Data on Machine Learning - Artificial Neural Networks Reported by H. Zheng and Co-Researchers

摘要

"Artificial neural network (ANN) and partial least-squares regression (PLSR) models were developed tonpredict the changes of anthocyanin (AC), ascorbic acid (AA), total phenols (TP), total flavonoid (TF), andnDPPH radical scavenging activity (SA) in bayberry juice during storage based on fractal analysis (FA)nand red, green, and blue (RGB) intensity values. The results show the root mean squared error (RMSE)nof ANN-FA decreased 2.44 and 12.45% for AC (RMSE = 18.673 mg/100 mL, R-2 = 0.939) and AAn(RMSE = 8.694 mg/100 mL, R-2 = 0.935) compared with PLSR-RGB, respectively," investigators innJinhua, People's Republic of China report.