Littérature scientifique sur le sujet « Probabilistic analysi »
Créez une référence correcte selon les styles APA, MLA, Chicago, Harvard et plusieurs autres
Consultez les listes thématiques d’articles de revues, de livres, de thèses, de rapports de conférences et d’autres sources académiques sur le sujet « Probabilistic analysi ».
À côté de chaque source dans la liste de références il y a un bouton « Ajouter à la bibliographie ». Cliquez sur ce bouton, et nous générerons automatiquement la référence bibliographique pour la source choisie selon votre style de citation préféré : APA, MLA, Harvard, Vancouver, Chicago, etc.
Vous pouvez aussi télécharger le texte intégral de la publication scolaire au format pdf et consulter son résumé en ligne lorsque ces informations sont inclues dans les métadonnées.
Articles de revues sur le sujet "Probabilistic analysi"
De la Sen, M. « On Probabilistic Alpha-Fuzzy Fixed Points and Related Convergence Results in Probabilistic Metric and Menger Spaces under Some Pompeiu-Hausdorff-Like Probabilistic Contractive Conditions ». Journal of Function Spaces 2015 (2015) : 1–12. http://dx.doi.org/10.1155/2015/213174.
Texte intégralRiveros, Bruno, Mariana Rosim, Gabriel Pedro, Rosa Lucchetta et Marcelo Nita. « Análise de custo-efetividade e a análise de sensibilidade, um roteiro para execução de uma abordagem probabilística : Introdução à análise de sensibilidade probabilística (Parte I) ». Jornal de Assistência Farmacêutica e Farmacoeconomia 1, no 2 (décembre 2016) : 33–38. http://dx.doi.org/10.22563/2525-7323.2016.v1.n2.p.33-38.
Texte intégralPavese, Carlotta. « Probabilistic Knowledge in Action ». Analysis 80, no 2 (1 avril 2020) : 342–56. http://dx.doi.org/10.1093/analys/anz094.
Texte intégralIrzik, G. « Armstrong's account of probabilistic laws ». Analysis 51, no 4 (1 octobre 1991) : 214–17. http://dx.doi.org/10.1093/analys/51.4.214.
Texte intégralFitelson, B. « A probabilistic theory of coherence ». Analysis 63, no 3 (1 juillet 2003) : 194–99. http://dx.doi.org/10.1093/analys/63.3.194.
Texte intégralTsujimoto, Kazuki, et Toshiaki Omori. « Switching Probabilistic Slow Feature Analysis for Time Series Data ». International Journal of Machine Learning and Computing 10, no 6 (décembre 2020) : 740–45. http://dx.doi.org/10.18178/ijmlc.2020.10.6.999.
Texte intégralChase, J. « The non-probabilistic two envelope paradox ». Analysis 62, no 2 (1 avril 2002) : 157–60. http://dx.doi.org/10.1093/analys/62.2.157.
Texte intégralFlandoli, Franco, et Marco Romito. « Probabilistic analysis of singularities for the 3D Navier-Stokes equations ». Mathematica Bohemica 127, no 2 (2002) : 211–18. http://dx.doi.org/10.21136/mb.2002.134166.
Texte intégralLIU, Jinlin, et Changhong PENG. « ICONE23-1839 AN OVERVIEW-PROBABILISTIC SAFETY ANALYSIS FOR RESEARCH REACTORS ». Proceedings of the International Conference on Nuclear Engineering (ICONE) 2015.23 (2015) : _ICONE23–1—_ICONE23–1. http://dx.doi.org/10.1299/jsmeicone.2015.23._icone23-1_397.
Texte intégralFriederichs, Petra, Martin Göber, Sabrina Bentzien, Anne Lenz et Rebekka Krampitz. « A probabilistic analysis of wind gusts using extreme value statistics ». Meteorologische Zeitschrift 18, no 6 (1 décembre 2009) : 615–29. http://dx.doi.org/10.1127/0941-2948/2009/0413.
Texte intégralThèses sur le sujet "Probabilistic analysi"
POZZI, FEDERICO ALBERTO. « Probabilistic Relational Models for Sentiment Analysis in Social Networks ». Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/65709.
