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可解释的AI驱动的解释,使用物联网传感的智能温室中番茄果实扩张的环境驱动因素
Yunlong Li1, Tianle Wang2, Haoyuan Zu3
1Intelligent Manufacturing College, Tianjin Sino-German University of Applied Sciences, Tianjin, 300350, China.
Scientific reports
|November 19, 2025
概括
通过了解微气候影响,智能温室番茄的生长得到了优化. 土壤温度,光线和电导率是关键驱动因素,使精准农业的洞察力成为可能.
科学领域:
- 农业科学 农业科学
- 环境监测 环境监测
- 人工智能的人工智能
背景情况:
- 番茄果实扩张显著影响作物产量和市场价值.
- 了解微气候对水果发育的影响对于智能温室管理至关重要.
- 对番茄果实扩张环境驱动因素的定量分析仍然有限.
研究的目的:
- 开发一个物联网驱动的传感框架,用于监测影响番茄果扩张的环境因素.
- 利用可解释的人工智能 (XAI) 来解释微气候和水果生长之间的关系.
- 为智能农业中精密气候和成品管理提供可操作的见解.
主要方法:
- 实施了强大的物联网传感系统,以收集空气/土壤温度,湿度,光强度,CO2,土壤水分和土壤电导率的实时数据.
- 采用随机森林回归模型与夏普利添加式拓展 (SHAP) 和部分依赖图 (PDP) 集成用于数据分析和解释.
- 验证了开发的物联网-XAI框架的预测准确性和可解释性.
主要成果:
- 确定了土壤温度 (~21.8°C),光强度和土壤电导率作为影响番茄果扩张的主要驱动因素.
- 对这些关键环境因素观察到不同的值行为.
- 在R2 = 0.82和平均平方误差 (MSE) = 0.0046.6的情况下实现了高的预测性能.
结论:
- 拟议的IoT-XAI框架有效地将复杂的传感器数据转化为可理解的洞察力,以优化番茄种植.
- 可解释的机器学习为可持续的智能农业中精确的气候和生产策略提供了强大的工具.
- 这种方法支持数据驱动的决策,以提高水果的大小,可销售性和整体产量.
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