Explainable Machine Learning Framework for Soil Moisture Stress Assessment and Irrigation Decision Support
构建可解释机器学习框架，预测次日土壤湿度并支持灌溉决策。
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#灌溉量预测
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没有这个标签，内容接近AIDspat: Introduction of a model framework to estimate spatio-temporal agricultural irrigation demands – A study area in Germany
提出AIDspat模型，结合土壤水平衡与灌溉调度，估算时空农业灌溉需求。
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Crop Simulation Model: A Digital Tool for Sustainable Water Management in Agriculture
综述作物模拟模型在估算作物需水与灌溉管理中的应用及改进方向。
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Hierarchical Conformal Risk Control for Artificial Intelligence Agriculture Irrigation Scheduling Under Unmodeled Infiltration: A Computer Safety-Guarantee Evaluation
提出分层保形风险控制，为未建模入渗下的灌溉调度提供安全保证。
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Smart water management in agriculture: convergence of sensors, imaging, AI, precision irrigation, and robotics systems
综述AI传感、成像、物联网精准灌溉、数字孪生与机器人集成用于作物水分管理。
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AquaCrop-derived surrogate model for crop yield response to monthly irrigation deficit
构建AquaCrop衍生的代理模型，快速映射月度灌溉亏缺与作物产量的非线性响应。
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Three-way debate – measurements, pedotransfer functions, and inverse modeling – input strategy for soil hydraulic parameters in wheat simulations
比较测量、传递函数和反演建模获取土壤水力参数对小麦模拟的影响。
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SMART IRRIGATION STRATEGY RECOMMENDED SYSTEM USING ML
提出基于ESP32传感与两阶段机器学习的智能灌溉推荐系统，预测土壤湿度并推荐灌溉动作。
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