Texte intégralCrotta, M. « PROBABILISTIC MODELLING IN FOOD SAFETY : A SCIENCE-BASED APPROACH FOR POLICY DECISIONS ». Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/339138.
Texte intégralSCOZZESE, FABRIZIO. « AN EFFICIENT PROBABILISTIC FRAMEWORK FOR SEISMIC RISK ANALYSIS OF STRUCTURAL SYSTEMS EQUIPPED WITH LINEAR AND NONLINEAR VISCOUS DAMPERS ». Doctoral thesis, Università degli Studi di Camerino, 2018. http://hdl.handle.net/11581/429547.
Texte intégralTagliaferri, Lorenza. « Probabilistic Envelope Curves for Extreme Rainfall Events - Curve Inviluppo Probabilistiche per Precipitazioni Estreme ». Master's thesis, Alma Mater Studiorum - Università di Bologna, 2008. http://amslaurea.unibo.it/99/.
Texte intégralSaad, Feras Ahmad Khaled. « Probabilistic data analysis with probabilistic programming ». Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/113164.
Texte intégralThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (pages 48-50).
Probabilistic techniques are central to data analysis, but dierent approaches can be challenging to apply, combine, and compare. This thesis introduces composable generative population models (CGPMs), a computational abstraction that extends directed graphical models and can be used to describe and compose a broad class of probabilistic data analysis techniques. Examples include hierarchical Bayesian models, multivariate kernel methods, discriminative machine learning, clustering algorithms, dimensionality reduction, and arbitrary probabilistic programs. We also demonstrate the integration of CGPMs into BayesDB, a probabilistic programming platform that can express data analysis tasks using a modeling language and a structured query language. The practical value is illustrated in two ways. First, CGPMs are used in an analysis that identifies satellite data records which probably violate Kepler's Third Law, by composing causal probabilistic programs with non-parametric Bayes in under 50 lines of probabilistic code. Second, for several representative data analysis tasks, we report on lines of code and accuracy measurements of various CGPMs, plus comparisons with standard baseline solutions from Python and MATLAB libraries.
by Feras Ahmad Khaled Saad.
M. Eng.
Shirmohammadi, Mahsa. « Qualitative analysis of synchronizing probabilistic systems ». Thesis, Cachan, Ecole normale supérieure, 2014. http://www.theses.fr/2014DENS0054/document.
Texte intégralMarkov decision processes (MDPs) are finite-state probabilistic systems with bothstrategic and random choices, hence well-established to model the interactions between a controller and its randomly responding environment.An MDP can be mathematically viewed as a one and half player stochastic game played in rounds when the controller chooses an action,and the environment chooses a successor according to a fixedprobability distribution.There are two incomparable views on the behavior of an MDP, when thestrategic choices are fixed. In the traditional view, an MDP is a generator of sequence of states, called the state-outcome; the winning condition of the player is thus expressed as a set of desired sequences of states that are visited during the game, e.g. Borel condition such as reachability.The computational complexity of related decision problems and memory requirement of winning strategies for the state-outcome conditions are well-studied.Recently, MDPs have been viewed as generators of sequences of probability distributions over states, calledthe distribution-outcome. We introduce synchronizing conditions defined on distribution-outcomes,which intuitively requires that the probability mass accumulates insome (group of) state(s), possibly in limit.A probability distribution is p-synchronizing if the probabilitymass is at least p in some state, anda sequence of probability distributions is always, eventually,weakly, or strongly p-synchronizing if respectively all, some, infinitely many, or all but finitely many distributions in the sequence are p-synchronizing.For each synchronizing mode, an MDP can be (i) sure winning if there is a strategy that produces a 1-synchronizing sequence; (ii) almost-sure winning if there is a strategy that produces a sequence that is, for all epsilon > 0, a (1-epsilon)-synchronizing sequence; (iii) limit-sure winning if for all epsilon > 0, there is a strategy that produces a (1-epsilon)-synchronizing sequence.We consider the problem of deciding whether an MDP is winning, for each synchronizing and winning mode: we establish matching upper and lower complexity bounds of the problems, as well as the memory requirementfor optimal winning strategies.As a further contribution, we study synchronization in probabilistic automata (PAs), that are kind of MDPs where controllers are restricted to use only word-strategies; i.e. no ability to observe the history of the system execution, but the number of choices made so far.The synchronizing languages of a PA is then the set of all synchronizing word-strategies: we establish the computational complexity of theemptiness and universality problems for all synchronizing languages in all winning modes.We carry over results for synchronizing problems from MDPs and PAs to two-player turn-based games and non-deterministic finite state automata. Along with the main results, we establish new complexity results foralternating finite automata over a one-letter alphabet.In addition, we study different variants of synchronization for timed andweighted automata, as two instances of infinite-state systems
Baier, Christel, Benjamin Engel, Sascha Klüppelholz, Steffen Märcker, Hendrik Tews et Marcus Völp. « A Probabilistic Quantitative Analysis of Probabilistic-Write/Copy-Select ». Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2013. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-129917.
