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Relevant bibliographies by topics / Microsimulation model

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Academic literature on the topic 'Microsimulation model'

Author: Grafiati

Published: 4 June 2021

Last updated: 19 February 2022

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Journal articles on the topic "Microsimulation model"

1

Walker, Joan L. "Making Household Microsimulation of Travel and Activities Accessible to Planners." Transportation Research Record: Journal of the Transportation Research Board 1931, no. 1 (January 2005): 38–48. http://dx.doi.org/10.1177/0361198105193100105.

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There is a large gap between the aggregate, trip-based models used by transportation planning agencies and the activity-based, microsimulation methods espoused by those at the forefront of research. The modeling environment presented here is intended to bridge this gap by providing a palatable way for planning agencies to move toward advanced methods. Three components to bridging the gap are emphasized: an incremental approach, a demonstration of clear gains, and a provision of an environment that eases initial implementation and allows for expansion. The modeling environment (called STEP2) is a household microsimulator, developed in TransCAD, that can be used to implement a four-step model as well as models with longer-term behavior and trip chaining. An implementation for southern Nevada is described, and comparisons are made with the region's aggregate four-step model. The models perform similarly in numerous ways. A key advantage to the microsimulator is that it provides impacts by socioeconomic group (essential for equity analysis) and individual trip movements (for use in a vehicle microsimulator). A sensitivity analysis indicates that the microsimulation model has less inelastic cross elasticity of transit demand with respect to auto travel times than the aggregate model (aggregation error). The trade-off is that microsimulators have simulation error; results are presented regarding the severity of this error. This work shows that a shift to microsimulation does not necessarily require substantial investment to achieve many of the benefits. One of the greatest advantages is a flexible environment that can expand to include additional sensitivity to demographics and transportation policy variables.

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O’Donoghue, Cathal. "Simulating migration microsimulation model." International Journal of Microsimulation 3, no. 2 (2009): 65–79. http://dx.doi.org/10.34196/ijm.00039.

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Šurdonja, Sanja, Daniela Nežić, and Aleksandra Deluka-Tibljaš. "The Roundabout Capacity Estimate Microsimulation Model." Journal of Maritime & Transportation Science 49-50, no. 1 (April 22, 2015): 143–65. http://dx.doi.org/10.18048/2015.49-50.143.

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Schweizer, Joerg, Cristian Poliziani, Federico Rupi, Davide Morgano, and Mattia Magi. "Building a Large-Scale Micro-Simulation Transport Scenario Using Big Data." ISPRS International Journal of Geo-Information 10, no. 3 (March 14, 2021): 165. http://dx.doi.org/10.3390/ijgi10030165.

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A large-scale agent-based microsimulation scenario including the transport modes car, bus, bicycle, scooter, and pedestrian, is built and validated for the city of Bologna (Italy) during the morning peak hour. Large-scale microsimulations enable the evaluation of city-wide effects of novel and complex transport technologies and services, such as intelligent traffic lights or shared autonomous vehicles. Large-scale microsimulations can be seen as an interdisciplinary project where transport planners and technology developers can work together on the same scenario; big data from OpenStreetMap, traffic surveys, GPS traces, traffic counts and transit details are merged into a unique transport scenario. The employed activity-based demand model is able to simulate and evaluate door-to-door trip times while testing different mobility strategies. Indeed, a utility-based mode choice model is calibrated that matches the official modal split. The scenario is implemented and analyzed with the software SUMOPy/SUMO which is an open source software, available on GitHub. The simulated traffic flows are compared with flows from traffic counters using different indicators. The determination coefficient has been 0.7 for larger roads (width greater than seven meters). The present work shows that it is possible to build realistic microsimulation scenarios for larger urban areas. A higher precision of the results could be achieved by using more coherent data and by merging different data sources.

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Lidbe, Abhay D., Alexander M. Hainen, and Steven L. Jones. "Comparative study of simulated annealing, tabu search, and the genetic algorithm for calibration of the microsimulation model." SIMULATION 93, no. 1 (January 2017): 21–33. http://dx.doi.org/10.1177/0037549716683028.

