Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 193 for “"Probabilistic model"”.
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A probabilistic model of corporate acquisitions
Thesis (Ph. D.)--Massachusetts Institute of Technology, Sloan School of Management, 1983.
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Probabilistic Model-Based Approach to Evolutionary Analysis of Non-Coding Sequences
… analyze non-coding sequences, which are based on probabilistic models of sequence evolution. We present a probabilistic framework for finding the locations of insertions and deletions (indels) in a multiple alignment. Its performance is found to be better than that obtained by a parsimony-based …
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The Bayesian validation metric : a framework for probabilistic model calibration and validation
In model development, model calibration and validation play complementary roles toward learning reliable models. In this thesis, we propose and develop the "Bayesian Validation Metric" (BVM) as a general model validation and testing tool. We show that the BVM can represent all the standard …
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An evolutionary programming approach to probabilistic model-based fault diagnosis of chemical processes
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 1995.
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A probabilistic model of the effects of satellite system automation on cost and availability
Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 1997.
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A probabilistic model for estimating demand for selected existing rural community hospitals that may be facing closure in West Virginia
… will be admitted to a particular hospital using models that incorporate location and size of competing hospitals. In this paper, the focus of econometric investigation and prediction is the probability that a patient will select e particular hospital. Four different service areas were delineated …
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A Probabilistic Model of A Floodplain Forest: Prediction of Changes in Species Distribution Due to Variable Backwater Conditions During Reservoir Operation
Made available in DSpace on 2014-12-11T18:28:20Z (GMT). No. of bitstreams: 1 7212167.pdf: 3594898 bytes, checksum: 7d6e66efb037fba52a90b52b0293829e (MD5) Previous issue date: 1971
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Implementation of symbolic model checking for probabilistic systems
… present efficient implementation techniques for probabilistic model checking, a method which can be used to analyse probabilistic systems such as randomised distributed algorithms, fault-tolerant processes and communication networks. A probabilistic model checker inputs a probabilistic model and …
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Wind shielding in refining and petrochemical facilities
… these unique facilities. This paper proposes a probabilistic model to predict the magnitude of shielding that is provided by the vast network of pipe rack structures that encircle these densely arranged facilities. The probabilistic model is built from data obtained through a broad sampling of …
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New model-based methods for non-differentiable optimization
Model-based optimization methods are effective for solving optimization problems with little structure, such as convexity and differentiability. Such algorithms iteratively find candidate solutions by generating samples from a parameterized probabilistic model on the solution space, and update the …
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Essays on Semiparametric Bayesian Regression
… provides a nonparametric method to construct the probabilistic model, the likelihood, so it provide a simple but powerful strategy for semiparametric Bayesian methods.
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Venture : an extensible platform for probabilistic meta-programming
… describes Venture, an extensible platform for probabilistic meta-programming. In Venture, probabilistic generative models, probability density functions, and probabilistic inference algorithms are all first-class objects. Any Venture program that makes random choices can be treated as a …
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Toward Concept-Based Text Understanding and Mining
… identification, we also extend the generative probabilistic model to address a significant application that are related to concept-based text understanding and mining---semantic integration between text and databases, based on entity identification and tracking.
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Next generation probabilistic prediction model for submarine propulsion shaft life
… that uncertainty by developing a more robust probabilistic model for submarine propulsion shaft reliability in order to more accurately predict probabilities of failure. To improve upon previous efforts, all the components and failure modes of the propulsion shaft were first identified. While …
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Visibility-Based Pursuit-Evasion with Probabilistic Evader Models
… in which a single pursuer has access to a probabilistic model describing how the evaders are likely to move in the environment. The application of our algorithm can be best viewed in the context of search and rescue. Although the victims (evaders) are not actively trying to escape from the …
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Probabilistic information retrieval in a distributed heterogeneous environment
This thesis describes a probabilistic model for optimum information retrieval in a distributed heterogeneous environment. The model assumes the collection of documents offered by the environment to be hierarchically partitioned into subcollections. Documents as well as subcollections have to be …
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A production simulation tool for systems with integrated photovoltaic energy sources.
… on power systems. The tool consists of a probabilistic model for the representation of the power output of the PV resources, at single or multiple sites on the network, and the incorporation of the model into an extended probabilistic simulation framework for the evaluation of the …
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Um modelo matemático para simulação e otimização do controle da qualidade da água em sistemas fluviais
… techniques such as simulation with mathematical models and optimization techniques added to a hydrologic probabilistic model, in the planning of the use of water resources to control water quality. The methodology is applied to Paraíba do Sul river basin in the state of São Paulo.
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Effective and efficient estimation of distribution algorithms for permutation and scheduling problems.
… branch of evolutionary computation that learn a probabilistic model of good solutions. Probabilistic models are used to represent relationships between solution variables which may give useful, human-understandable insights into real-world problems. Also, developing an effective PM has been shown …
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