Дисертації з теми "Partitions de Markov"
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Kenny, Robert. "Orbit complexity and computable Markov partitions." University of Western Australia. School of Mathematics and Statistics, 2008. http://theses.library.uwa.edu.au/adt-WU2008.0231.
Praggastis, Brenda L. "Markov partitions for hyperbolic toral automorphisms /." Thesis, Connect to this title online; UW restricted, 1992. http://hdl.handle.net/1773/5773.
Jeandenans, Emmanuelle. "Difféomorphismes hyperboliques des surfaces et combinatoires des partitions de Markov." Dijon, 1996. http://www.theses.fr/1996DIJOS032.
Cruz, Diaz Inti. "An Algorithmic Classification of Generalized Pseudo-Anosov Homeomorphisms via Geometric Markov Partitions." Electronic Thesis or Diss., Bourgogne Franche-Comté, 2023. http://www.theses.fr/2023UBFCK083.
This thesis aims to provide a classification of generalized pseudo-Anosov homeomorphisms up to topological conjugacy using an algorithmic approach. This entails obtaining finite and computable invariants for each conjugacy class.A Markov partition of a generalized pseudo-Anosov homeomorphism is a decomposition of the surface into a finite number of rectangles with disjoint interiors and such that their images intersect with any other rectangle in the Markov partition along a finite number of horizontal sub-rectangles. Every generalized pseudo-Anosov homeomorphism has a Markov partition, and, using the surface's orientation, we can endow any Markov partition with a geometrization. This process involves labeling the rectangles and choosing an orientation on the stable and unstable leaves of each of these rectangles.The geometric type of a geometric Markov partition was defined by Bonatti and Langevin in their book, "Difféomorphismes de Smale des surfaces," to classify saddle-type basic pieces for structurally stable diffeomorphisms on surfaces. A geometric type is an abstract combinatorial object that generalizes the incidence matrix of a Markov partition. It takes into account not only the number of times the image of a rectangle intersects with any other rectangle in the family but also the order and change of orientation induced by the homeomorphisms.This thesis employs the geometric type of a geometric Markov partition to classify the conjugacy classes of pseudo-Anosov homeomorphisms. Our main results can be summarized as follows:The geometric type is a complete invariant of conjugation: A pair of generalized pseudo-Anosov homeomorphisms is topologically conjugate to each other through an orientation-preserving homeomorphism if and only if they have geometric Markov partitions with the same geometric type.The realization: Geometric types are defined broadly, and not every abstract geometric type corresponds to a pseudo-Anosov homeomorphism. A geometric type T is considered part of the pseudo-Anosov class if there exists a generalized pseudo-Anosov homeomorphism with a geometric Markov partition of geometric type T. Our second result provides a computable and combinatorial criterion for determining whether an abstract geometric type belongs to the pseudo-Anosov class.Equivalent representations: Every generalized pseudo-Anosov homeomorphism has an infinite number of geometric Markov partitions with different geometric types. Our third result is an algorithm for determining whether two geometric types in the pseudo-Anosov class are realized by generalized pseudo-Anosov homeomorphisms that are topologically conjugated or not
Wong, Chi-hung, and 黃志雄. "Hand-written Chinese character recognition by hidden Markov models andradical partition." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1998. http://hub.hku.hk/bib/B31220058.
Wingate, David. "Solving Large MDPs Quickly with Partitioned Value Iteration." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd437.pdf.
Wong, Chi-hung. "Hand-written Chinese character recognition by hidden Markov models and radical partition /." Hong Kong : University of Hong Kong, 1998. http://sunzi.lib.hku.hk/hkuto/record.jsp?B19669380.
Smith, Adam Nicholas. "Bayesian Analysis of Partitioned Demand Models." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1497895561381294.
Hadriche, Abir. "Caractérisation du répertoire dynamique macroscopique de l'activité électrique cérébrale humaine au repos." Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4724/document.
We propose an algorithme based on set oriented approach of dynamical system to extract a coarse grained organization of brain state space on the basis of EEG signals. We use it for comparing the organization of the state space of large scale simulation of brain dynamics with actual brain dynamics of resting activity in healthy and SEP subjects
Joder, Cyril. "Alignement temporel musique-sur-partition par modèles graphiques discriminatifs." Phd thesis, Télécom ParisTech, 2011. http://pastel.archives-ouvertes.fr/pastel-00664260.