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Microsimulation modeling is one of the contemporary techniques that has potential to perform complex transportation studies faster, safer, and in a less expensive manner. However, to get accurate and reliable results, the microsimulation models need to be well calibrated. Microsimulation model consists of various sub-models each having many parameters, most of which are user-adjustable and are attuned for calibrating the model. Manual calibration involves an iterative trial-and-error process of using the intuitive discrete values of each parameter and feasible combinations of multiple parameters each time until the desired results are obtained. With this approach, it is possible to easily get caught in a never-ending circular process of fixing one problem only to generate another. This can make manual calibration a time-consuming process and is suggested only when the number of parameters is small. However, when the calibration parameter subset is large, an automated process is suggested in the literature. Amongst the meta-heuristics used for calibrating microsimulation models, the genetic algorithm (GA) has been widely used and simulated annealing (SA) has been used only once in the past. Thus, the question of which meta-heuristics is more suitable for the problem of calibration of the microsimulation model still remains open. Thus, the objective of this paper is to evaluate and compare the manual and three (the GA, SA, and tabu search (TS)) meta-heuristics for calibration of microsimulation models. This paper therefore addresses the need to examine and identify the suitability of a meta-heuristics for calibrating microsimulation models. The results show that the meta-heuristics approach can be relied upon for calibrating simulation models very effectively, as it offers the benefit of automating the cumbersome calibrating process. All three meta-heuristics (the GA, SA, and TS) have the ability to find better calibrating parameters than the manually calibrated parameters. The number of better solutions, the best solution, and convergence to the best solution by TS is better than those by the GA and SA. Significant time can be saved by automating calibration of microsimulation models using meta-heuristics. The approach presented in this research can be used to help engineers and planners achieve better modeled results, as the calibration of microsimulation models is likely to become more complex in the future.

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DeBacker, Jason, Richard W. Evans, and Kerk L. Phillips. "Integrating Microsimulation Models of Tax Policy into a DGE Macroeconomic Model." Public Finance Review 47, no. 2 (February 5, 2019): 207–75. http://dx.doi.org/10.1177/1091142118816744.

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This article proposes a method for integrating individual effective tax rates and marginal tax rates computed from a microsimulation (partial equilibrium) model of tax policy with a dynamic general equilibrium model of tax policy that can provide macroeconomic analysis or dynamic scores of tax reforms. Our approach captures the rich heterogeneity, realistic demographics, and tax-code detail of the microsimulation model and allows this detail to inform a general equilibrium model with a relatively high degree of heterogeneity. In addition, we propose a functional form in which tax rates depend jointly on the levels of both capital income and labor income.

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Klazar, Stanislav, and Martin Zelený. "Microsimulation Model for Distributional Analysis of Consumption Taxes." Český finanční a účetní časopis 2008, no. 3 (October 1, 2008): 56–68. http://dx.doi.org/10.18267/j.cfuc.280.

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Gomes, Gabriel, Adolf May, and Roberto Horowitz. "Congested Freeway Microsimulation Model Using VISSIM." Transportation Research Record: Journal of the Transportation Research Board 1876, no. 1 (January 2004): 71–81. http://dx.doi.org/10.3141/1876-08.

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Pasra, M., S. Hamid, A. Faisal, and H. Yatmar. "Model Microsimulation Roundabout Utilities in Makassar." IOP Conference Series: Materials Science and Engineering 875 (July 23, 2020): 012024. http://dx.doi.org/10.1088/1757-899x/875/1/012024.

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Wolf, Douglas A. "The Role of Microsimulation in Longitudinal Data Analysis." Canadian Studies in Population 28, no. 2 (December 31, 2001): 313. http://dx.doi.org/10.25336/p67k5x.

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Microsimulation is well known as a tool for static analysis of tax and transfer policies, for the generation of programmatic cost estimates, and dynamic analyses of socio-economic and demographic systems. However, microsimulation also has the potential to contribute to longitudinal data analysis in several ways, including extending the range of outputs generated by a model, addressing several defective-data problems, and serving as a vehicle for missing-data imputation. This paper discusses microsimulation procedures suitable for several commonly-used statistical models applied to longitudinal data. It also addresses the unique role that can be played by microsimulation in longitudinal data analysis, and the problem of accounting for the several sources of variability associated with microsimulation procedures.

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Dissertations / Theses on the topic "Microsimulation model"

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Jin, Jianhui. "A small area microsimulation model for water demand." Thesis, University of Leeds, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.507779.

