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Mediterranean Conference on Control and Automation

作者： Baras, John S. Applied Mathematics Statistics and Scientific Computation Program Institute for Systems Research University of Maryland College Park United States

ISBN: (纸本)9781457701252

Networked systems are ubiquitous. A taxonomy of networked systems includes infrastructure and communication networks, social and economic networks, biological networks and biological swarms, robotic swarms, and several other categories. Most networked systems include physical components and cyber components implemented in various ways. Thus many networked systems come from the domain of cyberphysical systems (CPS). Cooperative networked systems represent from a certain abstract point of view a distributed and (at least partially) asynchronous implementation of the well known cycle "sense-decide-actuate" of control systems. Yet the interaction of dynamics, sensing, control and decision making, with network structures has created the need for a new scientific basis for the modeling, analysis, design and performance evaluation of such networked systems. For example, efforts to develop a new "Network Science" have emerged. Similarly, efforts to develop new theories of computation that emphasize multiple agents interacting over networks, beyond the conventional concepts and principles of computation and computability, have been also undertaken very recently. In another direction, several efforts have been undertaken very recently to develop models for such systems that integrate continuous and event-triggered dynamics within a framework that permits validation and testing of correctness. Thus the consideration of cooperative networked systems have raised fundamental new questions and challenges. © 2011 IEEE.

关键词： Decision making

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A multiobjective optimization approach to smart growth in land development

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Socio-Economic Planning Sciences 2006年第3期40卷 212-248页

作者： Gabriel, Steven A. Faria, José A. Moglen, Glenn E. Department of Civil and Environmental Engineering University of Maryland College Park MD 20742 United States Applied Mathematics and Scientific Computation Program University of Maryland College Park MD 20742 United States

In this paper we apply a multiobjective optimization model of Smart Growth to land development. The term Smart Growth is meant to describe development strategies-that do not promote urban sprawl. However, the term is somewhat open to interpretation. The multiobjective aspects arise when considering the conflicting interests of the various stakeholders involved in land development decisions: the government planner, the environmentalist, the conservationist, and the land developer. We present a formulation-employing linear and convex quadratic objective functions subject to polyhedral and binary constraints for the stakeholders. The resulting optimization problems are convex, quadratic mixed integer programs that are NP-complete. We report numerical results with this model for Montgomery County, Maryland, and present them using a geographic information system (GIS). © 2005 Elsevier Ltd. All rights reserved.

关键词： Geographic Information System Integer programming Land use planning Large Scale Optimization Multiple objective programming Quadratic programming Smart Growth

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A family of growth models for representing the price process in online auctions 07

A family of growth models for representing the price process...

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Proceedings of the ninth international conference

作者： Hyde, Valerie Jank, Wolfgang Shmueli, Galit Applied Mathematics and Scientific Computation Program University of Maryland College Park MD 20742 Decision and Information Technologies Department Robert H. Smith School of Business University of Maryland College Park MD 20742

ISBN: (纸本)1595937005

Bids during an online auction arrive at unequally-spaced discrete time points. Our goal is to capture the entire continuous price-evolution function by representing it as a functional object. Various nonparametric smoothing methods exist to recover the functional object from the observed discrete bid data. Previous studies use penalized polynomial and monotone smoothing splines;however, these require the determination and storage of a large number of coefficients and often lengthy computational time. We present a family of parametric growth curves that describe the price-evolution during online auctions. This approach is parsimonious and has an appealing interpretation in the online auction context. We also provide an automated fitting algorithm that is computationally fast. Methods are illustrated using eBay data. Copyright 2007 ACM.

关键词： Cost accounting

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Preconditioning techniques for reduced basis methods for parameterized elliptic partial differential equations

Preconditioning techniques for reduced basis methods for par...

