Academic literature on the topic 'Risk assessment - Mathematical models'
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Journal articles on the topic "Risk assessment - Mathematical models"
Park, Colin N. "Mathematical models in quantitative assessment of carcinogenic risk." Regulatory Toxicology and Pharmacology 9, no. 3 (June 1989): 236–43. http://dx.doi.org/10.1016/0273-2300(89)90062-7.
Full textDe Wrachien, D., and S. Mambretti. "Mathematical models for flood hazard assessment." International Journal of Safety and Security Engineering 1, no. 4 (December 31, 2011): 353–62. http://dx.doi.org/10.2495/safe-v1-n4-353-362.
Full textKodell, Ralph L. "The use of mathematical models in carcinogenesis risk assessment." Mathematical and Computer Modelling 11 (1988): 146–51. http://dx.doi.org/10.1016/0895-7177(88)90470-0.
Full textСычев, Михаил, Mikhail Sychev, Владимир Минаев, Vladimir Minaev, Александр Фаддеев, and Aleksandr Faddeev. "Seismic risk assessment in tourist-recreational areas: mathematical models." Servis Plus 9, no. 2 (June 15, 2015): 25–34. http://dx.doi.org/10.12737/11309.
Full textEuhus, David M. "Understanding Mathematical Models for Breast Cancer Risk Assessment and Counseling." Breast Journal 7, no. 4 (July 2001): 224–32. http://dx.doi.org/10.1046/j.1524-4741.2001.20012.x.
Full textSeigneur, Christian, Akula Venkatram, Don Galya, Paul Anderson, David Liu, Donna Foliart, Rudolph von Burg, Yoram Cohen, Thomas Permutt, and Leonard Levin. "Review of mathematical models for health risk assessment: I. Overview." Environmental Software 7, no. 1 (January 1992): 3–7. http://dx.doi.org/10.1016/0266-9838(92)90018-y.
Full textSeigneur, Christian. "Review of mathematical models for health risk assessment: VI. population exposure." Environmental Software 9, no. 2 (January 1994): 133–45. http://dx.doi.org/10.1016/0266-9838(94)90005-1.
Full textLiu, David. "Review of mathematical models for health risk assessment: VII. chemical dose." Environmental Software 9, no. 3 (January 1994): 153–60. http://dx.doi.org/10.1016/0266-9838(94)90027-2.
Full textZirka, Andrii, Mariia Zirka, and Natalia Kadet. "FEATURES OF RISK ASSESSMENT IN THE CREATION OF UAV FOR VARIOUS PURPOSES." Science-based technologies 51, no. 3 (October 28, 2021): 193–204. http://dx.doi.org/10.18372/2310-5461.51.15994.
Full textMinaev, V. A., N. G. Topolsky, A. O. Faddeev, R. O. Stepanov, and D. S. Grachev. "Risk assessment models with functionally different influences on natural and technical systems." Technology of technosphere safety 89 (2020): 8–19. http://dx.doi.org/10.25257/tts.2020.3.89.8-19.
Full textDissertations / Theses on the topic "Risk assessment - Mathematical models"
Yeo, Keng Leong Actuarial Studies Australian School of Business UNSW. "Claim dependence in credibility models." Awarded by:University of New South Wales. School of Actuarial Studies, 2006. http://handle.unsw.edu.au/1959.4/25971.
Full textWang, Na. "Estimation of Extra Risk and Benchmark Dose in Dose Response Models." Fogler Library, University of Maine, 2008. http://www.library.umaine.edu/theses/pdf/WangN2008.pdf.
Full textZhu, Dongming 1963. "Asymmetric heavy-tailed distributions : theory and applications to finance and risk management." Thesis, McGill University, 2007. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=102854.
Full textOwen, Michelle L. "Exposure model : detailed profiling and quantification of the exposure of personnel to geotechnical hazards in underground mines." University of Western Australia. School of Civil and Resource Engineering, 2004. http://theses.library.uwa.edu.au/adt-WU2005.0031.
Full textKusnetsov, Michael. "Clearing models for systemic risk assessment in interbank networks." Thesis, London School of Economics and Political Science (University of London), 2018. http://etheses.lse.ac.uk/3804/.
Full textShen, Yunxiang. "Risk analysis and its application in mining project evaluation." Thesis, McGill University, 1987. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=64009.
Full textGalane, Lesiba Charles. "The risk parity approach to asset allocation." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95974.
