Comparison between the Arrhenius model and the radial basis function neural network (RBFNN) model for predicting quality changes of frozen shrimp (Solenocera melantho)

Zihan XuBeijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, ChinaView further author information

Xiaochang LiuBeijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, ChinaView further author information

Huiyi WangBeijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, ChinaView further author information

Hui HongBeijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, ChinaView further author information

Yongkang LuoBeijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, China;Beijing Higher Institution Engineering Research Center of Animal Product, China Agricultural University, Beijing, ChinaCorrespondence[email protected] [email protected]
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Comparison between the Arrhenius model and the radial basis function neural network (RBFNN) model for predicting quality changes of frozen shrimp (Solenocera melantho)

Table 1. Estimation of the reaction orders in Arrhenius models of quality indicators by r².

Table 2. MSE of RBFNN with varying quantities of hidden neurons.

Table 3. Measured values and predictive values of the Arrhenius model and the RBFNN model for shrimp stored at –28°C.

Table 4. r² and MSE of the Arrhenius model and the RBFNN model between the predicted values and the measured values.

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Comparison between the Arrhenius model and the radial basis function neural network (RBFNN) model for predicting quality changes of frozen shrimp (Solenocera melantho)

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Table 1. Estimation of the reaction orders in Arrhenius models of quality indicators by r2.

Table 2. MSE of RBFNN with varying quantities of hidden neurons.

Table 3. Measured values and predictive values of the Arrhenius model and the RBFNN model for shrimp stored at –28°C.

Table 4. r2 and MSE of the Arrhenius model and the RBFNN model between the predicted values and the measured values.

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Table 1. Estimation of the reaction orders in Arrhenius models of quality indicators by r².

Table 4. r² and MSE of the Arrhenius model and the RBFNN model between the predicted values and the measured values.