Multi-Crop Irrigation Need Classification Based on Machine Learning with an Indonesian-Language GenAI-UX Recommendation Layer
构建融合可解释机器学习与印尼语GenAI推荐层的智能灌溉决策支持系统。
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水稻 决策支持 机器学习
同时包含 水稻、决策支持、机器学习 的农业资讯，共 6 条。
Effects of within-season temporal aggregation of weather variables on performance and interpretability in rice yield machine learning models
评估生长季内天气变量时间聚合粒度对水稻产量机器学习模型预测与可解释性的影响。
A Privacy-Preserving Federated Learning Framework for Paddy Leaf Disease Detection Using an Enhanced Pretrained Novel EfficientNet-Lite4 Model
提出联邦学习结合改进EfficientNet-Lite4的水稻叶片病害检测框架，兼顾隐私与精度。
Afyon Kocatepe University Journal of Sciences and Engineering·10月6日 · 周二61 分 论文农业AI与大模型农业人工智能与决策模型阅读 1
Exploratory Explainable Machine Learning for Crop-Yield Interpretation: A Comparative Analysis of XGBoost, LightGBM, and CatBoost
比较XGBoost、LightGBM和CatBoost在作物产量可解释建模中的表现，强调评估协议与数
Hybrid Rule-Based and Machine Learning Decision-Support Framework for Smart Paddy Farming
提出规则与机器学习混合的水稻决策支持框架，提升决策精度并节水增产。
Spatial optimization of water-saving irrigation in Chinese rice paddies: Balancing yield, greenhouse gases, and cost using NSGA-II
构建空间优化框架，为中国稻田节水灌溉推广寻找兼顾产量、温室气体与成本的路径。