Prediction of Microwave-Assisted Extraction to Determine Zinc in Fish Muscles Using Support Vector Machine and Artificial Neural Network

Zhi-Han Xu ； Jin-Kun Yao ； Yi-Meng Wang

《Advance Journal of Food Science and Technology》 10卷9期 (2016/03) Pp. 680-686

並列摘要

In this study, the support vector machine and the artificial neural network are adopted in the microwave-assisted extraction method to determine the amount of zinc in fish muscle samples. In the experiment, the irradiation power, irradiation time, nitric acid concentration and temperature are set as independent variables while the amount of zinc was considered as a function of the four factors. By comparing the RMS error and the training time of the support vector machine and the artificial neural network, the most suitable predicting model can be determined. The results show that the MLFN model with 7 nodes performed the best with the lowest RMS error of 1.21 and 100% prediction accuracy.

並列關鍵字

Artificial neural networks ； microwave-assisted extraction ； predicting accuracy ； support vector machine