Thematische Bibliographien / Mathematical model

Inhaltsverzeichnis

  1. Zeitschriftenartikel
  2. Dissertationen
  3. Bücher
  4. Buchteile
  5. Konferenzberichte
  6. Berichte der Organisationen

Auswahl der wissenschaftlichen Literatur zum Thema „Mathematical model“

Autor: Grafiati
Veröffentlicht am 4. Juni 2021
Zuletzt aktualisiert am 8. November 2024

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Zeitschriftenartikel zum Thema "Mathematical model"

1

Kumar, Jitender, und V. K. Kukreja. „Mathematical Model of Pulp Washing Using Mathematica“. MATEC Web of Conferences 57 (2016): 05008. http://dx.doi.org/10.1051/matecconf/20165705008.

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Rifki Taufik, Muhammad, Dwi Lestari und Tri Wijayanti Septiarini. „Mathematical Model for Vaccinated Tuberculosis Disease with VEIT Model“. International Journal of Modeling and Optimization 5, Nr. 3 (Juni 2015): 192–97. http://dx.doi.org/10.7763/ijmo.2015.v5.460.

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Połowniak, Piotr, und Mariusz Sobolak. „Mathematical model of globoid worm for use of generating CAD model“. Mechanik, Nr. 2 (Februar 2015): 145/31. http://dx.doi.org/10.17814/mechanik.2015.2.53.

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ROTARU, Constantin, Oliver CIUICĂ, Eduard MIHAI, Ionică CÎRCIU und Radu DINCĂ. „SIMPLIFIED MATHEMATICAL MODEL FOR AIRCRAFTSRESPONSE CHARACTERISTICS“. SCIENTIFIC RESEARCH AND EDUCATION IN THE AIR FORCE 18, Nr. 1 (24.06.2016): 55–60. http://dx.doi.org/10.19062/2247-3173.2016.18.1.7.

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Stehney, Ann K., Sarah Flannery und David Flannery. „Mathematical Model“. Women's Review of Books 19, Nr. 1 (Oktober 2001): 7. http://dx.doi.org/10.2307/4023851.

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Wan, Delong, und Huiping Zeng. „Water environment mathematical model mathematical algorithm“. IOP Conference Series: Earth and Environmental Science 170 (Juli 2018): 032133. http://dx.doi.org/10.1088/1755-1315/170/3/032133.

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Bаzhanova, А. Yu, M. G. Suryaninov und G. B. Shotadze. „Finite elements mathematical model of geometric nonlinearity“. Odes’kyi Politechnichnyi Universytet. Pratsi, Nr. 2 (15.06.2015): 138–44. http://dx.doi.org/10.15276/opu.2.46.2015.25.

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TRIVEDI, PRATIK H. „An Appropriate Mathematical Model for A Product“. Global Journal For Research Analysis 3, Nr. 5 (15.06.2012): 11–12. http://dx.doi.org/10.15373/22778160/may2014/5.

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Bouizem, Nacera, Mohamed Helal, Bedr'Eddine Ainseba und Abdelkader Lakmeche. „Leukemia mathematical model“. ITM Web of Conferences 4 (2015): 01006. http://dx.doi.org/10.1051/itmconf/20150401006.

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Shrivastava, Rajesh, Deepika Basedia und Keerty Shrivastava. „Predictive Mathematical Model on Breast Cancer: A Study“. international journal of mathematics and computer research 12, Nr. 03 (31.03.2024): 4107–13. http://dx.doi.org/10.47191/ijmcr/v12i3.05.

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In the present study, we have designed a mathematical model to analyze whether the cases of breast cancer are maximized or minimized in Madhya Pradesh. Especially to check the age range in which it’s more susceptible to the disease and its means of therapy. The important data collected from Jawaharlal Nehru Cancer Hospital, Bhopal (JLNCH) and Gandhi Medical College, Bhopal (GMC) is from over ten years of reviews of the cases. Actual documentary and analytical methods were used to collect and analyze the data. It is concluded from the results that the number of cancer cases is increasing in both hospitals; its projection may reach up to 97.8% by the year 2023; the age range of 40–50 is more vulnerable to the disease. The line of treatment for breast cancer patients is surgery, chemotherapy, and radiotherapy in both hospitals.
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Dissertationen zum Thema "Mathematical model"

1

Tonner, Jaromír. „Overcomplete Mathematical Models with Applications“. Doctoral thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2010. http://www.nusl.cz/ntk/nusl-233893.

