Relevant bibliographies by topics / Risk assessment - Mathematical models

Contents

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

Academic literature on the topic 'Risk assessment - Mathematical models'

Author: Grafiati
Published: 4 June 2021
Last updated: 26 January 2023

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Journal articles on the topic "Risk assessment - Mathematical models"

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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.

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De 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.

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Kodell, 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.

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Сычев, 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.

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The article highlights the problem of evaluation of seismic risks in the tourism and recreational areas. To this end, the grounded and practically being tested mathematical model for evaluating the seismic stability of tourist-recreational area on the example of the Black Sea, the Caspian and the Mediterranean region. This model combines the influences of disturbances associated with the anomalous gravity field (vertical component), and takes into account modern crustal movements (horizontal component), calculated according to the space geodesy. The physical model of the geological environment
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Euhus, 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.

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Seigneur, 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.

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Seigneur, 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.

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Liu, 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.

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Zirka, 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.

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One of the perspective directions of the development to modern aviation is connected with designing and producing unmanned aerial vehicles (UAV) of various functionalities for applying in military and civilian spheres. The syntheses of UAV control systems, regardless of their type and purpose presumes the creation of adequate mathematical models, first of all adequate aerodynamic mathematical models. In the paper results that forms and justify the aerodynamic mathematical model and as well as the results of building a general mathematical model of the longitudinal movement of the perspective U
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Minaev, 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.

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Introduction. The complex combination of natural and technogenic factors that lead to dangerous threats to the health and life of the population, as well as to material values, creates a need to develop special mathematical models for risk assessment in the relevant territories. Herewith it is important to take into account the significant differences between these factors. The new areas of research are models that describe natural and technogenic risks using differential equations that reflect different types of functions. The article presents the development of this research area. Goals and
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Dissertations / Theses on the topic "Risk assessment - Mathematical models"

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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.

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Existing credibility models have mostly allowed for one source of claim dependence only, that across time for an individual insured risk or a group of homogeneous insured risks. Numerous circumstances demonstrate that this may be inadequate and insufficient. In this dissertation, we developed a two-level common effects model, based loosely on the Bayesian model, which allows for two possible sources of dependence, that across time for the same individual risk and that between risks. For the case of Normal common effects, we are able to derive explicit formulas for the credibility premium. This
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Wang, 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.

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Zhu, 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.

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This thesis focuses on construction, properties and estimation of asymmetric heavy-tailed distributions, as well as on their applications to financial modeling and risk measurement. First of all, we suggest a general procedure to construct a fully asymmetric distribution based on a symmetrically parametric distribution, and establish some natural relationships between the symmetric and asymmetric distributions. Then, three new classes of asymmetric distributions are proposed by using the procedure: the Asymmetric Exponential Power Distributions (AEPD), the Asymmetric Student-t Distributions (A
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Owen, 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.

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[Truncated abstract] This thesis presents an operationally applicable and reliable model for quantification of the exposure of underground mining personnel to geotechnical hazards. The model is shown to have the flexibility to apply to very different operational environments, within the context of mechanised metalliferous mines. It provides an essential component for carrying out quantitative geotechnical risk analyses of underground mines. Increasingly prevalent within the Australian mining industry are moves towards a riskbased philosophy instead of prescriptive design procedures. A barrier
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Kusnetsov, 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/.

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In this thesis I consider the problem of clearing models used for systemic risk assessment in interbank networks. I investigate two extensions of the classical Eisenberg & Noe (2001) model. The first extension permits the analysis of networks with interbank liabilities of several maturities. I describe a clearing mechanism that relies on a fixed-point formulation of the vector of each bank’s liquid assets at each maturity date for a given set of defaulted banks. This formulation is consistent with the main stylised principles of insolvency law, permits the construction of simple dynamic models
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Shen, 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.

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Galane, Lesiba Charles. "The risk parity approach to asset allocation." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/95974.

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Thesis (MSc)--Stellenbosch University, 2014.<br>ENGLISH 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 p
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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/.

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Baade, Ingrid Annette. "Survival analysis diagnostics." Thesis, Queensland University of Technology, 1997.

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Ghosh, Gregory. "Lifesafety Analysis in the Building Firesafety Method." Digital WPI, 2004. https://digitalcommons.wpi.edu/etd-theses/1106.

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"The purpose of this thesis is to demonstrate and enhance the technical basis of the procedure for evaluating lifesafety within the Building Firesafety Engineering Method (BFSEM). A framework for the analysis has been documented, but not extensively tested in a building situation. Hence, procedures to obtain the necessary input data and to evaluate that data needed to be developed. In addition, the general framework had to be tested rigorously enough to identify weaknesses. "
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Books on the topic "Risk assessment - Mathematical models"

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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.

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Quantitative operational risk models. Boca Raton: Taylor & Francis, 2012.

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Mathematical methods of environmental risk modeling. Boston, USA: Kluwer Academic Publishers, 2001.

