The incompressible Navier Stokes equations are solved numerically using the Fractional Step algorithm. A Cartesian staggered-grid solver based on a high order upwind reconstruction of the convective flux is developed ...
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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...
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 a...
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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.
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 smo...
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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.
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 ...
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PDE-based numerical simulation applications commonly use basic software infrastructure to manage mesh, geometry, and discretization data. The commonality of this infrastructure implies the software is theoretically am...
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ISBN:
(纸本)1563478072
PDE-based numerical simulation applications commonly use basic software infrastructure to manage mesh, geometry, and discretization data. The commonality of this infrastructure implies the software is theoretically amenable to re-use. However, the traditional reliance on library-based implementations of these functionalities hampers experimentation with different software instances that provide similar functionality. This is especially true for meshing and geometry libraries where applications often directly access the underlying data structures, which can be quite different from implementation to implementation. Thus, using different libraries interchangeably or interoperably for this functionality has proven difficult at best and has hampered the wide spread use of advanced meshing and geometry tools developed by the research community. To address these issues, the Terascale Simulation Tools and Technologies center is working to develop standard interfaces to enable the creation of interoperable and interchangeable simulation tools. In this paper, we focus on a language-and data-structure-independent interface supporting query and modification of mesh data conforming to a general abstract data model. We describe the model and interface, and provide programming "best practices" recommendations based on early experience implementing and using the interface.
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 intersect...
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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 intersect...
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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.
作者：
P. SussnerInstitute for Mathematics
Statisticsand Scientific Computation Department of Applied Mathematics State University of Campinas Sao Paulo Brazil
Perceptrons have been used to classify patterns into different classes. Several researchers introduced a novel class of artificial neural networks, called morphological neural networks. In this new theory, the first s...
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Perceptrons have been used to classify patterns into different classes. Several researchers introduced a novel class of artificial neural networks, called morphological neural networks. In this new theory, the first step in computing the next state of a neuron or in performing the next layer neural network computation involves the nonlinear operation of adding neural values and their synaptic strengths followed by forming the maximum of the results. Ritter et al. (1997) have shown that the properties of morphological neural networks differ drastically from those of traditional neural network models. In this paper, the author introduces a learning algorithm for multilayer morphological perceptrons which is capable of solving arbitrary classification problems of patterns into two classes.
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