An algorithm for decomposing large tally data in Monte Carlo particle simulations is proposed, analyzed, and implemented/tested in a production Monte Carlo code, OpenMC. The algorithm relies on disjoint sets of compute processes and servers of which the former simulate particles moving through the geometry and the latter runs in a continuous loop receiving scores from the compute processors and...

We employ a nonlinear, nonparametric method to model the stochastic behavior of changes in several short and long term U.S. interest rates. We apply a nonlinear autoregression to the series using the locally weighted regression (LWR) estimation method, a nearest-neighbor method, and evaluate the forecasting performance with a measure of root mean square error (RMSE). We compare the forecasting ...

Locally weighted regression (LWR) was created as a nonparametric method that can approximate a wide range of functions, is computationally efficient, and can learn continually from very large amounts of incrementally collected data. As an interesting feature, LWR can regress on non-stationary functions, a beneficial property, for instance, in control problems. However, it does not provide a pro...

This paper investigates the application of value-function-based reinforcement learning to a smart energy control system, specifically the task of controlling an HVAC system to minimize energy while satisfying residents’ comfort requirements. In theory, value-function-based reinforcement learning methods can solve control problems such as this one optimally. However, since choosing an appropriat...

In order to overcome the limitations of the standard first or-der model of traffic flow (LWR model), various second ordermodels involving relaxation and/or anticipation terms wereintroduced in the literature. These models have the particu-larity to possess an equilibrium which can be unstable if cer-tain so-called subcharacteristic conditions are not satisfied.It can...

Linewidth roughness (LWR) remains a difficult challenge for improvement in resist materials. We intend to review work that focused on the impact of key components LWR by analyzing unbiased power spectral density (PSD) curves. studied systematic changes ArF formulations and correlated these overall PSD In this manner, we could extract 3σ values correlation length low/high-frequency components. a...

Understanding the impacts of environmental factors on spatial–temporal and large-scale rodent distribution is important for damage prevention. Investigating rat hole density (RHD) one most effective methods to obtain intensity damage. However, previous field surveys or UAV-based remote sensing can only evaluate small-scale RHD its influencing factors. these studies did not consider temporal spa...

The performance of many traffic control strategies depends on how much the traffic flow models have been accurately calibrated. One of the most applicable traffic flow model in traffic control and management is LWR or METANET model. Practically, key parameters in LWR model, including free flow speed and critical density, are parameterized using flow and speed measurements gathered by inductive ...