Full textENGLISH ABSTRACT: We consider the problem of portfolio's asset allocation characterised by risk and return. Prior to the 2007-2008 financial crisis, this important problem was tackled using mainly the Markowitz mean-variance framework. However, throughout the past decade of challenging markets, particularly for equities, this framework has exhibited multiple drawbacks. Today many investors approach this problem with a 'safety first' rule that puts risk management at the heart of decision-making. Risk-based strategies have gained a lot of popularity since the recent financial crisis. One of the 'trendiest' of the modern risk-based strategies is the Risk Parity model, which puts diversification in terms of risk, but not in terms of dollar values, at the core of portfolio risk management. Inspired by the works of Maillard et al. (2010), Bruder and Roncalli (2012), and Roncalli and Weisang (2012), we examine the reliability and relationship between the traditional mean-variance framework and risk parity. We emphasise, through multiple examples, the non-diversification of the traditional mean-variance framework. The central focus of this thesis is on examining the main Risk-Parity strategies, i.e. the Inverse Volatility, Equal Risk Contribution and the Risk Budgeting strategies. Lastly, we turn our attention to the problem of maximizing the absolute expected value of the logarithmic portfolio wealth (sometimes called the drift term) introduced by Oderda (2013). The drift term of the portfolio is given by the sum of the expected price logarithmic growth rate, the expected cash flow, and half of its variance. The solution to this problem is a linear combination of three famous risk-based strategies and the high cash flow return portfolio.
AFRIKAANSE OPSOMMING: Ons kyk na die probleem van batetoewysing in portefeuljes wat gekenmerk word deur risiko en wins. Voor die 2007-2008 finansiele krisis, was hierdie belangrike probleem deur die Markowitz gemiddelde-variansie raamwerk aangepak. Gedurende die afgelope dekade van uitdagende markte, veral vir aandele, het hierdie raamwerk verskeie nadele getoon. Vandag, benader baie beleggers hierdie probleem met 'n 'veiligheid eerste' reël wat risikobestuur in die hart van besluitneming plaas. Risiko-gebaseerde strategieë het baie gewild geword sedert die onlangse finansiële krisis. Een van die gewildste van die moderne risiko-gebaseerde strategieë is die Risiko- Gelykheid model wat diversifikasie in die hart van portefeulje risiko bestuur plaas. Geïnspireer deur die werke van Maillard et al. (2010), Bruder and Roncalli (2012), en Roncalli and Weisang (2012), ondersoek ons die betroubaarheid en verhouding tussen die tradisionele gemiddelde-variansie raamwerk en Risiko- Gelykheid. Ons beklemtoon, deur middel van verskeie voorbeelde, die niediversifikasie van die tradisionele gemiddelde-variansie raamwerk. Die sentrale fokus van hierdie tesis is op die behandeling van Risiko-Gelykheid strategieë, naamlik, die Omgekeerde Volatiliteit, Gelyke Risiko-Bydrae en Risiko Begroting strategieë. Ten slotte, fokus ons aandag op die probleem van maksimering van absolute verwagte waarde van die logaritmiese portefeulje welvaart (soms genoem die drif term) bekendgestel deur Oderda (2013). Die drif term van die portefeulje word gegee deur die som van die verwagte prys logaritmiese groeikoers, die verwagte kontantvloei, en die helfte van die variansie. Die oplossing vir hierdie probleem is 'n lineêre kombinasie van drie bekende risiko-gebaseerde strategieë en die hoë kontantvloei wins portefeulje.
Blatt, Sharon L. "An in-depth look at the information ratio." Link to electronic thesis, 2004. http://www.wpi.edu/Pubs/ETD/Available/etd-0824104-155216/.
Full textBaade, Ingrid Annette. "Survival analysis diagnostics." Thesis, Queensland University of Technology, 1997.
Find full textGhosh, Gregory. "Lifesafety Analysis in the Building Firesafety Method." Digital WPI, 2004. https://digitalcommons.wpi.edu/etd-theses/1106.
Full textBooks on the topic "Risk assessment - Mathematical models"
Schmidli, Hanspeter. Characteristics of ruin probabilities in classical risk models with and without investment, Cox risk models and perturbed risk models. Århus, Denmark: University of Aarhus, Dept. of Theoretical Statistics, Institute of Mathematical Sciences, 2000.
Find full textQuantitative operational risk models. Boca Raton: Taylor & Francis, 2012.
Find full textMathematical methods of environmental risk modeling. Boston, USA: Kluwer Academic Publishers, 2001.
Find full textAven, Terje. Risk analysis. Chichester, West Sussex, United Kingdom: John Wiley & Sons, 2015.
Find full textRachev, Svetlozar T. Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization. New York: John Wiley & Sons, Ltd., 2008.
