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Relevant bibliographies by topics / Probabilities – Mathematical models

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Dissertations / Theses
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Academic literature on the topic 'Probabilities – Mathematical models'

Author: Grafiati

Published: 4 June 2021

Last updated: 31 January 2023

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Journal articles on the topic "Probabilities – Mathematical models"

1

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

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

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Bronevich, A. G., and I. N. Rosenberg. "Applying models of imprecise probabilities in the mathematical theory of criteria importance." Automation and Remote Control 78, no. 8 (August 2017): 1460–73. http://dx.doi.org/10.1134/s0005117917080070.

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Lomeli, Luis Martinez, Abdon Iniguez, Prasanthi Tata, Nilamani Jena, Zhong-Ying Liu, Richard Van Etten, Arthur D. Lander, Babak Shahbaba, John S. Lowengrub, and Vladimir N. Minin. "Optimal experimental design for mathematical models of haematopoiesis." Journal of The Royal Society Interface 18, no. 174 (January 2021): 20200729. http://dx.doi.org/10.1098/rsif.2020.0729.

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The haematopoietic system has a highly regulated and complex structure in which cells are organized to successfully create and maintain new blood cells. It is known that feedback regulation is crucial to tightly control this system, but the specific mechanisms by which control is exerted are not completely understood. In this work, we aim to uncover the underlying mechanisms in haematopoiesis by conducting perturbation experiments, where animal subjects are exposed to an external agent in order to observe the system response and evolution. We have developed a novel Bayesian hierarchical framew

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Loucopoulos, Constantine. "Effect of prior probabilities on the classificatory performance of parametric and mathematical programming approaches to the two-group discriminant problem." Journal of Applied Mathematics and Decision Sciences 1, no. 1 (January 1, 1997): 45–51. http://dx.doi.org/10.1155/s1173912697000047.

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A mixed-integer programming model (MIP) incorporating prior probabilities for the two-group discriminant problem is presented. Its classificatory performance is compared against that of Fisher's linear discrimininant function (LDF) and Smith's quadradic discriminant function (QDF) for simulated data from normal and nonnormal populations for different settings of the prior probabilities of group membership. The proposed model is shown to outperform both LDF and QDF for most settings of the prior probabilities when the data are generated from nonnormal populations but underperforms the parametri

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Forrester, P. J., and G. E. Andrews. "Height probabilities in solid-on-solid models. II." Journal of Physics A: Mathematical and General 20, no. 13 (September 11, 1987): 4465–81. http://dx.doi.org/10.1088/0305-4470/20/13/046.

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Forrester, P. J., and G. E. Andrews. "Height probabilities in solid-on-solid models. I." Journal of Physics A: Mathematical and General 19, no. 15 (October 21, 1986): L923—L926. http://dx.doi.org/10.1088/0305-4470/19/15/011.

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Zhao, Ming-Jie, and Herbert Jaeger. "Norm-Observable Operator Models." Neural Computation 22, no. 7 (July 2010): 1927–59. http://dx.doi.org/10.1162/neco.2010.03-09-983.

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Hidden Markov models (HMMs) are one of the most popular and successful statistical models for time series. Observable operator models (OOMs) are generalizations of HMMs that exhibit several attractive advantages. In particular, a variety of highly efficient, constructive, and asymptotically correct learning algorithms are available for OOMs. However, the OOM theory suffers from the negative probability problem (NPP): a given, learned OOM may sometimes predict negative probabilities for certain events. It was recently shown that it is undecidable whether a given OOM will eventually produce such

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PYKACZ, JAROSŁAW, and BART D'HOOGHE. "BELL-TYPE INEQUALITIES IN FUZZY PROBABILITY CALCULUS." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 09, no. 02 (April 2001): 263–75. http://dx.doi.org/10.1142/s021848850100079x.

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Bell-type inequalities, used in mathematical physics as a criterion to check whether a physical situation allows description in terms of classical (Kolmogorovian) or quantum probability calculus are applied to various fuzzy probability models. It occurs that the standard set of Bell-type inequalities does not allow to distinguish Kolmogorovian probabilities from fuzzy probabilities based on the most frequently used Zadeh intersection or probabilistic intersection, but it allows to distinguish all these models from fuzzy probability models based on Giles (Łukasiewicz) intersection. It is proved

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Raza, Ahmed, and Vladimir Ulansky. "Optimization of Condition Monitoring Decision Making by the Criterion of Minimum Entropy." Entropy 21, no. 12 (December 4, 2019): 1193. http://dx.doi.org/10.3390/e21121193.

