Modeling. The Secretary will commence monthly modeling of Minimum Probable, Maximum Probable and Most Probable hydrology for the subsequent 24-month period until the Minimum Probable 24-Month Study projects that Lake Xxxxxx will consistently remain above the Target Elevation for a 24-month period. Reclamation will report such modeling results to the Upper Division States and the Commission during monthly calls, see Section II.A.4.a.
Modeling. Seller shall provide all of the data to allow the modeling of the generators, transformers and control systems within the Facility. Seller shall validate or update the modeling data as requested by Company.
Modeling. With respect to the Modeling, Critical shall retain ownership of the analytical process. CRC shall retain ownership of all data provided for the Modeling and all results of the application of the analytical process to the data. Critical shall not, without prior written permission of CRC, transfer, disclose or otherwise provide the data or results of the Modeling to any person outside of Critical. Critical agrees that it shall thoroughly safeguard the confidentiality of the data in the Modeling results, and in no event shall it be to a lesser extent than Critical safeguards its own proprietary information. Critical agrees that access to such data and the Modeling results will be given only to employees of Critical who require access in the course of Critical's business, and such employees will be informed of the confidential nature thereof and shall be required to observe provisions of confidence as set forth herein.
Modeling a. Resource Provider shall provide PREPA with a PSS/E model for the Facility for approval no later than the Agreement Date.
Modeling. The CAISO and Bonneville will update, improve, and maintain the modeling of generation and transmission topology to adequately reflect the expected real-time system impacts on Bonneville’s transmission system and the EIM Area based on the data and information shared pursuant to this Agreement and data and information shared through NERC and WECC reliability standards or other regulations, Peak Reliability’s Universal Data Sharing Agreement or its successor, other applicable Peak Reliability policies or methodologies, and other agreements between the Parties.
Modeling. Disease mapping and small area estimation are related modeling techniques that have many applications in public health (Xxxxxxx et al., 2010). These overlapping families of methods share two competing main goals. One involves estimating local values precisely for each area; the other is having “small” areas to provide local details within broad trends. However, these main goals of disease mapping are in direct contradiction with each other. Usually, a small area comes with a small sample size, which means that precision of results is decreased (Xxxxxxx et al., 2010) and aggregating small areas to increase sample sizes sacrifices local detail. Small area methods seek to meet both goals by providing estimators that represent a weighted compromise between local and global data to improve local precision without entirely giving up local information. Disease mapping methods extend small area estimation by assuming positive spatial correlation between nearby observations, allowing local estimates to borrow more information from nearby areas rather than borrow information equally across all areas. The spatial setting provides a smoothing of extreme values and an easy way to visualize geographic patterns of disease. As one example, popular conditional autoregressive (CAR) models allow us to borrow information from neighborhood areas, and provide more accurate local estimates than one would obtain ignoring neighboring values. In spatial data, the CAR models often are implemented by Markov chain Monte Carlo (MCMC) algorithms (Xxxxxxx et al., 2010) and, more recently, Integrated Nested Laplace Approximation (INLA) (Blanogiardo & Cameletti, 2015). Usually, MCMC is the first choice when we are looking for posterior sampling for Bayesian models such as the CAR model. However, the biggest challenge is obtaining convergence in posterior samples in a reasonable amount of time (Xxxxxxx et al., 2015). MCMC approaches can be very time consuming and put a heavy burden on CPU for simulation. Unlike MCMC, INLA is a new algorithm based on numerical rather than Monte Carlo integration to perform Bayesian analysis and calculate approximations of posterior marginal directly (Rue et al., 2009), allowing much quicker computation than MCMC. INLA has been widely used to analyze lattice data with CAR model, and examples are easy to find (Bivand et al., 2015).
Modeling. ENGINEER shall investigate possible improvements to the overall performance of the channel including reshaping the channel and/or resizing the downstream bike path box culvert crossing at the confluence of the tributary and East Fork Xxxxxxxx Creek. If the modeling demonstrates a real benefit from installing a box culvert or additional cell, ENGINEER shall provide plans for the structure.
Modeling. 6.1 Develop GIS tools for visualizing and analyzing source tracking and sanitary survey investigation.
Modeling. As described in clause 13, PC Medics, Inc retains all copyrights and may use at its sole discretion any photograph or art work for portfolio, advertising purposes or similar commercial purposes. Should PC Medics, Inc use a photograph or Art work in which any person(s) is identifiable for such purposes then person(s) waive any claim to compensation for modeling or any similar claims.