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Chen, Donoho a Saunders (1998) studují problematiku hledání řídké reprezentace vektorů (signálů) s použitím speciálních přeurčených systémů vektorů vyplňujících prostor signálu. Takovéto systémy (někdy jsou také nazývány frejmy) jsou typicky vytvořeny buď rozšířením existující báze, nebo sloučením různých bazí. Narozdíl od vektorů, které tvoří konečně rozměrné prostory, může být problém formulován i obecněji v rámci nekonečně rozměrných separabilních Hilbertových prostorů (Veselý, 2002b; Christensen, 2003). Tento funkcionální přístup nám umožňuje nacházet v těchto prostorech přesnější reprezentace objektů, které, na rozdíl od vektorů, nejsou diskrétní. V této disertační práci se zabývám hledáním řídkých representací v přeurčených modelech časových řad náhodných veličin s konečnými druhými momenty. Numerická studie zachycuje výhody a omezení tohoto přístupu aplikovaného na zobecněné lineární modely a na vícerozměrné ARMA modely. Analýzou mnoha numerických simulací i modelů reálných procesů můžeme říci, že tyto metody spolehlivě identifikují parametry blízké nule, a tak nám umožňují redukovat původně špatně podmíněný přeparametrizovaný model. Tímto významně redukují počet odhadovaných parametrů. V konečném důsledku se tak nemusíme starat o řády modelů, jejichž zjišťování je většinou předběžným krokem standardních technik. Pro kratší časové řady (100 a méně vzorků) řídké odhady dávají lepší predikce v porovnání s těmi, které jsou založené na standardních metodách (např. maximální věrohodnosti v MATLABu - MATLAB System Identification Toolbox (IDENT)). Pro delší časové řady (500 a více) obě techniky dávají v podstatě stejně přesné predikce. Na druhou stranu řešení těchto problémů je náročnější, a to i časově, nicméně výpočetní doba je stále přijatelná.
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Jones, Jennifer Grace. „A mathematical model of emphysema“. Thesis, University of Bristol, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269229.

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Durfee, Lucille J. „BIO-MATHEMATICS: INTRODUCTION TO THE MATHEMATICAL MODEL OF THE HEPATITIS C VIRUS“. CSUSB ScholarWorks, 2016. https://scholarworks.lib.csusb.edu/etd/428.

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In this thesis, we will study bio-mathematics. We will introduce differential equations, biological applications, and simulations with emphasis in molecular events. One of the first courses of action is to introduce and construct a mathematical model of our biological element. The biological element of study is the Hepatitis C virus. The idea in creating a mathematical model is to approach the biological element in small steps. We will first introduce a block (schematic) diagram of the element, create differential equations that define the diagram, convert the dimensional equations to non-dimensional equations, reduce the number of parameters, identify the important parameters, and analyze the results. These results will tell us which variables must be adjusted to prevent the Hepatitis C virus from becoming chronic.
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Di, Domenico Chiara. „A mathematical model for migraine aura“. Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016. http://amslaurea.unibo.it/12350/.

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Nella tesi è descritto un modello matematico per l'aura emicranica e, più precisamente, per lo scotoma scintillante (schema di fortificazione) e per la Cortical Spreading Depression, il fenomeno neuropatofisiologico alla base dell'aura. In particolare è spiegato un modello cinematico per l'evoluzione della CSD nella corteccia visiva primaria, considerata un mezzo debolmente eccitabile, la mappa retino-corticale e il modello, tramite fibrato, dei Pinwheels di V1.
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Thorsen, Kjetil. „Mathematical Model of the Geomagnetic Field“. Thesis, Norwegian University of Science and Technology, Department of Mathematical Sciences, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9329.

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First comes a description of a mathematical model of the geomagnetic field. Then some discussion of the classical non-uniqueness results of Backus. Further we look at more recent results concerning reconstruction of the geomagnetic field from intensity and the normal component of the field. New stability estimate for this reconstruction is obtained.

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Cho, Jae Hyun. „Computer aids for mathematical model-building“. Thesis, Imperial College London, 1997. http://hdl.handle.net/10044/1/8256.