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Condition-based maintenance (CBM) is a promising technique for a wide variety of deteriorating systems. Condition-based maintenance’s effectiveness largely depends on the quality of condition monitoring. The majority of CBM mathematical models consider perfect inspections, in which the system condition is assumed to be determined error-free. This article presents a mathematical model of CBM with imperfect condition monitoring conducted at discrete times. Mathematical expressions were derived for evaluating the probabilities of correct and incorrect decisions when monitoring the system conditio

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Neustroev, S. S., V. I. Serdyukov, N. A. Serdyukova, and S. I. Shishkina. "Mathematical Modeling-based Analysis from the Great Patriotic War Events." Mathematics and Mathematical Modeling, no. 3 (August 25, 2019): 25–35. http://dx.doi.org/10.24108/mathm.0319.0000189.

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When fighting against terrorism in modern armed conflicts, combat vehicles, including tanks, are widely used. To minimise own losses of vehicles and personnel for overthrowing enemy is a relevant task. To solve it, the paper considers certain events in the history of the Great Patriotic War, which are associated with battle of tanks that spring an ambush. A mathematical model of the battle is built. The state graph of the system is given. Using this graph, a probability of tank kills and a ratio of mathematical expectations of losses have been calculated. This mathematical model generalizes th

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Dissertations / Theses on the topic "Probabilities – Mathematical models"

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Gong, Qi, and 龔綺. "Gerber-Shiu function in threshold insurance risk models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B40987966.

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Wan, Lai-mei. "Ruin analysis of correlated aggregate claims models." Thesis, Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B30705708.

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Huang, Sheng, and 黄盛. "Some properties of [¯gamma*n] and error control with group network codes." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B46606117.

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Wei, Zhenghong. "Empirical likelihood based evaluation for value at risk models." HKBU Institutional Repository, 2007. http://repository.hkbu.edu.hk/etd_ra/896.

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Kwan, Kwok-man, and 關國文. "Ruin theory under a threshold insurance risk model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38320034.

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Dunster, Joanne L. "Mathematical models of soft tissue injury repair : towards understanding musculoskeletal disorders." Thesis, University of Nottingham, 2012. http://eprints.nottingham.ac.uk/27797/.

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The process of soft tissue injury repair at the cellular lew I can be decomposed into three phases: acute inflammation including coagulation, proliferation and remodelling. While the later phases are well understood the early phase is less so. We produce a series of new mathematical models for the early phases coagulation and inflammation. The models produced are relevant not only to soft tissue injury repair but also to the many disease states in which coagulation and inflammation play a role. The coagulation cascade and the subsequent formation of the enzyme thrombin are central to the creat

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Venter, Rudolf Gerrit. "Pricing options under stochastic volatility." Diss., Pretoria : [s.n.], 2003. http://upetd.up.ac.za/thesis/available/etd09052005-120952.

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Sirkin, Jeffrey M. "Quantifying the probabilities of selection of surface warfare officers to executive officer." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2006. http://library.nps.navy.mil/uhtbin/hyperion/06Sep%5FSirkin.pdf.

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Thesis (M.S. in Operations Research)--Naval Postgraduate School, September 2006.<br>Thesis Advisor(s): Robert A. Koyak. "September 2006." Includes bibliographical references (p. 51). Also available in print.

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Przybyla, Craig Paul. "Microstructure-sensitive extreme value probabilities of fatigue in advanced engineering alloys." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34780.

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A novel microstructure-sensitive extreme value probabilistic framework is introduced to evaluate material performance/variability for damage evolution processes (e.g., fatigue, fracture, creep). This framework employs newly developed extreme value marked correlation functions (EVMCF) to identify the coupled microstructure attributes (e.g., phase/grain size, grain orientation, grain misorientation) that have the greatest statistical relevance to the extreme value response variables (e.g., stress, elastic/plastic strain) that describe the damage evolution processes of interest. This is an improv

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Reischman, Diann. "Order restricted inferences on parameters in generalized linear models with emphasis on logistic regression /." free to MU campus, to others for purchase, 1997. http://wwwlib.umi.com/cr/mo/fullcit?p9842560.

