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Frontiers in Genetics-Benchmarking of Feed-Forward Neural Network Models For Genomic Prediction of Quantitative Traits in Pigs by zhenshuangt199474 is a document available to read on EtoBox.

What is Frontiers in Genetics-Benchmarking of Feed-Forward Neural Network Models For Genomic Prediction of Quantitative Traits in Pigs about?

This research evaluates the performance of feed-forward neural network (FFNN) models for genomic prediction of quantitative traits in pigs, comparing them with traditional linear methods. The study finds that FFNN models consistently underperform compared to linear methods, with the best predictive accuracy achieved by a one-layer FFNN structure. Additionally, while GPUs enhance computational efficiency for FFNNs, the models remain more resource-intensive than conventional linear approaches.

Author

zhenshuangt199474

Language

EN