Relevant bibliographies by topics / Economics and mathematical modeling

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Economics and mathematical modeling'

Author: Grafiati
Published: 28 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Economics and mathematical modeling"

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Guerrini, Luca. "Mathematical modeling in economics." Physics of Life Reviews 9, no. 4 (2012): 415–17. http://dx.doi.org/10.1016/j.plrev.2012.08.005.

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Artamonov, A. A. "FORMALISM OF PHENOMENOLOGICAL THEORY IN MATHEMATICAL MODELING OF ECONOMIC PROCESSES." Прогрессивная экономика, no. 10 (October 8, 2024): 7–18. http://dx.doi.org/10.54861/27131211_2024_10_7.

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Introduction: In contrast to neoclassical economics, where agents are rational, their actions are rational, and they strive for equilibrium, complex economics proposes to consider systems as evolving, complex, and not necessarily striving for equilibrium. The application of complex economics is particularly relevant in conditions of uncertainty and rapidly changing economic conditions. To develop the tools of complex economics, it is necessary to search for new mathematical approaches; a revolutionary approach in economics could be an approach based on the formalism of phenomenological theory.
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Latysheva, O., and Yu Chupryna. "Economic and Mathematical Modeling in Budgeting." Economic Herald of the Donbas, no. 4 (74) (2023): 32–36. http://dx.doi.org/10.12958/1817-3772-2023-4(74)-32-36.

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The article is devoted to an overview of modern modeling approaches for effective management of enterprise budgets. The article examines the toolkit of economic and mathematical modeling that can be used in the budgeting system. It is proposed to increase the efficiency of the budgeting process by applying the tools of economic and mathematical modeling at the stages of budget development and resource allocation, as well as in the process of budget control and monitoring. To increase the clarity of the simulation procedure and results, a visualization of the TO BE model is presented in IDF0 no
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Makarov, Sergey I. "Mathematical modeling skills development among students of universities of economics." Samara Journal of Science 9, no. 2 (2020): 254–57. http://dx.doi.org/10.17816/snv202307.

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This paper discusses approaches to economic and mathematical modeling skills development among students of universities of economics. The need for this competency among specialists in the digital economy is shown. The motivation of the student the future specialist in the digital economy in mastering the basic techniques of economic processes and systems modeling is outlined. The sections of the school course in mathematics are given, which are the basis for the development of these skills. Mathematical courses are examined; their study is considered to be the foundation for the development of
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N.V., Murzina. "MATHEMATICAL METHODS IN ECONOMICS." ИННОВАЦИОННЫЕ НАУЧНЫЕ ИССЛЕДОВАНИЯ 2022. 6-1(20) (September 17, 2022): 87–91. https://doi.org/10.5281/zenodo.7089449.

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The paper deals with mathematical problems using the concepts of covariance and correlation. The article highlights the relationship between mathematics and economics. The object of consideration and study are mathematical concepts and laws, economic phenomena and models. The paper analyzes the basic concepts of economics and the patterns of economic processes. Features of the application of mathematical methods in economics.
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Saikinov, Viktor E., Alexander L. Zolkin, Taisiya G. Garbuzova, and Rasul K. Khubiev. "MATHEMATICAL MODELING IN THE ECONOMIC PROCESS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 8/6, no. 149 (2024): 5–13. http://dx.doi.org/10.36871/ek.up.p.r.2024.08.06.001.

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The article presents an analysis of mathematical models that allow for the assessment and forecasting of economic processes. The purpose of the work is to analyze existing models taking into account current economic conditions and potential development. The research uses methods of econometrics modeling in the analysis of socio-economic processes and their interactions. Attention is paid to the importance of mathematical modeling and improving the accuracy of economic forecasts necessary for making effective management decisions. The authors consider specific models and techniques that are app
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Abduvahobovich, Nazarov Xolmòmin. "MATHEMATICS FOR ECONOMISTS: THE ESSENTIAL TOOLBOX." International Journal of Pedagogics 4, no. 6 (2024): 51–55. http://dx.doi.org/10.37547/ijp/volume04issue06-08.