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Books on the topic "Probabilities – Mathematical models"

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Probabilities in physics. Oxford: Oxford University Press, 2011.

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Ross, Sheldon M. Applied probability models with optimization applications. New York: London, 1992.

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Ross, Sheldon M. Applied probability models with optimization applications. New York: Dover Publications, 1992.

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Puppe, Clemens. Distorted probabilities and choice under risk. Berlin: Springer-Verlag, 1991.

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Reeb, J. E. An introduction to models and probability concepts. Corvallis, Or: Oregon State University Extension Service, 1998.

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Reeb, J. E. An introduction to models and probability concepts. Corvallis, Or: Oregon State University Extension Service, 1998.

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Finite mathematics for the managerial, life, and social sciences. Belmont, CA: Brooks/Cole, Cengage Learning, 2012.

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Tan, Soo Tang. Finite mathematics for the managerial, life, and social sciences. 9th ed. Belmont, CA: Brooks/Cole Cengage Learning, 2009.

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Tan, Soo Tang. Finite mathematics for the managerial, life, and social sciences. 7th ed. Pacific Grove, CA: Thomson-Brooks/Cole, 2003.

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Tan, Soo Tang. Finite mathematics for the managerial, life, and social sciences. 6th ed. Pacific Grove, CA: Brooks/Cole, 2000.

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Book chapters on the topic "Probabilities – Mathematical models"

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Hendry, David F. "Mathematical Models and Economic Forecasting: Some Uses and Mis-Uses of Mathematics in Economics." In Probabilities, Laws, and Structures, 319–35. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3030-4_23.

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Vicig, Paolo. "Conditional and Comparative Probabilities in Artificial Intelligence." In Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, 271–80. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1424-8_19.

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Moral, Serafín, and Nic Wilson. "Revision Rules for Convex Sets of Probabilities." In Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, 113–27. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1424-8_7.

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Kordzakhia, Nino, Alexander Novikov, and Gurami Tsitsiashvili. "On ruin probabilities in risk models with interest rate." In Mathematical and Statistical Methods for Actuarial Sciences and Finance, 245–53. Milano: Springer Milan, 2012. http://dx.doi.org/10.1007/978-88-470-2342-0_29.

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Lafuente, Miguel, David Ejea, Raúl Gouet, F. Javier López, and Gerardo Sanz. "Approximations of $$\delta $$-Record Probabilities in i.i.d. and Trend Models." In Trends in Mathematical, Information and Data Sciences, 73–81. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04137-2_8.

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Di Biase, Giuseppe, and Antonio Maturo. "Checking the Coherence of Conditional Probabilities in Expert Systems: Remarks and Algorithms." In Mathematical Models for Handling Partial Knowledge in Artificial Intelligence, 191–200. Boston, MA: Springer US, 1995. http://dx.doi.org/10.1007/978-1-4899-1424-8_11.

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Aslett, Louis J. M. "Sampling from Complex Probability Distributions: A Monte Carlo Primer for Engineers." In Uncertainty in Engineering, 15–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-83640-5_2.

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AbstractModels which are constructed to represent the uncertainty arising in engineered systems can often be quite complex to ensure they provide a reasonably faithful reflection of the real-world system. As a result, even computation of simple expectations, event probabilities, variances, or integration over utilities for a decision problem can be analytically intractable. Indeed, such models are often sufficiently high dimensional that even traditional numerical methods perform poorly. However, access to random samples drawn from the probability model under study typically simplifies such problems substantially. The methodologies to generate and use such samples fall under the stable of techniques usually referred to as ‘Monte Carlo methods’. This chapter provides a motivation, simple primer introduction to the basics, and sign-posts to further reading and literature on Monte Carlo methods, in a manner that should be accessible to those with an engineering mathematics background. There is deliberately informal mathematical presentation which avoids measure-theoretic formalism. The accompanying lecture can be viewed at https://www.louisaslett.com/Courses/UTOPIAE/.

