We base our method on the ensemble smoother with multiple data assimilation (ES-MDA) as it is one of the most widely used iterative ensemble smoothing techniques. In this paper, we formulate a flexible iterative ensemble smoother, which can be used to calibrate imperfect models where model errors cannot be neglected. This results in a bias estimated parameters and as a consequence might result in predictions with questionable quality. These approximations commonly introduce some type of model error which is generally unknown and when the models are calibrated, the effects of the model errors could be smeared by adjusting the model parameters to match historical observations. While significant efforts are usually made to ensure the accuracy of the mathematical model, it is widely known that the physical models are only an approximation of reality. However, iterative ensemble smoothers have been designed for perfect models under the main assumption that the specified physical models and subsequent discretized mathematical models have the capability to model the reality accurately.
Calibrating model in transcad software#
Experience with software development tools such as GitHub, version control, issue tracking, testing, etc.Iterative ensemble smoothers have been widely used for calibrating simulators of various physical systems due to the relatively low computational cost and the parallel nature of the algorithm.Experience with one or more transportation modeling packages (Cube, EMME, TransCAD, and/or VISUM).Proficiency in scientific computer programming with Java, C++, Python, R, C#/.Net, JavaScript, or similar.Effective in a variety of communication settings: one-to-one and in groups with peers, supervisors, and clients in-person and long-distance.Experience with and understanding of database and statistical software (e.g.Scripting experience with Python (pandas, NumPy), R, VB, GISDK, or similar.0-3 years’ experience in transportation and/or land-use models, data science, or a related field.Master’s degree or higher in a quantitative field, such as engineering, math, computer science, or geography.
You participate in meetings with team members and clients, and you manage your tasks on time, within budget, and to the pleasure of your clients. You are amiable and have strong interpersonal, analytical, and problem-solving skills that enable you to create and communicate complex technical materials in clear, concise, and meaningful ways that technical and non-technical people will understand. You have good technical judgment and work as a team player who is a resourceful, clear, and creative thinker. You are part of a team that is dedicated to developing innovative “best in class” models, software, and forecasts for regions and states throughout the US. More specifically, modeling activities include specification and estimation of models, data analysis, scripting, model implementation, software development, and calibrating and validating model components. Your work also involves a wide range of transportation modeling activities, including model design, data analysis and scripting, development and evaluation of forecasts, and documentation of technical work. Your work involves data development, data management, and data analysis using standard databases and GIS, as well as statistical analysis and programming to support the development and application of travel forecasting models. You help develop forecasting tools and data products to support US transportation agencies as they navigate the rapidly evolving world of smart mobility.
0 kommentar(er)