Texte intégralMunch, Mélanie. « Améliorer le raisonnement dans l'incertain en combinant les modèles relationnels probabilistes et la connaissance experte ». Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPASB011.
Texte intégralThis thesis focuses on integrating expert knowledge to enhance reasoning under uncertainty. Our goal is to guide the probabilistic relations’ learning with expert knowledge for domains described by ontologies.To do so we propose to couple knowledge bases (KBs) and an oriented-object extension of Bayesian networks, the probabilistic relational models (PRMs). Our aim is to complement the statistical learning with expert knowledge in order to learn a model as close as possible to the reality and analyze it quantitatively (with probabilistic relations) and qualitatively (with causal discovery). We developped three algorithms throught three distinct approaches, whose main differences lie in their automatisation and the integration (or not) of human expert supervision.The originality of our work is the combination of two broadly opposed philosophies: while the Bayesian approach favors the statistical analysis of the given data in order to reason with it, the ontological approach is based on the modelization of expert knowledge to represent a domain. Combining the strenght of the two allows to improve both the reasoning under uncertainty and the expert knowledge
Echard, Benjamin. « Assessment by kriging of the reliability of structures subjected to fatigue stress ». Thesis, Clermont-Ferrand 2, 2012. http://www.theses.fr/2012CLF22269/document.
Texte intégralTraditional procedures for designing structures against fatigue are grounded upon the use of so-called safety factors in an attempt to ensure structural integrity while masking the uncertainties inherent to fatigue. These engineering methods are simple to use and fortunately, they give satisfactory solutions with regard to safety. However, they do not provide the designer with the structure’s safety margin as well as the influence of each design parameter on reliability. Probabilistic approaches are considered in this thesis in order to acquire this information, which is essential for an optimal design against fatigue. A general approach for probabilistic analysis in fatigue is proposed in this manuscript. It relies on the modelling of the uncertainties (load, material properties, geometry, and fatigue curve), and aims at assessing the reliability level of the studied structure in the case of a fatigue failure scenario. Classical reliability methods require a large number of calls to the mechanical model of the structure and are thus not applicable when the model evaluation is time-demanding. A family of methods named AK-RM (Active learning and Kriging-based Reliability methods) is proposed in this research work in order to solve the reliability problem with a minimum number of mechanical model evaluations. The general approach is applied to two case studies submitted by SNECMA in the frame of the ANR project APPRoFi
Kassa, Negede Abate. « Probabilistic safety analysis of dams ». Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2010. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-60843.
Texte intégralLivres sur le sujet "Probabilistic analysi"
Hynes, Mary Ellen. Probabilistic liquefaction analysis. Washington, DC : Division of Engineering Technology, Office of Nuclear Regulatory Research, U.S. Nuclear Regulatory Commission, 1999.
Trouver le texte intégralHynes, M. E. Probabilistic liquefaction analysis. Washington, D.C : U.S. Nuclear Regulatory Commission, 1990.
Trouver le texte intégralHofri, Micha. Probabilistic Analysis of Algorithms. New York, NY : Springer New York, 1987. http://dx.doi.org/10.1007/978-1-4612-4800-2.
Texte intégralProbabilistic techniques in analysis. New York : Springer-Verlag, 1995.
Trouver le texte intégralNational Research Council (U.S.). Panel on Seismic Hazard Analysis. Probabilistic seismic hazard analysis. Washington, D.C : National Academy Press, 1988.
Trouver le texte intégralAlon, Noga. The probabilistic method. 3e éd. New York, NY : John Wiley, 2008.