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Boumans, Marcel. "Mathematics as Quasi-matter to Build Models as Instruments." In Probabilities, Laws, and Structures, 307–18. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-3030-4_22.

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Bacharoudis, Konstantinos, Atanas Popov, and Svetan Ratchev. "Application of Advanced Simulation Methods for the Tolerance Analysis of Mechanical Assemblies." In IFIP Advances in Information and Communication Technology, 153–67. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72632-4_11.

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AbstractIn the frame of a statistical tolerance analysis of complex assemblies, for example an aircraft wing, the capability to predict accurately and fast specified, very small quantiles of the distribution of the assembly key characteristic becomes crucial. The problem is significantly magnified, when the tolerance synthesis problem is considered in which several tolerance analyses are performed and thus, a reliability analysis problem is nested inside an optimisation one in a fully probabilistic approach. The need to reduce the computational time and accurately estimate the specified probabilities is critical. Therefore, herein, a systematic study on several state of the art simulation methods is performed whilst they are critically evaluated with respect to their efficiency to deal with tolerance analysis problems. It is demonstrated that tolerance analysis problems are characterised by high dimensionality, high non-linearity of the state functions, disconnected failure domains, implicit state functions and small probability estimations. Therefore, the successful implementation of reliability methods becomes a formidable task. Herein, advanced simulation methods are combined with in-house developed assembly models based on the Homogeneous Transformation Matrix method as well as off-the-self Computer Aided Tolerance tools. The main outcome of the work is that by using an appropriate reliability method, computational time can be reduced whilst the probability of defected products can be accurately predicted. Furthermore, the connection of advanced mathematical toolboxes with off-the-self 3D tolerance tools into a process integration framework introduces benefits to successfully deal with the tolerance allocation problem in the future using dedicated and powerful computational tools.

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Bernhard, Pierre, Jacob C. Engwerda, Berend Roorda, J. M. Schumacher, Vassili Kolokoltsov, Patrick Saint-Pierre, and Jean-Pierre Aubin. "Emergence of Risk-Neutral Probabilities from a Game-Theoretic Origin." In The Interval Market Model in Mathematical Finance, 221–47. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-0-8176-8388-7_12.

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Conference papers on the topic "Probabilities – Mathematical models"

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Ma, Jin, and Xiaodong Sun. "Sharp Estimates of Ruin Probabilities for Insurance Models Involving Investments." In Proceedings of the International Conference on Mathematical Finance. WORLD SCIENTIFIC, 2001. http://dx.doi.org/10.1142/9789812799579_0007.

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Bruns, Morgan, and Christiaan J. J. Paredis. "Numerical Methods for Propagating Imprecise Uncertainty." In ASME 2006 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/detc2006-99237.

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Since engineering design requires decision making under uncertainty, the degree to which good decisions can be made depends upon the degree to which the decision maker has expressive and accurate representations of his or her uncertain beliefs. Whereas traditional decision analysis uses precise probability distributions to represent uncertain beliefs, recent research has examined the effects of relaxing this assumption of precision. A specific example of this is the theory of imprecise probability. Imprecise probabilities are more expressive than precise probabilities, but they are also more c

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Zheng, Liyu, Janis Terpenny, Peter Sandborn, and Raymond Nelson. "Design Refresh Planning Models for Managing Obsolescence." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70743.

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Fast moving technologies have caused high-tech components to have shortened life cycles, rendering them obsolete quickly. Obsolescence is a significant problem for systems with operational and support life that are much longer than the procurement lifetimes of their constituent components. Design refresh planning is a strategic way of managing obsolescence. Mathematical models are presented herein to determine the design refresh plan that minimizes total cost. The plan includes guidance on when to execute design refreshes (dates) and what obsolete/non-obsolete system components should be repla

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Sandquist, Gary M., and D. Shannon Sentell. "Assessing Aircraft Hazards to Nuclear Facilities." In 12th International Conference on Nuclear Engineering. ASMEDC, 2004. http://dx.doi.org/10.1115/icone12-49384.

