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A simulated annealing algorithm for the creation of synthetic population in activity-based travel demand model

KSCE JOURNAL OF CIVIL ENGINEERING 2016年第6期20卷 2513-2523页

作者： Kim, Jooyoung Lee, Seungjae Univ Seoul Integrated Urban Res Ctr Seoul 02504 South Korea Univ Seoul Dept Transportat Engn Seoul 02504 South Korea

Synthetic population serves as an agent group of the population of activity patterns that possesses identical socio-economic characteristics applied on the model that forecasts the travel demand in the activity-based profile. During the development of agentbased traffic simulation model, the accuracy of simulation outcomes relies highly on population synthesis. This study endeavors to develop a synthetic population, based on the Simulated Annealing (SA) algorithm for the activity-based travel demand model. Hill climbing and cooling schedule are essential elements to be considered when applying SA into the synthetic population. Also, metropolis-hasting algorithm was employed to decide whether to select or dismiss the follow-up distribution so that hill climbing phenomenon can be prevented. Additionally, the stability of the algorithm was figured through a scenario analysis of the optimal combination of iteration and temperature T on cooling issue. On the basis of this result, the current condition of micro sample and census data were utilized to compare the IPF (Iterative Proportional Fitting) of previous methodology with the establishment result of suggested algorithm. It is found that the algorithm is valid and built with the synthetic population based on SA through statistical verification. It is resulted from the application of the suggested SA method that such tradition algorithm as IPF has zero-cell or sample biased problems. However, not only can SA algorithm overcome such problems but also it can effectively address hill climbing and cooling schedule issues.

关键词： synthetic population simulated annealing iterative proportional fitting metropolis-hasting algorithm activity-based simulation

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Identifiability of PBPK models with applications to dimethylarsinic acid exposure

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JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS 2015年第6期42卷 591-609页

作者： Garcia, Ramon I. Ibrahim, Joseph G. Wambaugh, John F. Kenyon, Elaina M. Setzer, R. Woodrow Univ N Carolina Dept Biostat Chapel Hill NC 27599 USA US EPA Natl Hlth & Environm Effects Lab Res Triangle Pk NC 27711 USA US EPA Natl Ctr Computat Toxicol Res Triangle Pk NC 27711 USA

Any statistical model should be identifiable in order for estimates and tests using it to be meaningful. We consider statistical analysis of physiologically-based pharmacokinetic (PBPK) models in which parameters cannot be estimated precisely from available data, and discuss different types of identifiability that occur in PBPK models and give reasons why they occur. We particularly focus on how the mathematical structure of a PBPK model and lack of appropriate data can lead to statistical models in which it is impossible to estimate at least some parameters precisely. Methods are reviewed which can determine whether a purely linear PBPK model is globally identifiable. We propose a theorem which determines when identifiability at a set of finite and specific values of the mathematical PBPK model (global discete identifiability) implies identifiability of the statistical model. However, we are unable to establish conditions that imply global discrete identifiability, and conclude that the only safe approach to analysis of PBPK models involves Bayesian analysis with truncated priors. Finally, computational issues regarding posterior simulations of PBPK models are discussed. The methodology is very general and can be applied to numerous PBPK models which can be expressed as linear time-invariant systems. A real data set of a PBPK model for exposure to dimethyl arsinic acid (DMA(V)) is presented to illustrate the proposed methodology.

关键词： PBPK Models Identifiability Gibbs sampling metropolis-hasting algorithm Dimethyl arsinic acid

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A Reproducibility Analysis of Synthetic Population Generation

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Transportation Research Procedia 2015年 6卷 50-63页

作者： Jooyoung Kim Seungjae Lee Research Professor Integrated Urban Research Center University of Seoul Seoul 130-743 Korea Professor Department of Transportation Eng University of Seoul Seoul 130-743 Korea

For the development of agent based traffic simulation model, population synthesis is critical to the accuracy of simulation outcomes. This paper attempts to develop the synthetic population generation based on the Simulated Annealing (SA) algorithm for the activity-based travel demand model. This algorithm leads to estimate the activity schedules according to the multi-dimensional characteristics of the synthetic populations. However, appropriate rules have not been established for the estimation of parameters in simulated annealing, and it requires a significant amount of time to find optimal solution. In order to apply SA into the synthetic population, hill climbing and cooling schedule should be considered. In this study, total absolute error was calculated to prevent hill climbing and used metropolis- hasting algorithm to determine whether to select or dismiss follow-up distribution. In addition, stability of the algorithm was determined through scenario analysis of the optimal combination of iteration and temperature “T” on the cooling schedule. Based on this result, the current condition of household travel diary survey and census data were used to compare the IPF(Iterative Proportional Fitting) of a previous methodology with the result of establishing suggested algorithm, performing procedures of creating synthetic population, and suggesting the validity of algorithm created with the synthetic population based on SA through statistical verification.