Baptista, Diogo Pedro Ferreira Nascimento. "Iteradas de aplicações do plano no plano." Doctoral thesis, Universidade de Évora, 2008. http://hdl.handle.net/10174/12257.
Sörensen, Kristina. "Clustering in Financial Markets : A Network Theory Approach." Thesis, KTH, Optimeringslära och systemteori, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-150577.
I denna uppsats studeras graf partition av en typ av komplexa nätverk som kallas power law grafer. Specifikt fokuserar vi på marknadengrafen, konstruerad av tidsserier av aktiepriser på den amerikanska aktiemarknaden. Två olika metoder, initialt utvecklade för klusteranalys i sociala nätverk samt för bildanalys appliceras för att få graf-partitioner och resultaten utvärderas utifrån strukturen och kvaliten på partitionen. Utöver marknadsgrafen studeras aven power law grafer från tre olika teoretiska grafmodeller. Denna studie belyser topologiska egenskaper vanligt förekommande i många power law grafer samt modellerns olikheter och begränsningar. Våra resultat visar att marknadsgrafen endast uppvisar en tydlig klustrad struktur för högre korrelation-trösklar. Genom att studera den interna strukturen hos varje kluster fann vi att kluster kan vara ett alternativ till traditionell marknadsindelning med industriella sektorer. Slutligen studerades partitioner för olika tidsserier för att undersöka dynamiken och stabiliteten i partitionsstrukturen. Trots att resultaten från denna del inte var entydiga tror vi att detta kan vara ett intressant spår för framtida studier.
Ocakli, Mehmet. "A Video Tracker System For Traffic Monitoring And Analysis." Master's thesis, METU, 2007. http://etd.lib.metu.edu.tr/upload/2/12608712/index.pdf.
s field of view. This provides to perform traffic analysis about the scene, which can be used to optimize traffic flows and identify potential accidents. The scene inspected in this study is assumed stationary to achieve high performance solution to the problem. This assumption provides to detect moving objects more accurately, as well as ability of collecting a-priori information about the scene. A new algorithm is proposed to solve the multi-vehicle tracking problem that can deal with problems such as occlusion, short period object lost or inaccurate object detection. Two different tracking methods are used together in the developed tracking system, namely, the multi-model Kalman tracker and the Markov scene partition tracker. By the combination of these vehicle trackers with the developed occlusion reasoning approach, the continuity of the track is achieved for situations such as target loss and occlusion. The developed system is a system that collects a-priori information about the junction and then used it for scene modeling in order to increase the performance of the tracking system. The proposed system is implemented on real-world image sequences. The simulation results demonstrates that, the proposed multi-vehicle tracking system is capable of tracking a target in a complex environment and able to overcome occlusion and inaccurate detection problems as well as abrupt changes in its trajectory.
Cuvillier, Philippe. "On temporal coherency of probabilistic models for audio-to-score alignment." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066532/document.
This thesis deals with automatic alignment of audio recordings with corresponding music scores. We study algorithmic solutions for this problem in the framework of probabilistic models which represent hidden evolution on the music score as stochastic process. We begin this work by investigating theoretical foundations of the design of such models. To do so, we undertake an axiomatic approach which is based on an application peculiarity: music scores provide nominal duration for each event, which is a hint for the actual and unknown duration. Thus, modeling this specific temporal structure through stochastic processes is our main problematic. We define temporal coherency as compliance with such prior information and refine this abstract notion by stating two criteria of coherency. Focusing on hidden semi-Markov models, we demonstrate that coherency is guaranteed by specific mathematical conditions on the probabilistic design and that fulfilling these prescriptions significantly improves precision of alignment algorithms. Such conditions are derived by combining two fields of mathematics, Lévy processes and total positivity of order 2. This is why the second part of this work is a theoretical investigation which extends existing results in the related literature
Cuvillier, Philippe. "On temporal coherency of probabilistic models for audio-to-score alignment." Electronic Thesis or Diss., Paris 6, 2016. http://www.theses.fr/2016PA066532.
