Sentence examples for model selection strategy from inspiring English sources

In order to follow the time-varying characteristics of wind generation, multiple time dependent base forecasting models and an online model selection strategy are established, thus adaptively selecting the most probable base model for each prediction.

We describe an alternative model selection strategy that identifies which hypothesis, selected from an a priori-compiled set of hypotheses, explains the most variation in the outcome.

The new model selection strategy is more reliable than known model selection criteria.

In addition, a new model selection strategy based on well-known model selection criteria is proposed.

Verification results show that the third method using the model selection strategy is the most efficient one for nonlinear structural parameter identification.

We evaluate the performance of the RELM using batch and recursive learning rules, and also introduce a model selection strategy based on Particle Swarm Optimization (PSO) to find an optimal architecture for datasets contaminated with non-Gaussian noise and outliers.

These approaches rely on different model selection strategies and use different criteria to evaluate model fit relative to its complexity.

Therefore, an interaction with the image data and with image priors is necessary to drive model selection strategies.

The proposed model selection strategies are outlined and a Monte Carlo assessment of their finite sample properties is reported.

Prior to phylogenetic analyses, model selections with different model selection strategies (AIC, AICc, BIC) were performed with ProtTest with all single-gene and multi-gene alignment files.

This strategy provided a grand total of 336 composite datasets for evaluating the performance of the different model selection strategies.