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Chen, Siyu S. M. Massachusetts Institute of Technology Department of Civil and Environmental Engineering. "Calibrating activity-based travel demand model system via microsimulation." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123233.

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Thesis: S.M. in Transportation, Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2019
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 79-83).
This thesis addresses the problem of calibrating activity-based travel demand model systems. After estimation, it is common practice to use aggregate measurements to calibrate the estimated model system's parameters. However, calibration of activity-based model systems has received much less attention. Existing calibration approaches are myopic heuristics in the sense that they do not consider inter-dependency among choice-models and do not have a systematic way to adjust model parameters. Also, other simulation-based approaches do not perform well in large-scale applications. In this thesis, we focus on utility-maximizing nested logit activity-based model systems and calibrating count based aggregate statistics like OD flows, mode shares, activity shares and so on. We formulate the calibration problem as a simulation-based optimization problem and propose a stochastic gradient-based solution procedure to solve it. The solution procedure relies on microsimulation to calculate expected aggregate statistics of interest to the calibration problem. Additionally, we derive approximate analytical expressions for the gradient of the objective function -that are evaluated through microsimulation on mini-batches of the population. The proposed solution procedure is sensitive to the fundamental structure of the activity-based model system and is non-myopic in considering the dependencies across its model components. Finally, we show -through a real-world application- that the proposed solution procedure outperforms other state-of-the-art purely simulation-based optimization approaches in terms of computational efficiency, stability, and convergence. We also compare various gradient-based solution algorithms to determine the best algorithm to update the parameters. This work has the potential to facilitate wider and easier application of activity-based model systems.
by Siyu Chen.
S.M. in Transportation
S.M.inTransportation Massachusetts Institute of Technology, Department of Civil and Environmental Engineering

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Lenormand, Maxime. "Initialize and Calibrate a Dynamic Stochastic Microsimulation Model: Application to the SimVillages Model." Phd thesis, Université Blaise Pascal - Clermont-Ferrand II, 2012. http://tel.archives-ouvertes.fr/tel-00764929.

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Le but de cette thèse est de développer des outils statistiques permettant d'initialiser et de calibrer les modèles de microsimulation dynamique stochastique, en partant de l'exemple du modèle SimVillages (développé dans le cadre du projet Européen PRIMA). Ce modèle couple des dynamiques démographiques et économiques appliquées à une population de municipalités rurales. Chaque individu de la population, représenté explicitement dans un ménage au sein d'une commune, travaille éventuellement dans une autre, et possède sa propre trajectoire de vie. Ainsi, le modèle inclut-il des dynamiques de choix de vie, d'étude, de carrière, d'union, de naissance, de divorce, de migration et de décès. Nous avons développé, implémenté et testé les modèles et méthodes suivants: * un modèle permettant de générer une population synthétique à partir de données agrégées, où chaque individu est membre d'un ménage, vit dans une commune et possède un statut au regard de l'emploi. Cette population synthétique est l'état initial du modèle. * un modèle permettant de simuler une table d'origine-destination des déplacements domicile-travail à partir de données agrégées. * un modèle permettant d'estimer le nombre d'emplois dans les services de proximité dans une commune donnée en fonction de son nombre d'habitants et de son voisinage en termes de service. * une méthode de calibration des paramètres inconnus du modèle SimVillages de manière à satisfaire un ensemble de critères d'erreurs définis sur des sources de données hétérogènes. Cette méthode est fondée sur un nouvel algorithme d'échantillonnage séquentiel de type Approximate Bayesian Computation.

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Papapanagos, Harry. "On the analysis of tax reform : a microsimulation tax-benefit model for Greece." Thesis, University of Essex, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.333725.

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Válková, Michaela. "Mikroskopický model dopravy ulic Veveří a Kounicova." Master's thesis, Vysoké učení technické v Brně. Fakulta stavební, 2018. http://www.nusl.cz/ntk/nusl-371971.

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Diploma thesis deals with microscopic traffic model of the streets Veveří and Kounicova including adjacent road network. This model was created in software Aimsun based on maps, the results of the directional survey, traffic intensity at junctions and signal plans. Elaborated model of the current state location of interest was calibrated according to the traffic intensities on the entrance and exit roads. They have also been designed and created three possible variants of the solution streets Veveří and Kounicova. All variants were finally compared and evaluated.