This thesis deals with automatic alignment of audio recordings with corresponding music scores. We study algorithmic solutions for this problem in the framework of probabilistic models which represent hidden evolution on the music score as stochastic process. We begin this work by investigating theoretical foundations of the design of such models. To do so, we undertake an axiomatic approach which is based on an application peculiarity: music scores provide nominal duration for each event, which is a hint for the actual and unknown duration. Thus, modeling this specific temporal structure through stochastic processes is our main problematic. We define temporal coherency as compliance with such prior information and refine this abstract notion by stating two criteria of coherency. Focusing on hidden semi-Markov models, we demonstrate that coherency is guaranteed by specific mathematical conditions on the probabilistic design and that fulfilling these prescriptions significantly improves precision of alignment algorithms. Such conditions are derived by combining two fields of mathematics, Lévy processes and total positivity of order 2. This is why the second part of this work is a theoretical investigation which extends existing results in the related literature
Viricel, Clement. "Contributions au développement d'outils computationnels de design de protéine : méthodes et algorithmes de comptage avec garantie." Thesis, Toulouse, INSA, 2017. http://www.theses.fr/2017ISAT0019/document.
This thesis is focused on two intrinsically related subjects : the computation of the normalizing constant of a Markov random field and the estimation of the binding affinity of protein-protein interactions. First, to tackle this #P-complete counting problem, we developed Z*, based on the pruning of negligible potential quantities. It has been shown to be more efficient than various state-of-the-art methods on instances derived from protein-protein interaction models. Then, we developed #HBFS, an anytime guaranteed counting algorithm which proved to be even better than its predecessor. Finally, we developed BTDZ, an exact algorithm based on tree decomposition. BTDZ has already proven its efficiency on intances from coiled coil protein interactions. These algorithms all rely on methods stemming from graphical models : local consistencies, variable elimination and tree decomposition. With the help of existing optimization algorithms, Z* and Rosetta energy functions, we developed a package that estimates the binding affinity of a set of mutants in a protein-protein interaction. We statistically analyzed our esti- mation on a database of binding affinities and confronted it with state-of-the-art methods. It appears that our software is qualitatively better than these methods
Vincent, Thomas. "Modèles hémodynamiques spatiaux adaptatifs pour l'imagerie cérébrale fonctionnelle." Paris 11, 2010. http://www.theses.fr/2010PA112365.
The approaches developed in this PhD take place in the analysis of functional brain imaging seeking the characterization of brain structures specialization. The central modality was functional magnetic resonance imaging (fMRI) which provides an indirect, hemodynamic, measure of the neural activity. Data analysis methods are conventionally divided into: (i) a localization task of activations and (ii) an estimation task i. E. Characterizing the hemodynamic response function (HRF) linking the stimulations provided by the paradigm to the observed fMRI signal. This PhD addresses the tasks (i) and (ii) simultaneously in a joint detection-estimation model (JDE), respecting the obvious interdependence of these two processes. The JDE approach here has been extended to express a model of spatial correlation on the local response level associated with the HRF, enabling the approach to be multivariate for the detection as well as the estimation tasks. In the Bayesian framework, this modeling is achieved by the expression of a prior discrete Markov field involving a regularization factor. The unsupervised treatment regarding this parameter for the whole brain has been developed by adaptively taking into account the heterogeneity of the geometries of brain regions. The approach is validated on the cortical surface, but also in the volume through several group analyses with different acquisition conditions. These were used to assess the impact of the method in terms of significance of activation and its positioning relative to the traditional approach
Chen, Qian. "Bayesian Methods for Estimation, Inference and Forecasting of Flexible Models for Value-at-Risk and Tail Conditional Expectations." Thesis, The University of Sydney, 2011. http://hdl.handle.net/2123/7863.
Kéchichian, Razmig. "Structural priors for multiobject semi-automatic segmentation of three-dimensional medical images via clustering and graph cut algorithms." Phd thesis, INSA de Lyon, 2013. http://tel.archives-ouvertes.fr/tel-00967381.
Jiménez, Rojas Francisco. "Los grupos de empresa y la relación individual de trabajo en el marco de una economía productiva descentralizada." Doctoral thesis, Universidad de Murcia, 2012. http://hdl.handle.net/10803/87344.
The decentralized and flexible productive organization, boosted by globalization, new information and knowledge technologies, has been replacing the Fordist Keynesian inspiration since the last quarter of the 20th century; besides it has been worsening the labour markets, which involves a precariousness of employment conditions and an outstanding backing down of “welfare states” and job factor neutralization. Once the traditional principle of business uniqueness has been overwhelmed, a complex and multiple –the corporate group- employer arises; this employer is characterized by the difficulty of being identified and acquires an increasingly featuring role, inside a regulatory working context almost deregulated, where, on the fringe fraud, the unitarian corporate group management doesn’t imply deducing a solidarity liability from its activity. Inside that “particular economical unity” made up by the group, a deal-breaker or a gap is detected between the decision-making management faculties –decision unity- and the organizational ones –dependence and another person’s benefits-.