Trouver le texte intégralAlon, Noga. The probabilistic method. New York : Wiley, 1992.
Trouver le texte intégralH, Spencer Joel, dir. The probabilistic method. Hoboken, New Jersey : John Wiley & Sons, Inc., 2016.
Trouver le texte intégralAlon, Noga. The Probabilistic Method. New York : John Wiley & Sons, Ltd., 2005.
Trouver le texte intégralAlon, Noga. The probabilistic method. 3e éd. New York, NY : John Wiley, 2008.
Trouver le texte intégralChapitres de livres sur le sujet "Probabilistic analysi"
Reidys, Christian. « Probabilistic Analysis ». Dans Combinatorial Computational Biology of RNA, 143–86. New York, NY : Springer New York, 2010. http://dx.doi.org/10.1007/978-0-387-76731-4_5.
Texte intégralSnapp, Robert R. « Probabilistic Analysis ». Dans Encyclopedia of Social Network Analysis and Mining, 1–28. New York, NY : Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4614-7163-9_155-1.
Texte intégralMaxim, Dorin, Liliana Cucu-Grosjean et Robert I. Davis. « Probabilistic Analysis ». Dans Handbook of Real-Time Computing, 1–23. Singapore : Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-4585-87-3_9-1.
Texte intégralSnapp, Robert R. « Probabilistic Analysis ». Dans Encyclopedia of Social Network Analysis and Mining, 1362–88. New York, NY : Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4614-6170-8_155.
Texte intégralMaxim, Dorin, Liliana Cucu-Grosjean et Robert I. Davis. « Probabilistic Analysis ». Dans Handbook of Real-Time Computing, 323–46. Singapore : Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-287-251-7_9.
Texte intégralBürgisser, Peter, et Felipe Cucker. « Probabilistic Analysis ». Dans Grundlehren der mathematischen Wissenschaften, 21–58. Berlin, Heidelberg : Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38896-5_2.
Texte intégralSnapp, Robert R. « Probabilistic Analysis ». Dans Encyclopedia of Social Network Analysis and Mining, 1866–92. New York, NY : Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7131-2_155.
Texte intégralKingston, John, Robert Nertney, Rudolf Frei, Philippe Schallier et Floor Koornneef. « Barrier Analysis Analysed in MORT Perspective ». Dans Probabilistic Safety Assessment and Management, 364–69. London : Springer London, 2004. http://dx.doi.org/10.1007/978-0-85729-410-4_59.
Texte intégralHuang, Xiaoxia. « Probabilistic Portfolio Selection ». Dans Portfolio Analysis, 11–60. Berlin, Heidelberg : Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-11214-0_2.
Texte intégralLarsen, Rasmus, et Klaus Baggesen Hilger. « Probabilistic Generative Modelling ». Dans Image Analysis, 861–68. Berlin, Heidelberg : Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/3-540-45103-x_114.
Texte intégralActes de conférences sur le sujet "Probabilistic analysi"
Ramanath, Vinay, et Gene E. Wiggs. « DACE Based Probabilistic Optimization of Mechanical Components ». Dans ASME Turbo Expo 2006 : Power for Land, Sea, and Air. ASMEDC, 2006. http://dx.doi.org/10.1115/gt2006-91024.
Texte intégralParajuli, H. Ram, J. Kiyono, H. Taniguchi, K. Toki et P. Nath Maskey. « Probabilistic seismic hazard assessment for Nepal ». Dans RISK ANALYSIS 2010. Southampton, UK : WIT Press, 2010. http://dx.doi.org/10.2495/risk100351.
Texte intégralCarvalho, E., J. Cruz, P. Barahona, Theodore E. Simos, George Psihoyios et Ch Tsitouras. « Probabilistic Reasoning with Continuous Constraints ». Dans Numerical Analysis and Applied Mathematics. AIP, 2007. http://dx.doi.org/10.1063/1.2790083.
Texte intégralSallaberry, Cédric J., Robert E. Kurth, Frederick W. Brust et Elizabeth A. Kurth. « Proposed Approach of Scenario Analysis Using a Probabilistic Code ». Dans ASME 2017 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/pvp2017-65989.