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Harding, Ann. "Lifetime income distribution and redistribution in Australia : applications of a dynamic cohort microsimulation model." Thesis, London School of Economics and Political Science (University of London), 1991. http://etheses.lse.ac.uk/1164/.

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The first part of the thesis describes the construction of Australia's first dynamic cohort microsimulation model. The model consists of a pseudo-cohort of 4000 males and females, who are aged from birth to death, with the processes of mortality, education, marriage, divorce, fertility, labour force participation, the receipt of earnings and other income, the receipt of social security and education transfers and the payment of income tax being simulated for every individual in the model for every year of life. The second part of the thesis describes some of the results which can be derived from the model. These include the differences in lifetime income by lifetime education and family status, the distribution of lifetime income, the difference between the lifetime and annual distributions of income, the lifetime and annual incidence of taxes and transfers, and the direction and extent of intra and interpersonal redistribution of income over the lifecycle due to government transfers and income taxes.

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Stevenson, Christopher Eric, and Chris Stevenson@aihw gov au. "A microsimulation study of the benefits and costs of screening for colorectal cancer." The Australian National University. National Centre for Epidemiology and Population Health, 2001. http://thesis.anu.edu.au./public/adt-ANU20040611.162207.

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This thesis examines the benefits and costs of screening for colorectal cancer in the context of an organised population screening programme. It uses microsimulation modelling to derive an optimally cost-effective screening protocol for various combinations of the available screening tests. ¶ First a mathematical model for the natural history of colorectal cancer is derived, based on analyses of Australian population and hospital-based cancer registries combined with data from published studies. Then a model for population based screening is derived based mainly on data from published screening studies, including the four major published randomised controlled trials of faecal occult blood test (FOBT) screening. These two models are used to simulate the application of a screening programme to the Australian population. The simulations are applied to a period of 40 years following 1990 (the studys base year), with both costs and benefits discounted back to the base year at an annual rate of 3%.¶ The models are applied to simulating a population screening programme based on FOBT with a colonoscopy follow up of positive tests. This simulation suggests that the optimal application of such a programme would be to offer annual screening to people aged 50 to 84 years. Such a programme would lead to a cumulative fall in years of life lost to colorectal cancer (YLL) of 28.5% at a cost per year of life saved (YLS) of $8,987. These costs and benefits are consistent with those arising from other currently funded health interventions. They are also consistent with the cost per YLS which Australian governments appear willing to pay for health interventions when justified on the basis of cost-effectiveness. The fall in colorectal cancer deaths from this screening programme should be first detectable by a national monitoring system after around three years of screening. However the full benefits from screening would not be realised before around 30 years of screening.¶ These simulations are based on the standard guaiac FOBT, but the results suggest that significant cost-effective gains could be made by using the newer immunochemical FOBT. Further cost-effect gains could be made by offering sigmoidoscopy every five years in addition to annual FOBT.¶ The models are then applied to simulating population screening programmes using colonoscopy and sigmoidoscopy as primary screening tools. Offering colonoscopy every ten years to all people aged from 45 to 85 leads to an overall fall in cumulative YLL of 37.6%, at a cost of $15,585 per YLS. Offering sigmoidoscopy every three years to all people aged 40 to 85 leads to an overall fall in cumulative YLL of 29.1%, at a cost of $4,862 per YLS. Both of these cost and benefit results are also consistent with the cost per YLS which Australian governments appear willing to pay. The fall in deaths with colonoscopy screening would also be detectable after three years of screening but the fall with sigmoidoscopy screening would not be detectable until after six years of screening. Sigmoidoscopy would need around 35 years of screening to reach its potential gains while colonoscopy screening would not reach its full potential during the 40 year screening period.¶ Finally the models are applied to targeting people at higher risk of cancer. The results show that offering colonoscopy every five years to people at higher risk because of a family history of colorectal cancer is a cost-effective addition to the annual FOBT screening programme.¶ An earlier version of chapter two of this thesis has been published as Stevenson CE 1995. Statistical models for cancer screening. Statistical Methods in Medical Research; 4: 1923.¶ An expanded version of chapter two, along with parts of chapter one, has been published as Stevenson CE 1998. Models of screening. In: Encyclopedia of Biostatistics. Armitage P, Colton T, eds. John Wiley and Sons Ltd, pp 39994022.