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Mathematics serves as a cornerstone for the field of economics, providing the essential tools for modeling, analyzing, and solving economic problems. This article delves into the importance of mathematics in economics, exploring key mathematical concepts and methods used by economists to understand and predict economic phenomena. By highlighting the interplay between mathematics and economics, we underscore the necessity of a robust mathematical foundation for both theoretical and applied economic analysis.
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Mokhov, Veniamin, Sergei Aliukov, Anatoliy Alabugin, and Konstantin Osintsev. "A Review of Mathematical Models of Macroeconomics, Microeconomics, and Government Regulation of the Economy." Mathematics 11, no. 14 (2023): 3246. http://dx.doi.org/10.3390/math11143246.

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This review analyzes articles on the mathematical modeling of economic facts and processes. Mathematical modeling of the economy has rapidly developed in the past and current centuries. This is explained by the fact that, firstly, economics does not tolerate full-scale experiments, secondly, mathematical modeling significantly improves the accuracy of research results, and, finally, thirdly, economics becomes a science only when it is based on mathematics. The article presents an overview of the main methods of economic modeling used in scientific research over the past twenty years. The revie
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Khurazovna, Aymatova Farida, and Shamsiyev Damin Najmiddinovich. "Mathematical Modeling of Company Activity." American Journal of Applied Science and Technology 5, no. 3 (2025): 38–41. https://doi.org/10.37547/ajast/volume05issue03-07.

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The article discusses the tasks of mathematical modeling of economic processes, particularly focusing on the mathematical modeling of tourism company activities. Under given conditions, a mathematical model is constructed, an optimal solution is found, and the results are analyzed.
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Köhler, Angela D. A. "The Dangers of Mathematical Modeling." Mathematics Teacher 95, no. 2 (2002): 140–45. http://dx.doi.org/10.5951/mt.95.2.0140.

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When setting long-term goals, mathematics teachers face a constant dilemma. Most of us realize that our students will need to be mathematically literate in their future jobs, be able to see the real world through mathematical eyes, and be ready to handle the huge quantities of numbers that will be presented to them in their company's reports and in the news. During most of the school year, however, we give our students problems that are already written in mathematical language. Even the socalled real-life applications often consist of just an equation from physics, medicine, or economics that
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Dissertations / Theses on the topic "Economics and mathematical modeling"

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GIRIBONE, PIER GIUSEPPE. "Mathematical modeling in Quantitative Finance and Computational Economics." Doctoral thesis, Università degli studi di Genova, 2021. http://hdl.handle.net/11567/1046108.

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The first part of my PhD Thesis deals with different Machine Learning techniques mainly applied to solve financial engineering and risk management issues. After a short literary review, every chapter analyzes a particular topic linked to the implementation of these models, showing the most suitable methodologies able to solve it efficiently. The following topics are therefore covered: *) Data Fitting and Regression *) Forecasting *) Classification *) Outlier Detection and Data Quality *) Pricing Every chapter provides the theoretical explanation of the model, the description of the impl
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Menzies, Nicolas Alan. "Mathematical Modeling to Evaluate Disease Control Policy." Thesis, Harvard University, 2014. http://dissertations.umi.com/gsas.harvard:11356.

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In this dissertation I assessed three distinct policy questions: the implications of introducing a new tuberculosis diagnostic in southern Africa, the potential value of research related to HIV treatment policy in South Africa, and the causal effect of state cigarette taxes imposed between 1996 and 2013 on health outcomes in the United States.
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Fatouros, Dimitrios Michael. "Mathematical modelling for international tax planning." Thesis, Imperial College London, 1998. http://hdl.handle.net/10044/1/7954.

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Shockley, Jordan Murphy. "WHOLE FARM MODELING OF PRECISION AGRICULTURE TECHNOLOGIES." UKnowledge, 2010. http://uknowledge.uky.edu/gradschool_diss/105.

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This dissertation investigated farm management concerns faced by grain producers due to the acquisition of various precision agriculture technologies. The technologies evaluated in the three manuscripts included 1) auto-steer navigation, 2) automatic section control, and 3) autonomous machinery. Each manuscript utilized a multifaceted economic model in a whole-farm decision-making framework to determine the impact of precision agriculture technology on machinery management, production management, and risk management. This approach allowed for a thorough investigation into various precision agr
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Chow, Fung-kiu, and 鄒鳳嬌. "Modeling the minority-seeking behavior in complex adaptive systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2003. http://hub.hku.hk/bib/B29367487.

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Blix, Magnus. "Essays in mathematical finance : modeling the futures price." Doctoral thesis, Handelshögskolan i Stockholm, Finansiell Ekonomi (FI), 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:hhs:diva-534.