"Model-based clustering with network covariates by combining a modified product partition model with hidden Markov random field." Thesis, 2012. http://library.cuhk.edu.hk/record=b5549146.
為了測試本文提出的新方法的聚類性能,我們在兩個合成數據集上進行了模擬實驗。該實驗涵括多種類型的應變量,協變量網絡結構。結果顯示該方法在大部分實驗條件下都具有高正確聚類率。我們還將此返法應用於兩個真實數據集。第一個真實數據集利用學術期刊間相互引用的信息幫助對學術期刊的分門別類。第二個真實數據集合併酵母中基因的表達、轉錄因子結合位點和基因間的調控網絡信息,已對基因做詳細的功能分類。這兩個基於真實數據的實驗都給出諸多有意義的結果。
The product partition model was recently extended for the covariate-dependent random partition of subjects, where the covariates are limited to properties of individual subjects. For many clustering problems in biomedical or social studies, we often have extra clustering information from the pairwise association among subjects, such as the regulatory relationship between genes or the social network among people. Here we propose a model-based method for clustering with network information by combining a modified product partition model with hidden Markov random field. The Bayesian approach is used for statistical inference. Markov Chain Monte Carlo algorithms are used to compute the model. In order to improve the mixing of the chain, the Sequentially-Allocated Merge-Split Sampler is adapted to perform group moves as an eort to lower the chance of trapping in local modes.
The new method is tested on two synthesized data sets to evaluate its performance on different types of response variables, covariates and networks. The correct clustering rate is satisfactory under a wide range of conditions. We also applied this new method on two real data sets. The first real data set is the journal data, where the cross citation information among journals is used to groups journals to different categories. The second real data set involves the gene expression, motif binding and gene network of yeast, where the goal is to find detail gene functional groups. Both experiments yielded interesting results.
Detailed summary in vernacular field only.
Detailed summary in vernacular field only.
Fung, Ling Hiu.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2012.
Abstracts also in Chinese.
Abstract --- p.i
Acknowledgement --- p.iv
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Technical Background --- p.7
Chapter 2.1 --- Variable notation --- p.8
Chapter 2.2 --- Two exemplary models for the response variable --- p.10
Chapter 2.3 --- PPMx --- p.12
Chapter 2.3.1 --- PPM - definition and its equivalence to DPM --- p.12
Chapter 2.3.2 --- PPMx - extension with covariates --- p.15
Chapter 2.3.3 --- Posterior inference --- p.18
Chapter 2.4 --- HMRF --- p.19
Chapter 2.4.1 --- Definition --- p.19
Chapter 2.4.2 --- Constrained Dirichlet Process Mixture --- p.21
Chapter 3 --- Model-based Clustering with Network Covariates --- p.27
Chapter 3.1 --- Design of the model --- p.27
Chapter 3.2 --- The Bayesian MCNC model --- p.30
Chapter 3.3 --- MCMC computing --- p.31
Chapter 3.4 --- Performance evaluation criteria --- p.37
Chapter 4 --- Simulation study --- p.39
Chapter 4.1 --- Network --- p.39
Chapter 4.2 --- Covariates --- p.41
Chapter 4.3 --- The Phase model (M1) --- p.42
Chapter 4.4 --- The Normal model (M2) --- p.52
Chapter 4.5 --- Comparing correct clustering percentage and correct co-occurrence percentage --- p.62
Chapter 5 --- Real data --- p.68
Chapter 5.1 --- Journal cross-citation data --- p.68
Chapter 5.2 --- Gene Network of yeast data --- p.76
Chapter 6 --- Conclusions --- p.89
Chapter A --- p.91
Chapter A.1 --- Covariates --- p.91
Chapter A.1.1 --- Continuous covariates --- p.91
Chapter A.1.2 --- Categorical covariates --- p.94
Chapter A.1.3 --- Count covariates --- p.96
Chapter A.2 --- Phase model --- p.98
Chapter A.2.1 --- Prior specification --- p.99
Chapter A.2.2 --- Data generation --- p.99
Chapter A.2.3 --- Posterior estimation --- p.100
Chapter A.3 --- Normal model --- p.111
Chapter A.3.1 --- Prior specification --- p.111
Chapter A.3.2 --- Data generation --- p.112
Chapter A.3.3 --- Posterior estimation --- p.112
Chapter A.4 --- Journal dataset --- p.115
"Structural equation models with continuous and polytomous variables: comparisons on the bayesian and the two-stage partition approaches." 2003. http://library.cuhk.edu.hk/record=b5891707.
Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 33-34).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Bayesian Approach --- p.4
Chapter 2.1 --- Model Description --- p.5
Chapter 2.2 --- Identification --- p.6
Chapter 2.3 --- Bayesian Analysis of the Model --- p.8
Chapter 2.3.1 --- Posterior Analysis --- p.8
Chapter 2.3.2 --- The Gibbs Sampler --- p.9
Chapter 2.3.3 --- Conditional Distributions --- p.10
Chapter 2.4 --- Bayesian Estimation --- p.13
Chapter 3 --- Two-stage Partition Approach --- p.15
Chapter 3.1 --- First Stage: PRELIS --- p.15
Chapter 3.2 --- Second Stage: LISREL --- p.17
Chapter 3.2.1 --- Model Description --- p.17
Chapter 3.2.2 --- Identification --- p.17
Chapter 3.2.3 --- LISREL Analysis of the Model --- p.18
Chapter 4 --- Comparison --- p.19
Chapter 4.1 --- Simulation Studies --- p.19
Chapter 4.2 --- Real Data Studies --- p.28
Chapter 5 --- Conclusion & Discussion --- p.30
Chapter A --- Tables for the Two Approaches --- p.35
Chapter B --- Manifest variables in the ICPSR examples --- p.51
Chapter C --- PRELIS & LISREL Scripts for Simulation Studies --- p.52
WANG, YI NUO, and 王一諾. "Experiment on the influence of Fire resistance on market selling non-load-bearing metal stud partition walls to a standard fire." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/16425982163590593207.
國立臺灣科技大學
建築系
102
With the developing of society, architectural engineering is becoming larger, complicated and higher. Traditional labor-intensive constructions are replacing by new method of constructions, such as non-load-bearing metal stud Calcium silicate board wall. This wall has many advantages, such as unified construction method, less time to construct and so on. Both Cross-Strait and other countries have explicit standard for the method of fire resistance test for structural parts of building, however it doesn’t contain fire wall assembly with switchbox exposed to a standard fire. Some materials which are found in market sell does not have the same qualify with Lab materials. All these security risks are exist in daily life. This paper study literature,experiment with market selling materials. It also wants to investigate the influence of Fire resistance on market selling non-load-bearing metal stud Calcium silicate board wall assembly with switchbox exposed to a standard fire and the different between market sell materials and Lab materials by Literature study and Experimental study.
Desjardins, Guillaume. "Improving sampling, optimization and feature extraction in Boltzmann machines." Thèse, 2013. http://hdl.handle.net/1866/10550.
Despite the current widescale success of deep learning in training large scale hierarchical models through supervised learning, unsupervised learning promises to play a crucial role towards solving general Artificial Intelligence, where agents are expected to learn with little to no supervision. The work presented in this thesis tackles the problem of unsupervised feature learning and density estimation, using a model family at the heart of the deep learning phenomenon: the Boltzmann Machine (BM). We present contributions in the areas of sampling, partition function estimation, optimization and the more general topic of invariant feature learning. With regards to sampling, we present a novel adaptive parallel tempering method which dynamically adjusts the temperatures under simulation to maintain good mixing in the presence of complex multi-modal distributions. When used in the context of stochastic maximum likelihood (SML) training, the improved ergodicity of our sampler translates to increased robustness to learning rates and faster per epoch convergence. Though our application is limited to BM, our method is general and is applicable to sampling from arbitrary probabilistic models using Markov Chain Monte Carlo (MCMC) techniques. While SML gradients can be estimated via sampling, computing data likelihoods requires an estimate of the partition function. Contrary to previous approaches which consider the model as a black box, we provide an efficient algorithm which instead tracks the change in the log partition function incurred by successive parameter updates. Our algorithm frames this estimation problem as one of filtering performed over a 2D lattice, with one dimension representing time and the other temperature. On the topic of optimization, our thesis presents a novel algorithm for applying the natural gradient to large scale Boltzmann Machines. Up until now, its application had been constrained by the computational and memory requirements of computing the Fisher Information Matrix (FIM), which is square in the number of parameters. The Metric-Free Natural Gradient algorithm (MFNG) avoids computing the FIM altogether by combining a linear solver with an efficient matrix-vector operation. The method shows promise in that the resulting updates yield faster per-epoch convergence, despite being slower in terms of wall clock time. Finally, we explore how invariant features can be learnt through modifications to the BM energy function. We study the problem in the context of the spike & slab Restricted Boltzmann Machine (ssRBM), which we extend to handle both binary and sparse input distributions. By associating each spike with several slab variables, latent variables can be made invariant to a rich, high dimensional subspace resulting in increased invariance in the learnt representation. When using the expected model posterior as input to a classifier, increased invariance translates to improved classification accuracy in the low-label data regime. We conclude by showing a connection between invariance and the more powerful concept of disentangling factors of variation. While invariance can be achieved by pooling over subspaces, disentangling can be achieved by learning multiple complementary views of the same subspace. In particular, we show how this can be achieved using third-order BMs featuring multiplicative interactions between pairs of random variables.