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Francois, Clément, Philippe Laramée, Nora Rahhali, Ylana Chalem, Samuel Aballéa, Aurélie Millier, Sébastien Bineau, Mondher Toumi, and Jürgen Rehm. "A Predictive Microsimulation Model to Estimate the Clinical Relevance of Reducing Alcohol Consumption in Alcohol Dependence." Karger, 2014. https://tud.qucosa.de/id/qucosa%3A71614.

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Background: Alcohol consumption is one of the most important factors for disease and disability in Europe. In clinical trials, nalmefene has resulted in a significant reduction in the number of heavy-drinking days (HDDs) per month and total alcohol consumption (TAC) among alcohol-dependent patients versus placebo. Methods: A microsimulation model was developed to estimate alcohol-attributable diseases and injuries in patients with alcohol dependence and to explore the clinical relevance of reducing alcohol consumption. Results: For all diseases and injuries considered, the number of events (inpatient episodes) increased with the number of HDDs and TAC per year. The model predicted that a reduction of 20 HDDs per year would result in 941 fewer alcohol-attributable events per 100,000 patients, while a reduction in intake of 3,000 g/year of pure alcohol (ethanol) would result in 1,325 fewer events per 100,000 patients. Conclusion: The potential gains of reducing consumption in alcohol-dependent patients were considerable.

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Wu, Mingqing Belinda. "A hybrid microsimulation model for a UK city population with dynamic, spatial and agent based features." Thesis, University of Leeds, 2012. http://etheses.whiterose.ac.uk/3758/.

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This research aims to study and understand a complex social system through the development of an individual based hybrid model of the population of Leeds, UK. It attempts to demonstrate the importance of individual based modelling and simulation tools within the scope of demographic planning, as well as in application of a variety of substantive research and planning environments. The model adopts a hybrid modelling approach that combines the strength of two individual based modelling approaches: the first employs a dynamic spatial Micro-Simulation Model (MSM) and the second uses an Agent Based Model (ABM). This framework enables the modelling of a complex social system that is both theoretically and practically challenging. It attempts to provide a fuller picture of the population evolution through the simulation of discrete changes experienced by a large number of individuals within small areas and demonstrates heterogeneous characteristics in individuals and their behaviours reflecting not only individual demographic characteristics, but also interactions with each other and/or their local environment. This thesis describes the modelling method, system development, results alignment and model applications, as well as discussing the limitations and future potential of this model.

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Schofield, Deborah, and n/a. "Modelling health care expenditure : a new microsimulation approach to simulating the distributional impact of the Pharmaceutical Benefits Scheme." University of Canberra. Information Sciences & Engineering, 1999. http://erl.canberra.edu.au./public/adt-AUC20061107.171802.

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In this thesis, a microsimulation model was developed using methods which were intended to overcome the main criticism of earlier models developed in Australia - that their estimation of the distribution of health benefits1 across income groups was not accurate. To determine whether the new model � called the Person Level Model of Pharmaceutical Benefits (PLM-PB) � was more accurate, two typical means-based models were also built to replicate the most commonly used methods in Australia. A comparison of the results of the three models revealed that while they produced comparable results at the aggregate when compared with administrative data, the PLM-PB was much more accurate in capturing distributional differences by beneficiary and medication type. The PLM-PB also indicated that, as anticipated, PBS benefits were more pro-poor than earlier means-based models had suggested. The PLM-PB had another important advantage in that the method also captured the variation in the use of medication and thus the subsidy received within sub-populations. As the PLM-PB was found to be more accurate than the means-based model, a multivariate analysis of the distribution of PBS subsidy across a number of socio-economic groups was undertaken as an example application of the model. It was found that health status (defined by number of recent illnesses) and concession card type were most important in explaining the amount of PBS subsidy received. This indicates that the distribution of PBS expenditure meets the policy objectives of assisting those most in need, whether need is defined as poor health or low income. 1 Benefits refer to expenditure as transfers from government to individuals rather than the general health benefits of using medication.

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Books on the topic "Microsimulation model"

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F, Gentleman Jane, Robertson D, and Monica Tomiak, eds. Smoothing procedures for simulated longitudinal microdata. [Ottawa, Ont.]: Statistics Canada, 1990.

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Antcliff, Susan. An introduction to DYNAMOD: A dynamic population microsimulation model. Canberra City, ACT: National Centre for Social and Economic Modelling, Faculty of Management, University of Canberra, 1993.