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This thesis consists of four papers dealing with the futures price process. In the first paper, we propose a two-factor futures volatility model designed for the US natural gas market, but applicable to any futures market where volatility decreases with maturity and varies with the seasons. A closed form analytical expression for European call options is derived within the model and used to calibrate the model to implied market volatilities. The result is used to price swaptions and calendar spread options on the futures curve. In the second paper, a financial market is specified where the und
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Catney, Denise Catherine. "Mathematical modelling of abbatoir condemnation data." Thesis, Queen's University Belfast, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.388044.

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Дядечко, Алла Миколаївна, Алла Николаевна Дядечко, Alla Mykolaivna Diadechko, and N. M. Manko. "Mathematical modeling economic growth within the framework of solow model." Thesis, Видавництво СумДУ, 2010. http://essuir.sumdu.edu.ua/handle/123456789/17577.

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Васильєва, Тетяна Анатоліївна, Татьяна Анатольевна Васильева, Tetiana Anatoliivna Vasylieva, et al. "Economic and mathematical modeling reasons for differentiated development of pandemic in ukraine." Thesis, Sumy State University, 2020. https://essuir.sumdu.edu.ua/handle/123456789/80947.

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The question of the negative effects virus COVID-19 has changed the vector of scientific interests of many scientists. Economists' goal is a find quick way to overcome the economic crisis, by reason of total quarantine and search the cause-and-effect relationships between the different spread of the disease within country.
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Melegaro, Alessia. "Epidemiology, mathematical modelling and economics of Streptococcus pneumoniae : assessing the potential impact of vaccination." Thesis, University of Warwick, 2005. http://wrap.warwick.ac.uk/61760/.

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This thesis explores aspects of Streptococcus pneumoniae (pneumococcus) epidemiology and control, in view of the possible widespread introduction of conjugate vaccines in England and Wales. A review and analysis of a range of different epidemiological data sources showed that the burden of pneumococcal disease in England and Wales is high and remains mostly a condition of the very young and the elderly. A meta-analysis demonstrated the effectiveness of the polysaccharide vaccine against invasive pneumococcal disease among healthy elderly, to whom vaccination was not recommended at the start of
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Books on the topic "Economics and mathematical modeling"

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Champ, Bruce. Modeling monetary economics. Wiley, 1994.

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Hritonenko, Natali. Mathematical modeling in economics, ecology, and environment. Kluwer Academic Publishers, 1999.

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ova, Jitka Dupac. Stochastic modeling in economics and finance. Kluwer Academic Publishers, 2002.

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Dupačová, Jitka. Stochastic modeling in economics and finance. Kluwer Academic Publishers, 2002.

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Frank, Schweitzer, ed. Modeling complexity in economic and social systems. World Scientific, 2002.

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Hritonenko, Natali. Mathematical Modeling in Economics, Ecology and the Environment. Springer US, 1999.

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Champ, Bruce. Modeling monetary economies. J. Willey, 1994.

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P, I︠A︡t︠s︡enko I︠U︡, ed. Mathematical modeling in economics, ecology, and environment. Kluwer Academic Publishers, 1999.

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Hritonenko, Natali, and Yuri Yatsenko. Mathematical Modeling in Economics, Ecology and the Environment. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4419-9733-3.

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Hritonenko, Natali, and Yuri Yatsenko. Mathematical Modeling in Economics, Ecology and the Environment. Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-9311-2.

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Book chapters on the topic "Economics and mathematical modeling"

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Serovajsky, Simon. "Mathematical model of economics." In Mathematical Modelling. Chapman and Hall/CRC, 2021. http://dx.doi.org/10.1201/9781003035602-8.

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Petrova, Elizaveta A., Tamara K. Filimonova, and Galina A. Ovseenko. "Mathematical Modeling of Transportation Flows." In Finance, Economics, and Industry for Sustainable Development. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56380-5_31.

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Gil Martín, Samuel. "Fundamental Principles of Modeling in Macroeconomics." In Trends in Mathematical Economics. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-32543-9_9.

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Winkelmann, Rainer. "Econometric Modeling — Extensions." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-662-21735-1_4.

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Gersovitz, Mark. "Mathematical Epidemiology and Welfare Economics." In Modeling the Interplay Between Human Behavior and the Spread of Infectious Diseases. Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5474-8_12.

