Weight Loss Prediction Model for Pig Carcass Based on a Genetic Algorithm Back-Propagation Neural Network

摘要

Because the weight loss ofa pig carcass in the spray-chilling process is easily affected by the sprayingfrequency and duration, a prediction model for weight loss based on a genetic algorithm (GA) back-propagation (BP) neural network IS proposed in this article. With three-way crossbred pig carcasses selected as the test materials, the duration and time interval of high-frequency spraying, the duration and time interval of low-frequency spraying, and the duration of a single fo the network model. Theweight and threshold of the network were then optimized by the GA. The prediction model for pig carcass weight loss established by the GA BP neural network yielded a correlation coefficient of R- 0.99747 between the network output value of the test samples and the target value. Weight loss prediction by the model is feasible and allows better expression of the nonlinear relationship between weight loss and the main controlling factors. The results can be a reference for chilled meat production.