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Aven, Terje. Risk analysis. Chichester, West Sussex, United Kingdom: John Wiley & Sons, 2015.

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Rachev, Svetlozar T. Advanced Stochastic Models, Risk Assessment, and Portfolio Optimization. New York: John Wiley & Sons, Ltd., 2008.

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Gorelik, V. A. Modeli ot︠s︡enki kollektivnogo i sistemnogo riska. Moskva: Vychislitelʹnyĭ t︠s︡entr im. A.A. Dorodnit︠s︡yna Rossiĭskoĭ akademii nauk, 2011.

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Zhivetin, Vladimir. Banking system risk management: Mathematical modeling. Moscow: Institute for Risk Problems, 2012.

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Zhivetin, Vladimir. Vvedenie v teorii︠u︡ riska (dinamicheskikh sistem). Moskva: In-t problem riska, 2008.

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Jemel̦janovs, A. Objekta riska novērtēšana. Rīga: Rīgas Tehniskā universitāte, 2007.

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Zhivetin, Vladimir. Vvedenie v sistemnui︠u︡ riskologii︠u︡: Strukturno-funkt︠s︡ionalʹnai︠a︡ teorii︠a︡ sistem (v chetyrekh tomakh). Moskva: Institut problem riska, 2012.

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Book chapters on the topic "Risk assessment - Mathematical models"

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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.

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Hill, 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.

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Wickramaratne, 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.

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Seo, 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.

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Navrátil, 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.

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Axelsen, 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.

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Biswas, 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.

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Caminade, 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.

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Abstract This expert opinion provides an overview of mathematical models that have been used to assess the impact of climate change on ticks and tick-borne diseases, ways forward in terms of improving models for the recent context and broad guidelines for conducting future climate change risk assessment.
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Rausand, Marvin. "Accident Models." In Risk Assessment, 137–76. Hoboken, New Jersey: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118281116.ch6.

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Cordell, 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.

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Conference papers on the topic "Risk assessment - Mathematical models"

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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.

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Risk analysis is used across many disciplines. Biological scientists use risk analysis to determine the chance of an adverse effect occurring. Engineers use it to assess the risk of structural failures. People in business and industry perform risk analysis to estimate profit and loss in decision making. Although there are many definitions of risk, the most accurate definition is based on probabilistic principles. To estimate risk quantitatively, a statistical model is used to describe the process and the associated risk is thereupon calculated. The underlying model and derivation of risk can l
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Zappalà, 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.

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Dinis, 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.

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Devgun, 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.

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Schnabel, 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.

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Grantham 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.

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Risk assessments are necessary to anticipate and prevent accidents from occurring or repeating. This paper focuses specifically on the relationship between function and risk by presenting a mathematical mapping from product function to risk likelihood. This type of mapping will aid designers by removing the subjectivity of the likelihood value from a risk element, provide three key risk element properties (design parameter, failure mode, and likelihood) for numerous risk elements with one simple mathematical calculation, and provide a means for inexperienced designers to effectively address ri
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Matuzas, 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.

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Components condition could change dynamically because of various dependencies existing in complex systems since usually not only physical connections exist in the system. Various processes (as degradation or wear out, reliability decrease, failures) affecting one component have influence to condition of other components as well. Current paper is devoted to the analysis and development of mathematical models to the reliability assessment of network systems. Degradation as the main process in the network systems is taken into account. The main attention in present work was paid to the mathematic
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Acton, 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.

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PIPESAFE is a knowledge based hazard and risk assessment package for gas transmission pipelines, which has been developed jointly by an international group of gas transmission companies. PIPESAFE has been developed from the BG (formerly British Gas) TRANSPIRE package, to produce an integrated assessment tool for use on PCs. which includes a range of improvements and additional models backed by large scale experimentation. This paper describes the development of the PIPESAFE package, and the formulation and validation of the mathematical models included within it.
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Moskvichev, 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.

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Models and assessment methods of anthropogenic risk are analyzed at this article, general basis of mathematical approach for risk analysis is disclosed. Based on multivariate statistic methods, algorithm of analysis for Siberian territories safety is formulated, it allows to define acceptable level of risk for each territorial group (cities with population density more than 70 000, towns with population less than 70 000, and municipals areas).
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Zafirovski, 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.

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The intense demand and construction of tunnels is accompanied by uncertainties. The reason for appearance of uncertainties are the complex solutions and conditions for these structures. Location and dimensions are becoming more challenging, and the construction is predicted in complexed geological conditions, leading to application of new approaches, methodologies and technologies by the engineers. Most of the uncertainties and unwanted events in tunnelling occur in the construction phase, which generally leads to economic consequences and time losses. For easier handling of the uncertainties,
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Reports on the topic "Risk assessment - Mathematical models"

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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.

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Ploeger, 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.

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Wahl, 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.

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Eslinger, 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.

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Ehrhart, 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.

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Ehrhart, 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.

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Dusicka, 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.

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Jack 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.

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Hecht, 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.

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Ehrhart, 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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