Protein Secondary Structure Prediction based on BP Neural Network and Quasi-Newton Algorithm

摘要

Based on neural network, an improvement scheme that iterative matrix replace secondary derivative has been developed by introduced quasi-Newton algorithm. Profile code based on probability has been used and comparison of window width and learning training has been completed. The experiment results indicate that the prediction for secondary structures of protein obtain a very good effect based on neural network and quasi-Newton algorithm.