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Leopold-Wildburger, Ulrike. "Experimental Economics." In Mathematical Modelling in Economics. Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78508-5_64.

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Yu, Jiaji, Haojin Zhang, Yangyang Chen, Aixu Zhang, and Fengzhi Liu. "AI-Driven Economic Forecasting: Integrating Mathematical Modeling into Western Economics." In Advances in Economics, Business and Management Research. Atlantis Press International BV, 2025. https://doi.org/10.2991/978-94-6463-702-1_39.

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Winkelmann, Rainer. "Econometric Modeling — Basic Issues." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-662-21735-1_3.

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Hritonenko, Natali, and Yuri Yatsenko. "Mathematical Models of Biological Populations." In Mathematical Modeling in Economics, Ecology and the Environment. Springer US, 2013. http://dx.doi.org/10.1007/978-1-4614-9311-2_6.

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Jeliazkov, Ivan, and Mohammad Arshad Rahman. "Binary and Ordinal Data Analysis in Economics: Modeling and Estimation." In Mathematical Modeling with Multidisciplinary Applications. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118462706.ch6.

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Conference papers on the topic "Economics and mathematical modeling"

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Meftah, Mohammed Charaf Eddine, Abdelkader Laouid, Mostefa Kara, et al. "Mathematical Modeling of a Programmable Decision Network to Simulate the Socio-Economic Environment." In 2024 9th International Conference on Mathematics and Computers in Sciences and Industry (MCSI). IEEE, 2024. https://doi.org/10.1109/mcsi63438.2024.00015.

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Popova-Krumova, Petya, Sofia Yankova, and Biliana Ilieva. "Mathematical modeling of glycerol biotransformation." In 39TH INTERNATIONAL CONFERENCE APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS AMEE13. AIP, 2013. http://dx.doi.org/10.1063/1.4854744.

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Gushchin, Valentin A., and Pavel V. Matyushin. "Mathematical modeling of the incompressible fluid flows." In APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS (AMEE'14). AIP Publishing LLC, 2014. http://dx.doi.org/10.1063/1.4902468.

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Velmisov, Petr A., Andrey V. Ankilov, and Elizaveta P. Semenova. "Mathematical modeling of aeroelastic systems." In PROCEEDINGS OF THE 43RD INTERNATIONAL CONFERENCE APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS: (AMEE’17). Author(s), 2017. http://dx.doi.org/10.1063/1.5013977.

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Durcheva, Mariana, and Elena Nikolova. "Modeling mathematical logic using MAPLE." In PROCEEDINGS OF THE 44TH INTERNATIONAL CONFERENCE ON APPLICATIONS OF MATHEMATICS IN ENGINEERING AND ECONOMICS: (AMEE’18). Author(s), 2018. http://dx.doi.org/10.1063/1.5082125.

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Krivosheev, Oleg I. "Labour Excess and Social-Economic Inequality Phenomena in Agricultural Economics." In 2022 4th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). IEEE, 2022. http://dx.doi.org/10.1109/summa57301.2022.9974121.

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Sun, Xiaoying, and Chongkun Xu. "Research on the teaching of advanced mathematics into the idea of mathematical modeling." In 4th International Conference on Management Science, Education Technology, Arts, Social Science and Economics 2016. Atlantis Press, 2016. http://dx.doi.org/10.2991/msetasse-16.2016.75.

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Gao, Zheng, Xiaojing Tao, and Yubin Pan. "Quality Education of Political Thought in Mathematical Modeling." In Proceedings of the 2019 3rd International Conference on Education, Management Science and Economics (ICEMSE 2019). Atlantis Press, 2019. http://dx.doi.org/10.2991/icemse-19.2019.18.

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Zhang, Li. "Teaching Research in Probability Theory and Mathematical Statistics Modeling Idea." In 2015 3rd International Conference on Education, Management, Arts, Economics and Social Science. Atlantis Press, 2016. http://dx.doi.org/10.2991/icemaess-15.2016.60.

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Velmisov, Petr A., Yuliya V. Pokladova, and Usama J. Mizher. "Mathematical modeling of the mechanical system “pipeline - pressure sensor”." In PROCEEDINGS OF THE 45TH INTERNATIONAL CONFERENCE ON APPLICATION OF MATHEMATICS IN ENGINEERING AND ECONOMICS (AMEE’19). AIP Publishing, 2019. http://dx.doi.org/10.1063/1.5133495.