关键词： Population Synthesis Simulated Annealing metropolis-hasting algorithm Hill Climbing Cooling Schedule

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Bayesian estimations with isotropic and anisotropic matrices for a multinomial logit model 18th

Bayesian estimations with isotropic and anisotropic matrices...

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18th Annual International Conference on Knowledge-Based and Intelligent Information and Engineering Systems (KES)

作者： Matsumoto, Nozomi Kurosawa, Takeshi Tokyo Univ Sci Dept Math Informat Sci Grad Sch Sci Shinjuku Ku Tokyo 1628601 Japan Tokyo Univ Sci Fac Sci Dept Math Informat Sci Tokyo 1628601 Japan

This paper studies a metropolis-hastings (MH) algorithm of unknown parameters for a multinomial logit model. The MH algorithm which is one of the Bayesian estimation requires prior and proposal distributions. A selection of the prior and proposal distributions is an important issue of the Bayesian estimation. However, there is no a decisive approach for the determination of prior and proposal distributions. A posterior distribution is obtained from two distributions. The MH algorithm generates samples from the posterior distribution of the unknown parameters. Unless we give appropriate distributions, it leads to an inappropriate posterior distribution. In this paper, we discuss differences in the behaviors of autocorrelation functions in a selection of the proposal distributions. (C) 2014 The Authors. Published by Elsevier B.V.

关键词： Bayesian estimation isotropic anisotropic proposal distribution autocorrelation functions metropolis-hasting algorithm

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Estimation for the Parameter of Poisson-Exponential Distribution under Bayesian Paradigm

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Journal of Data Science 2014年第1期12卷 157-173页

作者： Sanjay Kumar Singh Umesh Singh Manoj Kumar Department of Statistics Banaras Hindu University DST-CIMS Banaras Hindu University

The present paper deals with the maximum likelihood and Bayes estimation procedure for the shape and scale parameter of Poisson-exponential distribution for complete sample. Bayes estimators under symmetric and asymmetric loss function are obtained using Markov Chain Monte Carlo (MCMC) technique. Performances of the proposed Bayes estimators have been studied and compared with their maximum likelihood estimators on the basis of Monte Carlo study of simulated samples in terms of their risks. The methodology is also illustrated on a real data set.

关键词： Bayes estimators complementary risk entropy loss function Gibbs sampling loss function metropolis-hasting algorithm prior distribution

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Bayesian Estimations with Isotropic and Anisotropic Matrices for a Multinomial Logit Model

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Procedia Computer Science 2014年 35卷 1474-1481页

作者： Nozomi Matsumoto Takeshi Kurosawa Department of Mathematical Information Science Graduate School of Science Tokyo University of Science 1-3 Kagurazaka Shinjuku-ku Tokyo 162-8601 Japan Department of Mathematical Information Science Faculty of Science Tokyo University of Science 1-3 Kagurazaka Shinjuku-ku Tokyo 162-8601 Japan

关键词： Bayesian estimation isotropic anisotropic proposal distribution autocorrelation functions metropolis-hasting algorithm

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Inversely estimating temperature sensitivity of soil carbon decomposition by assimilating a turnover model and long-term field data

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SOIL BIOLOGY & BIOCHEMISTRY 2012年 46卷 191-199页

作者： Sakurai, Gen Jomura, Mayuko Yonemura, Seiichiro Iizumi, Toshichika Shirato, Yasuhito Yokozawa, Masayuki Natl Inst Agroenvironm Sci Tsukuba Ibaraki 3058604 Japan Nihon Univ Coll Bioresources Sci Fujisawa Kanagawa 2520880 Japan