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Darabi, Pirooz. „A mathematical model for cement kilns“. Thesis, University of British Columbia, 2007. http://hdl.handle.net/2429/32346.

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Rotary kilns have numerous industrial applications including cement production. Frequent operational problems such as low thermal efficiency, refractory failure, and poor product quality have prompted extensive efforts to improve and optimize their design. Mathematical modeling and Computational Fluid Dynamics constitute effective tools recently used for these purposes. A cement kiln consists of three major parts: the hot flow, the bed, and the wall. A CFD code which had the capability of simulating the hot gas was developed further to simulate the kiln. In the present work, two 1-D mathematical models are proposed and implemented in the existing CFD code. The first model consists of the steady-state solution for the material and temperature evolution within the bed. The second one simulates tire combustion in the kiln. The tire burning model assumes that tire combustion occurs in two major successive steps, devolatization and char combustion. For the devolatization model, external heat and mass transfer, three parallel reactions, and enthalpy effects are considered the dominant phenomena. The char combustion model considers the enthalpy effect and the external mass transfer. With the aid of the developed model, full-scale industrial cement kilns under steady-state and realistic operational conditions are simulated. In addition, cement kilns with combustion of full scrap tires in the middle of them are mathematically modeled. The limits and feasibility of tire combustion are further explored by running numerical simulations with different tire flow rates and different injector locations. The flow field, temperature distribution and species distribution are presented. Analysis of the results indicates that, with the help of the proposed model, a better understanding of the important processes within cement kilns can be obtained. The model can be used for addressing operational problems and optimizing designs. It is also concluded that successful firing of tires can lead to a cheaper, longer lasting, and less polluting kiln.
Applied Science, Faculty of
Mechanical Engineering, Department of
Graduate
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She, Chunfeng. „A mathematical model for power derivatives“. [Bloomington, Ind.] : Indiana University, 2007. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3297110.

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Thesis (Ph.D.)--Indiana University, Dept. of Mathematics, 2007.
Title from dissertation home page (viewed Sept. 29, 2008). Source: Dissertation Abstracts International, Volume: 69-02, Section: B, page: 1045. Adviser: Victor W. Goodman.
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Roose, T. „Mathematical model of plant nutrient uptake“. Thesis, University of Oxford, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.365790.

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This thesis deals with the mathematical modelling of nutrient uptake by plant roots. It starts with the Nye-Tinker-Barber model for nutrient uptake by a single bare cylindrical root. The model is treated using matched asymptotic expansion and an analytic formula for the rate of nutrient uptake is derived for the first time. The basic model is then extended to include root hairs and mycorrhizae, which have been found experimentally to be very important for the uptake of immobile nutrients. Again, analytic expressions for nutrient uptake are derived. The simplicity and clarity of the analytical formulae for the solution of the single root models allows the extension of these models to more realistic branched roots. These models clearly show that the `volume averaging of branching structure' technique commonly used to extend the Nye-Tinker-Barber with experiments can lead to large errors. The same models also indicate that in the absence of large-scale water movement, due to rainfall, fertiliser fails to penetrate into the soil. This motivates us to build a model for water movement and uptake by branched root structures. This model considers the simultaneous flow of water in the soil, uptake by the roots, and flow within the root branching network to the stems of the plant. The water uptake model shows that the water saturation can develop pseudo-steady-state wet and dry zones in the rooting region of the soil. The dry zone is shown to stop the movement of nutrient from the top of the soil to the groundwater. Finally we present a model for the simultaneous movement and uptake of both nutrients and water. This is discussed as a new tool for interpreting available experimental results and designing future experiments. The parallels between evolution and mathematical optimisation are also discussed.
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Kelly, R. J. „Mathematical model of multi-phase snowmelt“. Thesis, University of East Anglia, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.377740.

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Bücher zum Thema "Mathematical model"

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Williams, H. P. Model building in mathematical programming. 5. Aufl. Chichester, West Sussex: Wiley, 2013.

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W, Zucchini, Hrsg. Model selection. New York: Wiley, 1986.

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Prestel, Alexander, und Charles N. Delzell. Mathematical Logic and Model Theory. London: Springer London, 2011. http://dx.doi.org/10.1007/978-1-4471-2176-3.