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Reports on the topic "Economics and mathematical modeling"

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Roberts, D. L., and D. E. Gottschlich. Mathematical modeling and economic analysis of membrane separation of hydrogen from gasifier synthesis gas. Mathematical modeling topical report. Office of Scientific and Technical Information (OSTI), 1988. http://dx.doi.org/10.2172/10161735.

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Hlushak, Oksana M., Svetlana O. Semenyaka, Volodymyr V. Proshkin, Stanislav V. Sapozhnykov, and Oksana S. Lytvyn. The usage of digital technologies in the university training of future bachelors (having been based on the data of mathematical subjects). [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3860.

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This article demonstrates that mathematics in the system of higher education has outgrown the status of the general education subject and should become an integral part of the professional training of future bachelors, including economists, on the basis of intersubject connection with special subjects. Such aspects as the importance of improving the scientific and methodological support of mathematical training of students by means of digital technologies are revealed. It is specified that in order to implement the task of qualified training of students learning econometrics and economic and m
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Pasupuleti, Murali Krishna. Quantum Cognition: Modeling Decision-Making with Quantum Theory. National Education Services, 2025. https://doi.org/10.62311/nesx/rrvi225.

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Abstract Quantum cognition applies quantum probability theory and mathematical principles from quantum mechanics to model human decision-making, reasoning, and cognitive processes beyond the constraints of classical probability models. Traditional decision theories, such as expected utility theory and Bayesian inference, struggle to explain context-dependent reasoning, preference reversals, order effects, and cognitive biases observed in human behavior. By incorporating superposition, interference, and entanglement, quantum cognitive models offer a probabilistic framework that better accounts
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Saptsin, Vladimir, and Володимир Миколайович Соловйов. Relativistic quantum econophysics – new paradigms in complex systems modelling. [б.в.], 2009. http://dx.doi.org/10.31812/0564/1134.

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This work deals with the new, relativistic direction in quantum econophysics, within the bounds of which a change of the classical paradigms in mathematical modelling of socio-economic system is offered. Classical physics proceeds from the hypothesis that immediate values of all the physical quantities, characterizing system’s state, exist and can be accurately measured in principle. Non-relativistic quantum mechanics does not reject the existence of the immediate values of the classical physical quantities, nevertheless not each of them can be simultaneously measured (the uncertainty principle
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Voronina, Darina Evgenievna. Complex verification in the tasks of economic and mathematical modeling of spatial economic systems. Institute for Regional Economic Studies Russian Academy of Science, 2025. https://doi.org/10.52897/tms-2025-05-05.

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Roberts, D. L., and D. E. Gottschlich. Mathematical modeling and economic analysis of membrane separation of hydrogen from gasifier synthesis gas. Office of Scientific and Technical Information (OSTI), 1988. http://dx.doi.org/10.2172/5046000.

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Saptsin, V., Володимир Миколайович Соловйов, and I. Stratychuk. Quantum econophysics – problems and new conceptions. КНУТД, 2012. http://dx.doi.org/10.31812/0564/1185.

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This article is dedicated to the econophysical analysis of conceptual fundamentals and mathematical apparatus of classical physics, relativity theory, non-relativistic and relativistic quantum mechanics. The historical and methodological aspects as well as the modern state of the problem of the socio-economic modeling are considered.
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Alexey Sergeevich, Mikulenok. Economic and mathematical modeling in the tasks of regional management of the Arctic zone of the Russian Federation. Institute for Regional Economic Studies Russian Academy of Science, 2024. http://dx.doi.org/10.52897/tms-2024-14-10.

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Equihua, M., and O. Perez-Maqueo. Mathematical Modeling and Conservation. American Museum of Natural History, 2010. http://dx.doi.org/10.5531/cbc.ncep.0154.

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Formal models are indispensable tools in natural resource management and in conservation biology. Explicit modeling can be a helpful tool for studying these systems, communicating across disciplines, and integrating varying viewpoints of numerous stakeholders. This module demonstrates how to explicitly construct models as alternative representations to help interpret and understand nature. Through a synthesis and two exercises, it describes the general context of scientific modeling (i.e., use and types of models), and allows students to practice building a model by evaluating the relationship
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Mitler, Henri E. Mathematical modeling of enclosure fires. National Institute of Standards and Technology, 1991. http://dx.doi.org/10.6028/nist.ir.90-4294.

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