Attention LSTM-based animal husbandry index prediction method and prediction system

The invention discloses a livestock index prediction method based on attention LSTM. The livestock index prediction method comprises the following steps: collecting historical data of each index generated in a livestock feeding process; judging whether missing values exist in the historical data or not, and classifying the historical data into a first complete data set and a missing data set; dividing and preprocessing the missing data set according to the proportion of missing values in the missing data set to obtain a second complete data set and a corrected data set; performing missing value filling on the corrected data set by using a data similarity filling method to obtain a third complete data set; and based on a pre-established LSTM attention neural network model, inputting the first complete data set, the second complete data set and the third complete data set into the model for calculation, and outputting a prediction result of each index. According to the method, the problem that the traditional L