用注意力模型预测奶牛产奶寿命，准确率达83%
Prediction of Herd Life in Dairy Cows Using Multi-Head Attention Transformers
- 基于多头注意力机制分析奶牛全生命周期数据
- 在7个农场1.9万头牛上实现83%的寿命预测决定系数
- 适合需要提升奶牛养殖效率的牧场管理者
奶农需基于客观评估决定保留或淘汰奶牛。为此，需识别更具韧性的个体，使其能更好地适应农场环境并完成更多泌乳期。该决策过程复杂，对环境与经济均有重大影响。本研究开发了一种基于AI的模型，利用从出生起记录的历史多变量时间序列数据预测奶牛在群体中的存活时间。通过采用先进的多头注意力变换器技术，分析了来自澳大利亚7个农场、约78万条记录、涉及1.9万头独特奶牛的数据。结果表明，该模型在所研究农场中对群体寿命的预测决定系数达到83%，展现出在奶牛群管理中的实际应用潜力。
原文摘要 · Abstract (English)
Dairy farmers should decide to keep or cull a cow based on an objective assessment of her likely performance in the herd. For this purpose, farmers need to identify more resilient cows, which can cope better with farm conditions and complete more lactations. This decision-making process is inherently complex, with significant environmental and economic implications. In this study, we develop an AI-driven model to predict cow longevity using historical multivariate time-series data recorded from birth. Leveraging advanced AI techniques, specifically Multi-Head Attention Transformers, we analysed approximately 780,000 records from 19,000 unique cows across 7 farms in Australia. The results demonstrate that our model achieves an overall determination coefficient of 83% in predicting herd life across the studied farms, highlighting its potential for practical application in dairy herd management.
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