Prediction of Annual Daylighting Performance Using Inverse Models

Performance Prediction in Cycling Using Antagonistic Models

Two antagonistic models are used to model the training-performance relationship during an eight week cycling training, with a prediction of the performances in the last week of training. Results indicated different qualities of the model fits for the test data for both models. Mean differences between predicted and real performances were 2.39% for the Fitness-Fatigue-Model and 4.43% for the Per...

GPU performance prediction using parametrized models

Prediction Models for Annual U.S. Hurricane Counts

The authors build on their efforts to understand and predict coastal hurricane activity by developing statistical seasonal forecast models that can be used operationally. The modeling strategy uses May–June averaged values representing the North Atlantic Oscillation (NAO), the Southern Oscillation index (SOI), and the Atlantic multidecadal oscillation to predict the probabilities of observing U...

Prediction of Vapor-Liquid Equilibria Using CEOS /GE Models

The present study investigates the use of different GE mixing rules in cubic equations of state for prediction of phase behavior of multicomponent hydrocarbon systems. To predict VLE data in multicomponent symmetric and asymmetric mixtures such as systems that contain light gases (nitrogen, carbon dioxide, etc.) and heavy hydrocarbons, the SRK equation of state has been combined with excess Gib...

Classification Performance Prediction Using Parametric Scattering Feature Models

We consider a method for estimating classification performance of a model-based synthetic aperture radar (SAR) automatic target recognition system. Target classification is performed by comparing an unordered feature set extracted from a measured SAR image chip with an unordered feature set predicted from a hypothesized target class and pose. A Bayes likelihood metric that incorporates uncertai...