Find full textGorelik, V. A. Modeli ot︠s︡enki kollektivnogo i sistemnogo riska. Moskva: Vychislitelʹnyĭ t︠s︡entr im. A.A. Dorodnit︠s︡yna Rossiĭskoĭ akademii nauk, 2011.
Find full textZhivetin, Vladimir. Banking system risk management: Mathematical modeling. Moscow: Institute for Risk Problems, 2012.
Find full textZhivetin, Vladimir. Vvedenie v teorii︠u︡ riska (dinamicheskikh sistem). Moskva: In-t problem riska, 2008.
Find full textJemel̦janovs, A. Objekta riska novērtēšana. Rīga: Rīgas Tehniskā universitāte, 2007.
Find full textZhivetin, Vladimir. Vvedenie v sistemnui︠u︡ riskologii︠u︡: Strukturno-funkt︠s︡ionalʹnai︠a︡ teorii︠a︡ sistem (v chetyrekh tomakh). Moskva: Institut problem riska, 2012.
Find full textBook chapters on the topic "Risk assessment - Mathematical models"
Brannigan, Vincent, and Carol Smidts. "Risk Based Regulation Using Mathematical Risk Models." In Probabilistic Safety Assessment and Management ’96, 721–25. London: Springer London, 1996. http://dx.doi.org/10.1007/978-1-4471-3409-1_115.
Full textHill, M. D. "Use of Mathematical Models in Risk Assessment and Risk Management." In Radionuclides in the Food Chain, 335–61. London: Springer London, 1988. http://dx.doi.org/10.1007/978-1-4471-1610-3_24.
Full textWickramaratne, G. A. de S. "Application of Mathematical Dose-Response Models vs. Physiological Models in Risk Assessment in Reproductive Toxicology." In Risk Assessment of Prenatally-Induced Adverse Health Effects, 279–87. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-77753-0_21.
Full textSeo, Fumiko. "Multiple Risk Assessment with Random Utility Models in Probabilistic Group Decision Making." In Lecture Notes in Economics and Mathematical Systems, 161–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-57311-8_13.
Full textNavrátil, Josef, Veronika Sadovská, and Irena Švarcová. "Health Risk Assessment of Combustion Products from Simulated Residential Fire." In Mathematical-Statistical Models and Qualitative Theories for Economic and Social Sciences, 15–23. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-54819-7_2.
Full textAxelsen, Jørgen Aagaard. "A physiologically driven mathematical simulation model as a tool for extension of results from laboratory tests to ecosystem effects." In Ecological Risk Assessment of Contaminants in Soil, 233–50. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6361-7_11.
Full textBiswas, Swarnava, Anoop Kumar Prasad, Debajit Sen, Dinesh Bhatia, and Moumita Mukherjee. "Comparative Study on Predictive Mathematical Models for Risk Assessment of nCOVID-19 Pandemic in India." In Lecture Notes in Bioengineering, 393–404. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6915-3_39.
Full textCaminade, Cyril. "How to model the impact of climate change on vector-borne diseases?" In Climate, ticks and disease, 26–31. Wallingford: CABI, 2021. http://dx.doi.org/10.1079/9781789249637.0004.
Full textRausand, Marvin. "Accident Models." In Risk Assessment, 137–76. Hoboken, New Jersey: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118281116.ch6.
Full textCordell, Andrea, and Ian Thompson. "Risk Assessment." In The Procurement Models Handbook, 27–29. Third edition. | Abingdon, Oxon ; New York, NY : Routledge, 2019. | Earlier editions published as: Purchasing models handbook: a guide to the most popular business models used in purchasing / Andrea Reynolds and Ian Thompson.: Routledge, 2019. http://dx.doi.org/10.4324/9781351239509-9.
Full textConference papers on the topic "Risk assessment - Mathematical models"
Razzaghi, Mehdi. "Teaching Statistical Models for Risk Assessment." In Bridging the Gap: Empowering and Educating Today’s Learners in Statistics. International Association for Statistical Education, 2022. http://dx.doi.org/10.52041/iase.icots11.t6c1.
Full textZappalà, G., S. Bonamano, A. Madonia, G. Caruso, and M. Marcelli. "Microbiological risk assessment in a coastal marine environment through the use of mathematical models." In WATER POLLUTION 2012. Southampton, UK: WIT Press, 2012. http://dx.doi.org/10.2495/wp120011.
Full textDinis, Jairson, Ana I. Pereira, and Elza M. Fonseca. "Mathematical model for the assessment of fracture risk associated with osteoporosis." In NUMERICAL ANALYSIS AND APPLIED MATHEMATICS ICNAAM 2012: International Conference of Numerical Analysis and Applied Mathematics. AIP, 2012. http://dx.doi.org/10.1063/1.4756262.