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Bateman, J. E. Surface exafs: A mathematical model. Chilton: Rutherford Appleton Laboratory, 2000.

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

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Williams, H. P. Model solving in mathematical programming. Chichester: J. Wiley, 1993.

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Ivanov, Viktor Vladimirovich. Model development and optimization. Dordrecht: Kluwer Academic Publishers, 1999.

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service), SpringerLink (Online, Hrsg. Model Theory and Applications. Berlin, Heidelberg: Springer-Verlag Berlin Heidelberg, 2011.

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Cheung, Yun-Hsing. A simple mathematical model of lottery play. Perth, W.A: Edith Cowan University, Faculty of Business, School of Finance and Business Economics, 1996.

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Hart, Bradd T. Algebraic Model Theory. Dordrecht: Springer Netherlands, 1997.

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Buchteile zum Thema "Mathematical model"

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Danilov, Vladimir, Roman Gaydukov und Vadim Kretov. „Mathematical Model“. In Heat and Mass Transfer, 59–130. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0195-1_3.

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Qin, Tongran. „Mathematical Model“. In Springer Theses, 19–35. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61331-4_2.

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Gross, Sven, und Arnold Reusken. „Mathematical model“. In Springer Series in Computational Mathematics, 327–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19686-7_10.

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Gross, Sven, und Arnold Reusken. „Mathematical model“. In Springer Series in Computational Mathematics, 385–90. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19686-7_12.

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Gross, Sven, und Arnold Reusken. „Mathematical model“. In Springer Series in Computational Mathematics, 161–95. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-19686-7_6.

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Feireisl, Eduard, Trygve G. Karper und Milan Pokorný. „Mathematical Model“. In Mathematical Theory of Compressible Viscous Fluids, 25–30. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-44835-0_2.

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Mbiock, Aristide, und Roman Weber. „Mathematical Model“. In Radiation in Enclosures, 53–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57094-0_4.

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Gass, Saul I., und Carl M. Harris. „Mathematical model“. In Encyclopedia of Operations Research and Management Science, 495. New York, NY: Springer US, 2001. http://dx.doi.org/10.1007/1-4020-0611-x_592.

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Weik, Martin H. „mathematical model“. In Computer Science and Communications Dictionary, 985. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_11176.

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Vulfson, Iosif. „Mathematical Model“. In Foundations of Engineering Mechanics, 41–62. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-12634-0_3.

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Konferenzberichte zum Thema "Mathematical model"

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Weckesser, Markus, Malte Lochau, Michael Ries und Andy Schürr. „Mathematical Programming for Anomaly Analysis of Clafer Models“. In MODELS '18: ACM/IEEE 21th International Conference on Model Driven Engineering Languages and Systems. New York, NY, USA: ACM, 2018. http://dx.doi.org/10.1145/3239372.3239398.

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„Model Composition for Biological Mathematical Systems“. In International Conference on Model-Driven Engineering and Software Development. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004699202170224.

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Petruk, Sergii, Ruslan Zhyvotovskyi und Andrii Shyshatskyi. „Mathematical Model of MIMO“. In 2018 International Scientific-Practical Conference Problems of Infocommunications. Science and Technology (PIC S&T). IEEE, 2018. http://dx.doi.org/10.1109/infocommst.2018.8632163.

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Cendrowski, S. K. „Mathematical model of retina“. In Second International Conference on Optical Information Processing, herausgegeben von Zhores I. Alferov, Yuri V. Gulyaev und Dennis R. Pape. SPIE, 1996. http://dx.doi.org/10.1117/12.262578.

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Mcheick, Hamid, Ahmad Karawash und Taha Baba. „Load Balancing Mathematical Model“. In 2011 Developments in E-systems Engineering (DeSE). IEEE, 2011. http://dx.doi.org/10.1109/dese.2011.63.

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Shempelev, A., P. Iglin und N. Tatarinova. „On condenser mathematical model method introduction into steam turbine unit mathematical model“. In 2017 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM). IEEE, 2017. http://dx.doi.org/10.1109/icieam.2017.8076455.

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Chrobak, Joanna M., Henar Herrero, Alberto Cabada, Eduardo Liz und Juan J. Nieto. „Mathematical model of cancer with competition“. In MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142956.

