宁夏工程技术2024，Vol.23Issue(1)：65-72,8.
基于双向多层门控循环神经网络的奶牛乳脂率预测模型研究
Study on the Prediction Model of Milk Fat Rate of Dairy Cows Based on Bidirectional Multilayer Gated Recurrent Neural Network
摘要
Abstract
Through data prediction of the milk fat rate of cows and precise feature selection of environmental data using the random forest algorithm,the ecological factors that significantly impact the milk fat rate were determined.On this basis,a milk fat rate prediction model(RF-BiGRU)that combines random forests with bidirectional gated recurrent neural networks was proposed,and related experiments were conducted.The results show that the model can improve the accuracy and efficiency of prediction.关键词
奶牛生理预测模型/随机森林算法/双向多层门控循环神经网络模型Key words
physiological prediction model of cow/random forest algorithm/bidirectional multilayer gated recurrent neural network分类
信息技术与安全科学引用本文复制引用
朱孟宇,由楚川,赵军..基于双向多层门控循环神经网络的奶牛乳脂率预测模型研究[J].宁夏工程技术,2024,23(1):65-72,8.基金项目
宁夏自然科学基金项目(2020AAC03028) （2020AAC03028）