Full textDevgun, Akash. "A rule based mathematical model to improve risk assessment on cloud server." In 2014 International Conference on Electronics,Communication and Computational Engineering (ICECCE). IEEE, 2014. http://dx.doi.org/10.1109/icecce.2014.7086617.
Full textSchnabel, Freya, Jennifer Chun, Shira Schwartz, Amber Guth, Deborah Axelrod, Richard Shapiro, Karen Hiotis, and Julia Smith. "Abstract A29: Mathematical models are not the be-all and end-all for breast cancer risk assessment." In Abstracts: AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; November 16-19, 2016; Orlando, FL. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7755.carisk16-a29.
Full textGrantham Lough, Katie, Robert Stone, and Irem Y. Tumer. "Function Based Risk Assessment: Mapping Function to Likelihood." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85053.
Full textMatuzas, Vaidas, Juozas Augutis, and Eugenijus Uspuras. "Degradation Assessment in Complex Systems." In 14th International Conference on Nuclear Engineering. ASMEDC, 2006. http://dx.doi.org/10.1115/icone14-89190.
Full textActon, Michael R., Phil J. Baldwin, Tim R. Baldwin, and Eric E. R. Jager. "The Development of the PIPESAFE Risk Assessment Package for Gas Transmission Pipelines." In 1998 2nd International Pipeline Conference. American Society of Mechanical Engineers, 1998. http://dx.doi.org/10.1115/ipc1998-2000.
Full textMoskvichev, V. V., U. S. Postnikova, and O. V. Taseiko. "Cluster analysis and individual anthropogenic risk." In Spatial Data Processing for Monitoring of Natural and Anthropogenic Processes 2021. Crossref, 2021. http://dx.doi.org/10.25743/sdm.2021.54.88.063.
Full textZafirovski, Zlatko, Vasko Gacevski, Zoran Krakutovski, Slobodan Ognjenovic, and Ivona Nedevska. "Methodology for tunnel risk assessment using fault and event tree analysis." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.1051.
Full textReports on the topic "Risk assessment - Mathematical models"
Lopez, A. R., L. A. Gritzo, and M. P. Sherman. Risk assessment compatible fire models (RACFMs). Office of Scientific and Technical Information (OSTI), July 1998. http://dx.doi.org/10.2172/661660.
Full textPloeger, S. K., M. J. Nollet, M. Sawada, and A. Abo El Ezz. Inventory models for regional scale natural hazards risk assessment. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 2018. http://dx.doi.org/10.4095/308352.
Full textWahl, L. E. A comparison of radiological risk assessment models: Risk assessment models used by the BEIR V Committee, UNSCEAR, ICRP, and EPA (for NESHAP). Office of Scientific and Technical Information (OSTI), March 1994. http://dx.doi.org/10.2172/10141938.
Full textEslinger, P. W., T. B. Miley, D. W. Engel, and P. J. II Chamberlain. SUMO, System performance assessment for a high-level nuclear waste repository: Mathematical models. Office of Scientific and Technical Information (OSTI), September 1992. http://dx.doi.org/10.2172/140865.
Full textEhrhart, Brian, and Ethan Hecht. Hydrogen Risk Assessment Models (HyRAM) Version 3.0 Technical Reference Manual. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1673177.
Full textEhrhart, Brian, and Ethan Hecht. Hydrogen Risk Assessment Models (HyRAM) Version 3.1 Technical Reference Manual. Office of Scientific and Technical Information (OSTI), May 2021. http://dx.doi.org/10.2172/1784842.
Full textDusicka, Peter. Bridge Damage Models for Seismic Risk Assessment of Oregon Highway Network. Portland State University Library, October 2011. http://dx.doi.org/10.15760/trec.19.
Full textJack Pashin, Guohai Jin, Chunmiao Zheng, Song Chen, and Marcella McIntyre. Discrete Fracture Network Models for Risk Assessment of Carbon Sequestration in Coal. Office of Scientific and Technical Information (OSTI), July 2008. http://dx.doi.org/10.2172/941131.
Full textHecht, Ethan, and Brian Ehrhart. Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) Version 4.0 Technical Reference Manual. Office of Scientific and Technical Information (OSTI), November 2021. http://dx.doi.org/10.2172/1832082.
Full textEhrhart, Brian, and Ethan Hecht. Hydrogen Plus Other Alternative Fuels Risk Assessment Models (HyRAM+) Version 4.1 Technical Reference Manual. Office of Scientific and Technical Information (OSTI), April 2022. http://dx.doi.org/10.2172/1865723.
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