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Holm, Einar. The SVERIGE spatial microsimulation model: Content, validation, and example applications. Umeå: Kulturgeografiska institutionen/SMC, Umeå universitet, 2002.

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Lifetime income distribution and redistribution: Applications of a microsimulation model. Amsterdam: North-Holland, 1993.

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Fredriksen, Dennis. Projections of population, education, labour supply, and public pension benfits: Analyses with the dynamic microsimulation MODEL MOSART. Oslo: Statistics Norway, 1998.

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Harding, Ann. Dynamic microsimulation models: Problems and prospects. London: Welfare State Programme, Suntory-International Centre for Economics and Related Disciplines, London School of Economics, 1990.

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Asghar, Zaidi M., Harding Ann 1958-, and Williamson Paul, eds. New frontiers in microsimulation modelling. Farnham, England: Ashgate, 2009.

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International Microsimulation Association. Inaugural meeting. New frontiers in microsimulation modelling. Farnham, England: Ashgate, 2009.

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Introduction to molecular-microsimulation of colloidal dispersions. Amsterdam: Elsevier, 2003.

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IARIW Special Conference on Microsimulation and Public Policy (1993 Canberra, A.C.T.). Microsimulation and public policy: Selected papers from the IARIW Special Conference on Microsimulation and Public Policy, Canberra, 5-9 December, 1993. Amsterdam: Elsevier, 1996.

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Book chapters on the topic "Microsimulation model"

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Bélanger, Alain, and Patrick Sabourin. "Creating a Basic Cohort Model." In Microsimulation and Population Dynamics, 1–27. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-44663-9_1.

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Davis, Peter, and Roy Lay-Yee. "SociaLab: A Dynamic Microsimulation Model." In Computational Social Sciences, 21–31. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-04786-3_3.

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O’Donoghue, Cathal. "Spatial Microsimulation Model for Environmental Policy." In Farm-Level Microsimulation Modelling, 283–319. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63979-6_10.

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O’Donoghue, Cathal. "Static Farm Microsimulation Model: Price Impact." In Farm-Level Microsimulation Modelling, 49–86. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63979-6_3.

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O’Donoghue, Cathal. "Farm-Level Income Generation Microsimulation Model." In Farm-Level Microsimulation Modelling, 177–214. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63979-6_7.

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O’Donoghue, Cathal. "Inter-temporal Microsimulation Model: Forestry Planting Decisions." In Farm-Level Microsimulation Modelling, 241–82. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63979-6_9.

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Marois, Guillaume, and Samir KC. "Converting a Cohort Component Model into a Microsimulation Model." In SpringerBriefs in Population Studies, 25–49. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79111-7_3.

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AbstractIn this chapter, we show and explain the code that reproduces the multistate projection of India described in Chap. 10.1007/978-3-030-79111-7_2 into a microsimulation model. The microsimulation code is divided into modules for each demographic event, namely the mortality, the education, the fertility, the domestic migration, and the reclassification of rural to urban areas. Section by section, we explain the code for the simulation and the production of outputs. We also a basic validation of the mode. The code file “Chapter 3—Replicating multistate.sas” contains the final complete code that generates the simulation for 2010–2060, including the setting up of the workspace (see Chap. 10.1007/978-3-030-79111-7_2).

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Merz, Joachim. "MICSIM: Concept, Developments, and Applications of a PC Microsimulation Model for Research and Teaching." In Social Science Microsimulation, 33–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/978-3-662-03261-9_2.

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Feldman, Olga, Roger Mackett, Emma Richmond, David Simmonds, and Vassilis Zachariadis. "A Microsimulation Model of Household Location." In Residential Location Choice, 223–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-12788-5_11.

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Marois, Guillaume, and Samir KC. "Getting Started." In SpringerBriefs in Population Studies, 11–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79111-7_2.

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AbstractThis chapter sets the stage before building the microsimulation model. First, we describe proprieties of the microsimulation model that will be built. The model is time-based, discrete-time and stochastic. We then describe properties of a multistate model that will be converted into a microsimulation model and we show how building a synthetic base population that consists of the individuals that will be projected. We finally explain how to set up the workspace in SAS.

