. "Mathematical Models of Mimicry." American Naturalist 131 (June 1988): S22—S41. http://dx.doi.org/10.1086/284765.

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29

Raup, David M. "Mathematical models of cladogenesis." Paleobiology 11, no. 1 (1985): 42–52. http://dx.doi.org/10.1017/s0094837300011386.

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The evolutionary pattern of speciation and extinction in any biologic group may be described by a variety of mathematical models. These models provide a framework for describing the history of taxonomic diversity (clade shape) and other aspects of larger evolutionary patterns. The simplest model assumes time homogeneity: that is, speciation and extinction probabilities are constant through time and within taxonomic groups. In some cases the homogeneous model provides a good fit to real world paleontological data, but in other cases the model serves only as a null hypothesis that must be reject

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30

Huggett, R. J. "Mathematical models in agriculture." Applied Geography 5, no. 2 (1985): 172. http://dx.doi.org/10.1016/0143-6228(85)90042-6.

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31

Skogerboe, Gaylord V. "Mathematical models in agriculture." Ecological Modelling 32, no. 4 (1986): 317–19. http://dx.doi.org/10.1016/0304-3800(86)90099-2.

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32

Traykov, M., and Iv Trenchev. "Mathematical Models in Genetics." Генетика 52, no. 9 (2016): 1089–96. http://dx.doi.org/10.7868/s0016675816080130.

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33

Macki, Jack W., Paolo Nistri, and Pietro Zecca. "Mathematical Models for Hysteresis." SIAM Review 35, no. 1 (1993): 94–123. http://dx.doi.org/10.1137/1035005.

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34

Pritchard, W. G. "Mathematical Models of Running." SIAM Review 35, no. 3 (1993): 359–79. http://dx.doi.org/10.1137/1035088.

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35

Rust, Roland T., and Richard Metters. "Mathematical models of service." European Journal of Operational Research 91, no. 3 (1996): 427–39. http://dx.doi.org/10.1016/0377-2217(95)00316-9.

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36

Othmer, Hans G. "Mathematical models in biology." Mathematical Biosciences 96, no. 1 (1989): 131–33. http://dx.doi.org/10.1016/0025-5564(89)90088-6.

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37

Po Wen Hu and Anupkumar M. Deshmukh. "Applications of mathematical models." Computers & Industrial Engineering 15, no. 1-4 (1988): 364–68. http://dx.doi.org/10.1016/0360-8352(88)90113-1.

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38

Liu, Liyuan. "Mathematical models of SARS." Theoretical and Natural Science 14, no. 1 (2023): 154–57. http://dx.doi.org/10.54254/2753-8818/14/20240924.

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The COVID-19 pandemic ignited renewed efforts in quantitative analysis of the impact of pathogens on human health. The mathematical models were critical in understanding the outbreaks for future preventive and reactive approaches to similar outbreaks. This paper intends to explore and provide an understanding of the SARS-CoV-2 infection process, especially its kinetics. Additionally, the paper aims to provide an overview of the immune systems response to infection, especially the immune systems response to infected cells. This paper relates the symptoms of influenza to the observed symptoms of

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39

Nastasi, Giovanni. "Mathematical Models and Simulations." Axioms 13, no. 3 (2024): 149. http://dx.doi.org/10.3390/axioms13030149.

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40

Nishant, Juneja*. "MATHEMATICAL MODELS IN ECOLOGY." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 4, no. 3 (2017): 43–45. https://doi.org/10.5281/zenodo.838569.

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Mathematical modelling is the process of translating the real word problem into the mathematical problem, solving mathematical problem to get some useful results, and then these results are interpreted in the language of real world. Modelling consists of writing in mathematical terms what is first expressed in words, using variables where necessary. Mathematical models are used in the natural sciences , engineering as well as in the social sciences. Statisticians, operations research analysts, and economists use mathematical models hugely. A model may help to explain a system and to study the

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41

Staribratov, Ivaylo, and Nikol Manolova. "Application of Mathematical Models in Graphic Design." Mathematics and Informatics LXV, no. 1 (2022): 72–81. http://dx.doi.org/10.53656/math2022-1-5-app.

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The article shares the practical experience in creating graphic design in the implementation of projects in the field of applied information technology. The creation of digital art is largely based on mathematical models and concepts that give a good perception of graphics, and it is scientifically justified. The STEAM approach is considered with the idea of the transdisciplinary level of integration between mathematics, graphic design and production practice in student education. For the development of projects like logo design, magazine cover and others, we use software specialized in the fi

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42

LEVKIN, Dmytro. "ARCHITECTONICS OF CALCULATED MATHEMATICAL MODELS UNDER UNCERTAINTY." Herald of Khmelnytskyi National University. Technical sciences 309, no. 3 (2022): 135–37. http://dx.doi.org/10.31891/2307-5732-2022-309-3-135-137.