Dharmasena, Kalu Arachchillage Senarath. "The Non-alcoholic Beverage Market in the United States: Demand Interrelationships, Dynamics, Nutrition Issues and Probability Forecast Evaluation." Thesis, 2010. http://hdl.handle.net/1969.1/ETD-TAMU-2010-05-7911.
Peyret, Thomas. "Développement de modèles prédictifs de la toxicocinétique de substances organiques." Thèse, 2013. http://hdl.handle.net/1866/9231.
Physiologically-based pharmacokinetic (PBPK) models simulate the internal dose metrics of chemicals based on species-specific and chemical-specific parameters. The existing quantitative structure-property relationships (QSPRs) allow to estimate the chemical-specific parameters (partition coefficients (PCs) and metabolic constants) but their applicability is limited by their lack of consideration of variability in input parameters and their restricted application domain (i.e., substances containing CH3, CH2, CH, C, C=C, H, Cl, F, Br, benzene ring and H in benzene ring). The objective of this study was to develop new knowledge and tools to increase the applicability domain of QSPR-PBPK models for predicting the inhalation toxicokinetics of organic compounds in humans. First, a unified mechanistic algorithm was developed from existing models to predict macro (tissue and blood) and micro (cell and biological fluid) level PCs of 142 drugs and environmental pollutants on the basis of tissue and blood composition along with physicochemical properties. The resulting algorithm was applied to compute the tissue:blood, tissue:plasma and tissue:air PCs in rat muscle (n = 174), liver (n = 139) and adipose tissue (n = 141) for acidic, neutral, zwitterionic and basic drugs as well as ketones, acetate esters, alcohols, ethers, aliphatic and aromatic hydrocarbons. Then, a quantitative property-property relationship (QPPR) model was developed for the in vivo rat intrinsic clearance (CLint) (calculated as the ratio of the in vivo Vmax (μmol/h/kg bw rat) to the Km (μM)) of CYP2E1 substrates (n = 26) as a function of n-octanol:water PC, blood:water PC, and ionization potential). The predictions of the QPPR as lower and upper bounds of the 95% mean confidence intervals were then integrated within a human PBPK model. Subsequently, the PC algorithm and QPPR for CLint were integrated along with a QSPR model for the hemoglobin:water and oil:air PCs to simulate the inhalation pharmacokinetics and cellular dosimetry of volatile organic compounds (VOCs) (benzene, 1,2-dichloroethane, dichloromethane, m-xylene, toluene, styrene, 1,1,1-trichloroethane and 1,2,4 trimethylbenzene) using a PBPK model for rats. Finally, the variability in the tissue and blood composition parameters of the PC algorithm for rat tissue:air and human blood:air PCs was characterized by performing Markov chain Monte Carlo (MCMC) simulations. The resulting distributions were used for conducting Monte Carlo simulations to predict tissue:blood and blood:air PCs for VOCs. The distributions of PCs, along with distributions of physiological parameters and CYP2E1 content, were then incorporated within a PBPK model, to characterize the human variability of the blood toxicokinetics of four VOCs (benzene, chloroform, styrene and trichloroethylene) using Monte Carlo simulations. Overall, the quantitative approaches for PCs and CLint implemented in this study allow the use of generic molecular descriptors rather than specific molecular fragments to predict the pharmacokinetics of organic substances in humans. In this process, the current study has, for the first time, characterized the variability of the biological input parameters of the PC algorithms to expand the ability of PBPK models to predict the population distributions of the internal dose metrics of organic substances prior to testing in animals or humans.