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Conference papers on the topic "Microsimulation model"

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Zinn, Sabine, Jutta Gampe, Jan Himmelspach, and Adelinde M. Uhrmacher. "A DEVS model for demographic microsimulation." In the 2010 Spring Simulation Multiconference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1878537.1878689.

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Huang, Weinan, Jian Sun, Heng Wang, and Keping Li. "Design of IDSS for Traffic Microsimulation Model Calibration." In 2008 Second International Symposium on Intelligent Information Technology Application (IITA). IEEE, 2008. http://dx.doi.org/10.1109/iita.2008.229.

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Swan, Breanna, Siddhartha Nambiar, Priscille Koutouan, Maria E. Mayorga, Julie Ivy, Edwards P. Fitts, and Stephen Fransen. "Evaluating Diabetic Retinopathy Screening Interventions in a Microsimulation Model." In 2020 Winter Simulation Conference (WSC). IEEE, 2020. http://dx.doi.org/10.1109/wsc48552.2020.9384074.

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Orlicky, Adam, Alina Mashko, and Josef Mik. "Microsimulation model for assessment of eHMI of autonomous vehicles." In 2021 Smart City Symposium Prague (SCSP). IEEE, 2021. http://dx.doi.org/10.1109/scsp52043.2021.9447377.

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Huang, Weinan, and Jian Sun. "A NGSA-II Based Parameter Calibration Algorithm for Traffic Microsimulation Model." In 2009 International Conference on Measuring Technology and Mechatronics Automation (ICMTMA). IEEE, 2009. http://dx.doi.org/10.1109/icmtma.2009.437.

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Schmidt, M., Y. Sahakyan, B. H. Cuthbertson, N. Daneman, R. Fowler, S. Goddard, R. Talla, and B. Sander. "Selective Digestive Decontamination in the ICU: A Dynamic Population, Microsimulation Model." In American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a4136.

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Gazder, U., M. Hamid, and M. Yazan. "Traffic Microsimulation Model for Bahrain: A Step Towards Smart Traffic System." In Smart Cities Symposium 2018. Institution of Engineering and Technology, 2018. http://dx.doi.org/10.1049/cp.2018.1383.

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Hussain, K. Zakir, M. Durairaj, and G. Rabia Jahani Farzana. "Analysing offender's attributes in the event of robbery by using microsimulation model." In 2012 IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT). IEEE, 2012. http://dx.doi.org/10.1109/icaccct.2012.6320726.

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Paul, M., V. Charan, V. Soni, and I. Ghosh. "Calibration Methodology of Microsimulation Model for Unsignalized Intersection under Heterogeneous Traffic Conditions." In ASCE India Conference 2017. Reston, VA: American Society of Civil Engineers, 2018. http://dx.doi.org/10.1061/9780784482025.063.

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Hannappel, Marc, Klaus G. Troitzsch, and Simone Bauschke. "Demographic And Educational Projections. Building An Event-Oriented Microsimulation Model With CoMICS II." In 26th Conference on Modelling and Simulation. ECMS, 2012. http://dx.doi.org/10.7148/2012-0613-0618.

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Reports on the topic "Microsimulation model"

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Basu, N., R. J. Pryor, T. Quint, and T. Arnold. Aspen: A microsimulation model of the economy. Office of Scientific and Technical Information (OSTI), October 1996. http://dx.doi.org/10.2172/399684.

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Spielauer, Martin. The "LifeCourse" model, a competing risk cohort microsimulation model: source code and basic concepts of the generic microsimulation programming language Modgen. Rostock: Max Planck Institute for Demographic Research, November 2006. http://dx.doi.org/10.4054/mpidr-wp-2006-046.

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Noble, Michael. How to implement sub-national poverty lines in a SOUTHMOD country model using conditional constants: The case of UGAMOD. UNU-WIDER, March 2021. http://dx.doi.org/10.35188/unu-wider/wtn/2021-3.

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This note describes how to incorporate sub-national poverty lines into a SOUTHMOD country model using conditional constants within the constants function in such a way that the Statistics Presenter can generate national-level poverty statistics. The Uganda tax-benefit microsimulation model UGAMOD is used as an example.

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Brown, M. J., C. Mueller, B. Bush, and P. Stretz. Exposure estimates using urban plume dispersion and traffic microsimulation models. Office of Scientific and Technical Information (OSTI), December 1997. http://dx.doi.org/10.2172/564119.

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