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The methodology and selected models used for assessing the frequency of aircraft crashes to critical surface facilities are examined. The DOE Standard model is the basis for comparing other models, particularly those used to assess risk to DOE facilities. The NRC methodology is relevant for nuclear power plants. A rigorous physical model that describes the Markov chain of events and their related probabilities that lead to aircraft hazards to ground facilities is developed. The chain of events is then quantified to provide a basis for comparison and evaluation of mathematical models. It is evi

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Kupciuniene, Kristina, and Robertas Alzbutas. "External Events Importance for Safety of the Ignalina Nuclear Power Plant." In 16th International Conference on Nuclear Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/icone16-48230.

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Probabilistic risk analysis of external events impact on the safety important systems of Ignalina nuclear power plant (NPP) is performed. At first, the methodology was established for screening out external events, which impact on Ignalina NPP safety is not significant. In order to estimate probabilities of external events occurrences the statistical data were collected, mathematical models were constructed and probabilities of these events occurrences were determined. For risk estimation, the following external events were studied: forest fires, external floods, aircraft crash, seismic events

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Salanova Grau, Josep Maria, and Miquel Estrada Romeu. "Social optimal shifts and fares of taxi services." In CIT2016. Congreso de Ingeniería del Transporte. Valencia: Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.3254.

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This paper presents a mathematical model for supporting the decision and policy making related to the optimal determination of shifts and fares of taxi services in a major city. The model is based on the system’s generalized cost function and uses continuous approximations and geometric probabilities for estimating the key performance indicators of the taxi market, which are waiting and access time for the customers (in-vehicle travel time does not depend on the offer side) and benefits for the drivers. The model is based on an econometric model with the inclusion of an elastic demand, which a

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Wang, Qian, and Jun Ji. "Reliability Analysis of Underground Structures Using Metamodels and FORM." In IABSE Congress, New York, New York 2019: The Evolving Metropolis. Zurich, Switzerland: International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/newyork.2019.1163.

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<p>An engineering reliability analysis method of underground structures using metamodels and a first-order reliability method (FORM) was studied. Surrogate models, or metamodels are approximate models that can be constructed to replace implicit response functions that involve finite element analyses. The radial basis functions (RBFs) are suitable for creating metamodels for general linear or nonlinear responses and they are locally and globally adaptive. After a performance function was replaced by an augmented RBF metamodel, an alternative FORM was applied. The method was tested using m

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Kupciuniene, Kristina, and Robertas Alzbutas. "Updated Probabilistic Analysis of External Events Data and Safety of the Nuclear Power Plant in Lithuania." In 17th International Conference on Nuclear Engineering. ASMEDC, 2009. http://dx.doi.org/10.1115/icone17-75736.

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The main purpose of performed work is the probabilistic analysis of extreme external events, which have a potential influence on safety of the present nuclear power plant (NPP) in Lithuania. This analysis can also be related to the future NPP in Lithuania at the same site. At first, the methodology was established for screening out hazardous events, which impact on the present Ignalina NPP safety is not significant. For risk estimation, the following external events were considered in detail: forest fire, external flood, airplane crash, extreme wind. In order to estimate probabilities of hazar

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Loboda, Igor, and Sergey Yepifanov. "A Mixed Data-Driven and Model Based Fault Classification for Gas Turbine Diagnosis." In ASME Turbo Expo 2010: Power for Land, Sea, and Air. ASMEDC, 2010. http://dx.doi.org/10.1115/gt2010-23075.

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In modern gas turbine health monitoring systems, the diagnostic algorithms based on gas path analysis may be considered as principal. They analyze gas path measured variables and are capable of identifying different faults and degradation mechanisms of gas turbine components (e.g. compressor, turbine, and combustor) as well as malfunctions of the measurement system itself. Gas path mathematical models are widely used in building fault classification required for diagnostics because faults rarely occur during field operation. In that case, model errors are transmitted to the model-based classif

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Doraiswamy, Srikanth, and Sundar Krishnamurty. "Bayesian Analysis in Engineering Model Assessment." In ASME 2000 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/detc2000/dtm-14546.

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Abstract Engineering design decisions often need to be made when complete knowledge of the system is not available. Getting such complete deterministic information may be impossible or impractical as the resources required to get the information may be unaffordable. The challenge then is to identify and construct an information-gathering strategy, one that can be expected to yield most reliable results in an efficient manner during design. In this context, an engineering model can be viewed as an information-gathering strategy, using which predictive information regarding the performance of a

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