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This article concerns the improvement of calculated mathematical models of technological, biotechnological, and economic systems. It is necessary to increase the number of considered parameters to increase the accuracy of calculating the parameters of complex systems during mathematical modeling. This leads to the need to solve nonlocal boundary value problems with non-stationary differential equations, to prove the correctness of which it is impossible to apply the traditional theory of existence and unity of solution. Note that after the architecture of boundary value problems assumes the ex

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43

Chehlarova, Toni, and Mladen Valkov. "Computer Models of One Mathematical Olympiad Problem." Mathematics and Informatics 67, no. 4 (2024): 433–42. https://doi.org/10.53656/math2024-4-6-com.

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Dynamic computer models of a geometry problem from the 23rd Balkan Mathematical Olympiad in 2006 are presented. Ideas for their use are described: for providing conditions for research work and formulating hypotheses, for discovering an idea for solving, for presenting a solution, for learning the software through tasks. A reference is made to dynamic computer models of other Olympiad tasks provided in the Virtual Mathematics Laboratory developed in the Institute of Mathematics and Informatics at the Bulgarian Academy of Sciences. The possibility of their usage in both informal and in formal e

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44

Iryono, Mustofa Baydillah, Indy Qonita, and Syifa Ratna Elya M. "Analysis of Students Mathematical Communication Ability Models on Set Materials." International Journal of Technology and Modeling 1, no. 1 (2022): 15–20. https://doi.org/10.63876/ijtm.v1i1.4.

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This study aims to see and analysis: The ability of mathematical communication to connect actual items, photos and diagrams into mathematical thinking. The ability of mathematical communication to provide explanations for thoughts, conditions, writing with gadgets, pictures, graphs, and actual algebra. The ability to speak mathematically expresses ordinary events in language or mathematical symbols. The ability of mathematical conversation to create state versions through writing, concrete gadgets, pictures, graphs, and algebraic methods. Mathematical verbal exchange ability to provide explana

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45

Vinayak Kishan Nirmale. "Mathematical Models for Infectious Disease Dynamics and Control Strategies." Communications on Applied Nonlinear Analysis 32, no. 1s (2024): 54–62. http://dx.doi.org/10.52783/cana.v32.2101.

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The study explores mathematical models related to the dynamics of infectious diseases and approaches to manage them. These models are essential resources for comprehending how illnesses spread throughout people and assessing how well control strategies work. The study of infectious disease epidemiology heavily relies on mathematical modeling and analysis. Here, we give a clear overview of the spread of disease, explain how to mathematically model this stochastic process, and show how to utilize this mathematical representation to analyze the emergent dynamics of real-world epidemics. The advan

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46

Purwanto, Burhan Eko, Icha Jusmalisa, Indah Permata Sari, Agus Jatmiko, and Andika Eko Pasetiyo. "Learning Models to Improved Mathematical Communication Skills." Desimal: Jurnal Matematika 3, no. 1 (2020): 7–16. http://dx.doi.org/10.24042/djm.v3i1.5650.

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The problem faced by students in slow learning is in terms of communication. The use of Auditory, Intellectually, Repetition (AIR) and Cooperative Think Pair Share (TPS) types is needed to help students communicate mathematically in expressing mathematical ideas. This study aims to determine whether or not there are differences in mathematical communication skills of students using the Auditory, Intellectually, Repetition (AIR) learning model with students who use Think Pair Share (TPS) Cooperative learning models. This research uses a quantitative approach using the Quasi Experiment method. T

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47

Leangarun, Teema, Poj Tangamchit, and Suttipong Thajchayapong. "Stock Price Manipulation Detection Based on Mathematical Models." International Journal of Trade, Economics and Finance 7, no. 3 (2016): 81–88. http://dx.doi.org/10.18178/ijtef.2016.7.3.503.

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48

Ojha, Pratima, and R. K. Dubey R.K.Dubey. "Mathematical Properties of Homogeneous and Isotropic Cosmological Models." International Journal of Scientific Research 2, no. 2 (2012): 83–84. http://dx.doi.org/10.15373/22778179/feb2013/30.

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49

ZAVGORODNIY, OLEXIY, DMYTRO LEVKIN, YANA KOTKO, and OLEXANDER MAKAROV. "RESEARCH OF COMPUTATIONAL MATHEMATICAL MODELS FOR TECHNICAL SYSTEMS." Herald of Khmelnytskyi National University. Technical sciences 319, no. 2 (2023): 108–12. http://dx.doi.org/10.31891/2307-5732-2023-319-1-108-112.

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In the theory of analysis and synthesis of technical systems, mathematical modelling and optimization of multilayer systems containing sources of physical fields occupy an important place. This is due to the fact that their state is described by means of boundary value problems with multidimensional differential equations. To solve the boundary value problems and implement the process of optimizing the technical parameters of the modelled systems, it is necessary to conduct interdisciplinary studies of computational and applied optimization mathematical models. Fulfilment of the conditions for

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50

Toxirjonovich, Orinov Nodirbek, and Mirzaaxmedov Muhammadbobur Karimberdiyevich. "Mathematical models of technical systems." ACADEMICIA: An International Multidisciplinary Research Journal 10, no. 11 (2020): 221–25. http://dx.doi.org/10.5958/2249-7137.2020.01343.9.

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