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作者： Elman, Howard C. Forstall, Virginia Department of Computer Science Institute for Advanced Computer Studies University of Maryland College ParkMD20742 United States Applied Mathematics and Statistics and Scientific Computation Program University of Maryland College ParkMD20742 United States

The reduced basis methodology is an efficient approach to solve parameterized discrete partial differential equations when the solution is needed at many parameter values. An offline step approximates the solution space, and an online step utilizes this approximation, the reduced basis, to solve a smaller reduced problem, which provides an accurate estimate of the solution. Traditionally, the reduced problem is solved using direct methods. However, the size of the reduced system needed to produce solutions of a given accuracy depends on the characteristics of the problem, and it may happen that the size is significantly smaller than that of the original discrete problem but large enough to make direct solution costly. In this scenario, it may be more effective to use iterative methods to solve the reduced problem. We construct preconditioners for reduced iterative methods which are derived from preconditioners for the full problem. This approach permits reduced basis methods to be practical for larger bases than direct methods allow. We illustrate the effectiveness of iterative methods for solving reduced problems by considering two examples, the steady-state diffusion and convection-diffusion-reaction equations. © 2015 Society for Industrial and applied mathematics.

关键词： Iterative methods

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Online traffic light control through gradient estimation using stochastic fluid models

Online traffic light control through gradient estimation usi...

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作者： Panayiotou, Christos G. Howell, William C. Fu, Michael Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Applied Mathematics Scientific Computation Program Department of Mathematics University of Maryland College Park MD 20742 United States Smith School of Business and Institute for Systems Research University of Maryland College Park MD 20742 United States

ISBN: (纸本)008045108X

in this paper, we consider the problem of dynamically regulating the timing of traffic light controllers in busy cities. We use a Stochastic Fluid Model (SFM) to model the dynamics of the queues formed at an intersection. Based on this model, we derive gradients of the queue lengths with respect to the green/red light lengths within a signal cycle. We report preliminary numerical results comparing the performance of the estimates with finite-difference and smoothed perturbation analysis estimates. Then all estimators are used to optimize the traffic system via Stochastic Approximation. Copyright © 2005 IFAC.

关键词： Stochastic systems

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Estimating functional agent-based models: An application to bid shading in online markets format 11

Estimating functional agent-based models: An application to ...

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13th Annual Genetic and Evolutionary computation Conference - Companion Publication, GECCO 2011 Companion

作者： Guo, Wei Jank, Wolfgang Rand, William Applied Mathematics and Statistics and Scientific Computation Program Department of Mathematics University of Maryland College Park MD United States Department of Decision Operations and Information Technology Robert H. Smith School of Business University of Maryland College Park MD United States Department of Marketing Robert H. Smith School of Business University of Maryland College Park MD United States

ISBN: (纸本)9781450306904

Bid shading is a common strategy in online auctions to avoid the "winner's curse". While almost all bidders shade their bids, at least to some degree, it is impossible to infer the degree and volume of shaded bids directly from observed bidding data. In fact, most bidding data only allows us to observe the resulting price process, i.e. whether prices increase fast (due to little shading) or whether they slow down (when all bidders shade their bids). In this work, we propose an agent-based model that simulates bidders with different bidding strategies and their interaction with one another. We calibrate that model (and hence estimate properties about the propensity and degree of shaded bids) by matching the emerging simulated price process with that of the observed auction data using genetic algorithms. From a statistical point of view, this is challenging because we match functional draws from simulated and real price processes. We propose several competing fitness functions and explore how the choice alters the resulting ABM calibration. We apply our model to the context of eBay auctions for digital cameras and show that a balanced fitness function yields the best results. © 2011 ACM.

关键词： Calibration

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Estimation of mask effectiveness perception for small domains using multiple data sources

arXiv

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arXiv 2021年

作者： Sen, Aditi Lahiri, Partha Applied Mathematics & Statistics and Scientific Computation University of Maryland College Park United States The Joint Program in Survey Methodology Department of Mathematics University of Maryland College ParkMD20742 United States

All pandemics are local;so learning about the impacts of pandemics on public health and related societal issues at granular levels is of great interest. COVID-19 is affecting everyone in the globe and mask wearing is one of the few precautions against it. To quantify people's perception of mask effectiveness and to prevent the spread of COVID-19 for small areas, we use Understanding America Study's (UAS) survey data on COVID-19 as our primary data source. Our data analysis shows that direct survey-weighted estimates for small areas could be highly unreliable. In this paper, we develop a synthetic estimation method to estimate proportions of mask effectiveness for small area using a logistic model that combines information from multiple data sources. We select our working model using an extensive data analysis facilitated by a new variable selection criterion for survey data and benchmarking ratios. We propose a jackknife method to estimate variance of our proposed estimator. From our data analysis, it is evident that our proposed synthetic method outperforms direct survey-weighted estimator with respect to commonly used evaluation measures. Copyright © 2021, The Authors. All rights reserved.