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Nakamura, Masaki, und Kazutoshi Sakakibara. „Formal Verification and Mathematical Optimization for Autonomous Vehicle Group Controllers“. In 2019 ACM/IEEE 22nd International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C). IEEE, 2019. http://dx.doi.org/10.1109/models-c.2019.00111.

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Itami, Teturo. „Mathematical model of group robots“. In 2013 9th Asian Control Conference (ASCC). IEEE, 2013. http://dx.doi.org/10.1109/ascc.2013.6606369.

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Henno, Jaak. „Mathematical Model of Natural Languages“. In 2006 IEEE International Conference on Computational Cybernetics. IEEE, 2006. http://dx.doi.org/10.1109/icccyb.2006.305733.

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Berichte der Organisationen zum Thema "Mathematical model"

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Pokorny, Richard, und Pavel R. Hrma. Mathematical Model of Cold Cap?Preliminary One-Dimensional Model Development. Office of Scientific and Technical Information (OSTI), März 2011. http://dx.doi.org/10.2172/1012879.

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Buchanan, C. R., und M. H. Sherman. A mathematical model for infiltration heat recovery. Office of Scientific and Technical Information (OSTI), Mai 2000. http://dx.doi.org/10.2172/767547.

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Preto, F. A mathematical model for fluidized bed coal combustion. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1985. http://dx.doi.org/10.4095/302616.

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Lovianova, Iryna V., Dmytro Ye Bobyliev und Aleksandr D. Uchitel. Cloud calculations within the optional course Optimization Problems for 10th-11th graders. [б. в.], September 2019. http://dx.doi.org/10.31812/123456789/3267.

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The article deals with the problem of introducing cloud calculations into 10th-11th graders’ training to solve optimization problems in the context of the STEM-education concept. After analyzing existing programmes of optional courses on optimization problems, the programme of the optional course Optimization Problems has been developed and substantiated implying solution of problems by the cloud environment CoCalc. It is a routine calculating operation and not a mathematical model that is accentuated in the programme. It allows considering more problems which are close to reality without adapting the material while training 10th-11th graders. Besides, the mathematical apparatus of the course which is partially known to students as the knowledge acquired from such mathematics sections as the theory of probability, mathematical statistics, mathematical analysis and linear algebra is enough to master the suggested course. The developed course deals with a whole class of problems of conventional optimization which vary greatly. They can be associated with designing devices and technological processes, distributing limited resources and planning business functioning as well as with everyday problems of people. Devices, processes and situations to which a model of optimization problem is applied are called optimization problems. Optimization methods enable optimal solutions for mathematical models. The developed course is noted for building mathematical models and defining a method to be applied to finding an efficient solution.
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McWilliams, Jennifer, und Melanie Jung. Development of a Mathematical Air-Leakage Model from MeasuredData. Office of Scientific and Technical Information (OSTI), Mai 2006. http://dx.doi.org/10.2172/883786.

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6

Schneider, Michael L., und Richard E. Price. Temperature Analysis: Howard A. Hanson Reservoir, Washington. Mathematical Model Investigation. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada200228.

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7

Smith, F. G. III. Mathematical model of the Savannah River Site waste tank farm. Office of Scientific and Technical Information (OSTI), Juli 1991. http://dx.doi.org/10.2172/5788555.

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8

Smith, F. G. III. Mathematical model of the Savannah River Site waste tank farm. Office of Scientific and Technical Information (OSTI), Juli 1991. http://dx.doi.org/10.2172/10131180.

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9

Näslund-Hadley, Emma. IDB Briefly Noted: No. 9 : June, 2011: Less Talk, More Play: Bolstering Math Learning in Argentina. Inter-American Development Bank, Juni 2011. http://dx.doi.org/10.18235/0008215.

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Annotation:
Argentina and the Inter-American Development Bank (IDB) joined forces to test a new math education model called Mathematics for All (MAT). After just one academic year, learning increased in schools using the model, with particularly dramatic improvements among underperforming students. This brief describes how MAT improved learning by focusing on the development of mathematical thinking rather than on the memorization of formulas.
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10

De Silva, K. N. A mathematical model for optimization of sample geometry for radiation measurements. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1988. http://dx.doi.org/10.4095/122732.

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