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Exploring the Potential of Symbolic Regression in Precision Livestock Farming

Paper recorded by Signals 4 on 2026-10-29 in cs.LG. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-29 on arXiv · recorded by Signals 4 on 2026-10-30

Category: cs.LG · 机器学习 · first seen 2026-10-30

Abstract

The ability to predict farrowing time in pigs is crucial for optimal farm management and ensuring piglet survival. This study investigates the potential of explainable artificial intelligence for precision livestock farming, focusing on acceleration sensor data from sows around the time of farrowing. Accurately predicting farrowing allows farmers to balance both, piglet safety by avoiding piglet c

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#136 most recent of 737 cs.LG papers we have recorded · ↑ newer: Surprise Alone Learns Lies: Evidence-Gated Continual Learning for LLMs · ↓ older: When Should We Intervene at Test Time?
Cite this page: Exploring the Potential of Symbolic Regression in Precision Livestock Farming: the #136 most recent of 737 cs.LG papers we have recorded (as of 2026-10-29). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/exploring-the-potential-of-symbolic-regression-in-precision-livestock-farming.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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