关键词： Data handling

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ONLINE TRAFFIC LIGHT CONTROL THROUGH GRADIENT ESTIMATION USING STOCHASTIC FLUID MODELS

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IFAC Proceedings Volumes 2005年第1期38卷 90-95页

作者： Christos G. Panayiotou William C. Howell Michael Fu Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Department of Mathematics Applied Mathematics Scientific Computation Program University of Maryland College Park MD 20742 USA Smith School of Business and Institute for Systems Research University of Maryland College Park MD 20742 USA

In this paper, we consider the problem of dynamically regulating the timing of traffic light controllers in busy cities. We use a Stochastic Fluid Model (SFM) to model the dynamics of the queues formed at an intersection. Based on this model, we derive gradients of the queue lengths with respect to the green/red light lengths within a signal cycle. We report preliminary numerical results comparing the performance of the estimates with finite-difference and smoothed perturbation analysis estimates. Then all estimators are used to optimize the traffic system via Stochastic Approximation.

关键词： Traffic control perturbation analysis stochastic approximation

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Representing GASPEC with the world gas model

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Energy Journal 2009年第SPECIAL ISSUE 1期30卷 97-118页

作者： Egging, Ruud Holz, Franziska Von Hirschhausen, Christian Gabriel, Steven A. 1143 Glenn L. Martin Hall Dept of Civil and Environmental Engineering University of Maryland College Park MD 20742-3021 United States DIW Berlin 10117 Berlin Mohrenstr. 58 Germany Chair of Energy Economics and Public Sector Management TU Dresden 01062 Dresden Germany Applied Mathematics and Scientific Computation Program University of Maryland College Park MD 20742 United States

This paper presents results of simulating a more collusive behavior of a group of natural gas producing and exporting countries, sometimes called GASPEC. We use the World Gas Model, a dynamic, strategic representation of world gas production, trade, and consumption between 2005 and 2030. In particular, we simulate a closer cooperation of the GASPEC countries when exporting pipeline gas and liquefied natural gas;we also run a more drastic scenario where GASPEC countries deliberately hold back production. The results show that compared to our Base Case, a gas cartel would reduce total supplied quantities and induce price increases in gas importing countries up to 22%. There is evidence that the natural gas markets in Europe and North America would be affected more than other parts of the world. Lastly, the vulnerability of gas importers worldwide is further illustrated by the results of a sensitivity case in which price levels are up to 87% higher in Europe and North America. Copyright © 2009 by the IAEE. All rights reserved.

关键词： Cartels Liquefied natural gas Natural gas pipelines Supply Natural gas Financial investments Imports Natural gas production Liquefaction Fuel consumption

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On the relationship between forecast accuracy and detection performance: An application to biosurveillance

On the relationship between forecast accuracy and detection ...

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IEEE Conference on Technologies for Homeland Security

作者： Thomas Lotze Galit Shmueli Applied Mathematics and Scientific Computation Program University of Maryland College Park MD USA Department of Decision Operations & Information Technologies and Center for Health and Information Decision Systems University of Maryland College Park MD USA

While many methods have been proposed for detecting disease outbreaks from pre-diagnostic data, their performance is usually not well understood. In this paper, we describe the relationship between forecast accuracy and the detection accuracy of a method. We argue that most existing temporal detection methods for biosurveillance can be characterized as a forecasting component coupled with a monitoring/detection component. We show that improved forecasting results in improved detection and we quantify the relationship between forecast accuracy and detection metrics under different scenarios. The forecast accuracy can then be used to rate an algorithm's expected performance in detecting outbreaks. Simulation is used to compare empirical performance with theoretical results; we also show examples with authentic biosurveillance data.

关键词： Control charts Yttrium Educational institutions Diseases Signal generators Bioinformatics Probability Condition monitoring Error correction Statistics

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