Change in temperature sensitivity of soil organic carbon (SOC) decomposition with change in soil qualities (i.e. decomposability or lability) is one of the most important issues to be evaluated for projection of future CO2 emissions from soils. We inversely estimated the temperature sensitivity of SOC decomposition rate by applying a hybrid of the metropolis-hasting algorithm and the particle filter method to the extended Rothamsted carbon model (RothC), together with long-term (9 years) experimental data on SOC obtained at five sites in Japanese upland soils. Contrary to the prediction of the Arrhenius kinetics theory, we found no significant differences in temperature sensitivity among soils with different qualities (represented as soil compartments in the RothC model). We also confirmed that there was a positive correlation between the relative temperature sensitivity of the humus compartment and future total CO2 emissions. The RothC model with default parameterization tended to overestimate future total CO2 emissions relative to the calibrated model, and the degree of overestimation was larger than that of underestimation. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Soil organic carbon Decomposition rate Temperature sensitivity Turnover model Long-term field experiment Data assimilation Particle filter metropolis-hasting algorithm

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INVERSE PROBLEM FOR ELECTROMAGNETIC PROPAGATION IN A DIELECTRIC MEDIUM USING MARKOV CHAIN MONTE CARLO METHOD

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INTERNATIONAL JOURNAL OF INNOVATIVE COMPUTING INFORMATION AND CONTROL 2012年第3B期8卷 2339-2346页

作者： Kojima, Fumio Knopp, Jeremy S. Kobe Univ Org Adv Sci & Technol Nada Ku Kobe Hyogo 6578501 Japan USAF AFRL RXLP Nondestruct Evaluat Branch Res Lab Wright Patterson AFB OH 45433 USA

This paper is concerned with a stochastic inverse methodology arising in electromagnetic imaging. Nondestructive testing using guided microwaves covers a wide range of industrial applications including early detection of anomalies in conducting materials. The focus of this paper is the identification of electromagnetic material parameters and emphasis is on one dimensional scattering of a dielectric slab. The direct problem can be solved numerically using the finite-difference time-domain method (FDTD). The Markov Chain Monte Carlo method (MCMC) is applied to the inversion problem. Some successful results of computational experiments are demonstrated in order to show the feasibility and applicability of the proposed method.

关键词： Microwave Dielectric loss Electrical cable FDTD metropolis-hasting algorithm

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A Short History of Markov Chain Monte Carlo: Subjective Recollections from Incomplete Data

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STATISTICAL SCIENCE 2011年第1期26卷 102-115页

作者： Robert, Christian Casella, George Univ Paris 09 CEREMADE F-75785 Paris 16 France Univ Florida Dept Stat Gainesville FL 32611 USA

We attempt to trace the history and development of Markov chain Monte Carlo (MCMC) from its early inception in the late 1940s through its use today. We see how the earlier stages of Monte Carlo (MC, not MCMC) research have led to the algorithms currently in use. More importantly, we see how the development of this methodology has not only changed our solutions to problems, but has changed the way we think about problems.

关键词： Gibbs sampling metropolis-hasting algorithm hierarchical models Bayesian methods

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Secure Range-Dependent Localization in Wireless Sensor Networks

Secure Range-Dependent Localization in Wireless Sensor Netwo...

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International Conference on Advanced Materials and Computer Science

作者： Zhang, Jia Zhang, Haiyan Lv, Jinna Liu, Yanchang Henan Inst Sci & Technol Xinxiang 453003 Peoples R China

ISBN: (纸本)9783037850978

In many applications of wireless sensor network (WSN), it is essential to ensure that sensors can determine their location, even in the presence of malicious adversaries. However, almost all the localization algorithms need the location information of reference nodes to locate the unknown nodes. When the location information is tempered by the attacks, the accuracy of these algorithms will degrade badly. We present a novel mechanism for secure localization. The mechanism aims to filter out malicious reference signals on the basis of the normal distribution trait among multiple reference signals. This will ensure each node to obtain correct information about its position in the presence of attackers. In this paper, a simulation circumstance which might be attacked is constructed to compare the improved algorithm with original one. The experiment results demonstrate that the proposed mechanism can effectively survive malicious attacks.

关键词： wireless sensor networks metropolis-hasting algorithm range-dependent localization Centroid

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