Texte intégralChang, Kuang-Hua, Xiaoming Yu et Kyung Choi. « Probabilistic structural stability prediction ». Dans 6th Symposium on Multidisciplinary Analysis and Optimization. Reston, Virigina : American Institute of Aeronautics and Astronautics, 1996. http://dx.doi.org/10.2514/6.1996-4064.
Texte intégralShin, Youngwon. « Improving Probabilistic Damage Tolerance Analysis for Inspection Optimization : Possibilistic-Probabilistic Approach ». Dans 12th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference. Reston, Virigina : American Institute of Aeronautics and Astronautics, 2008. http://dx.doi.org/10.2514/6.2008-6050.
Texte intégralWang, C., W. Gao et S. Tangaramvong. « Hybrid Probabilistic and Non-Probabilistic Analysis of Structures with Mixed Uncertainties ». Dans Second International Conference on Vulnerability and Risk Analysis and Management (ICVRAM) and the Sixth International Symposium on Uncertainty, Modeling, and Analysis (ISUMA). Reston, VA : American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413609.220.
Texte intégralTavakoli, Yashar, H. Haj Seyyed Javadi et Hossein Erfani. « A Probabilistic Analysis for Greedy Paths ». Dans NUMERICAL ANALYSIS AND APPLIED MATHEMATICS : International Conference on Numerical Analysis and Applied Mathematics 2008. American Institute of Physics, 2008. http://dx.doi.org/10.1063/1.2990983.
Texte intégralAfshin Abdollahi. « Probabilistic decision diagrams for exact probabilistic analysis ». Dans 2007 IEEE/ACM International Conference on Computer-Aided Design. IEEE, 2007. http://dx.doi.org/10.1109/iccad.2007.4397276.
Texte intégralBhimanadam, V. R., et F. J. Blom. « Probabilistic PTS Analysis ». Dans ASME 2016 Pressure Vessels and Piping Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/pvp2016-63112.
Texte intégralRapports d'organisations sur le sujet "Probabilistic analysi"
Benson, William E., Jr Berg et Joseph W. Probabilistic Seismic Hazard Analysis. Fort Belvoir, VA : Defense Technical Information Center, janvier 1988. http://dx.doi.org/10.21236/ada203074.
Texte intégralCohen, Paul R. Probabilistic, Dynamic Analysis of Plans. Fort Belvoir, VA : Defense Technical Information Center, mars 2004. http://dx.doi.org/10.21236/ada422223.
Texte intégralDarwiche, Adnan. Probabilistic Sensitivity Analysis for Situation Awareness. Fort Belvoir, VA : Defense Technical Information Center, juin 2008. http://dx.doi.org/10.21236/ada484629.
Texte intégralHansen, Jeffery. Probabilistic Analysis of Time Sensitive Systems. Fort Belvoir, VA : Defense Technical Information Center, octobre 2014. http://dx.doi.org/10.21236/ada610981.
Texte intégralBlakely, Scott. Probabilistic Analysis for Reliable Logic Circuits. Portland State University Library, janvier 2000. http://dx.doi.org/10.15760/etd.1859.
Texte intégralCheverton, R. D., et T. L. Dickson. HFIR vessel probabilistic fracture mechanics analysis. Office of Scientific and Technical Information (OSTI), janvier 1997. http://dx.doi.org/10.2172/654200.
Texte intégralZio, Enrico, et Nicola Pedroni. Uncertainty characterization in risk analysis for decision-making practice. Fondation pour une culture de sécurité industrielle, mai 2012. http://dx.doi.org/10.57071/155chr.
Texte intégralFranco, John. Probabilistic Analysis of Algorithms for NP-Complete Problems. Fort Belvoir, VA : Defense Technical Information Center, octobre 1986. http://dx.doi.org/10.21236/ada179537.
Texte intégralBlumenthal, Saul, et Prem Goel. Fatigue Crack Propagation : Probabilistic Modeling and Statistical Analysis. Fort Belvoir, VA : Defense Technical Information Center, mars 1988. http://dx.doi.org/10.21236/ada195885.
Texte intégralSeitz, R. PROBABILISTIC SENSITIVITY AND UNCERTAINTY ANALYSIS WORKSHOP SUMMARY REPORT. Office of Scientific and Technical Information (OSTI), juin 2008. http://dx.doi.org/10.2172/933167.
Texte intégral