Precision Agriculture Using AI for Crop Yield Prediction and Disease Detection: A Comprehensive Review of Machine Learning and Deep Learning Approaches for Sustainable, Data-Driven Farming
综述机器学习与深度学习在作物产量预测和叶片病害检测中的应用与挑战。
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Agri digital twin–driven intelligent computing framework for real-time crop yield forecasting and sustainable decision support
提出农业数字孪生框架，结合GRU与物联网实现实时产量预测与可持续决策支持。
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F.A.R.M. (Field Analysis Revenue Management): An IoT and ML Integrated Solution
提出F.A.R.M.系统，用IoT传感与机器学习实现作物推荐、价格预测和产量估算。
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Time Series Extrinsic Regression for Smart Agriculture: Field‐Level Crop Yield Prediction From Multisource Agricultural Time Series
将田块级作物产量预测建模为时间序列外回归，比较多源农业时间序列上的神经与非神经方法。
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MDPI Remote Sensing 18(18):3107 MODIS NDVI与机器学习作物产量预测比较研究
基于印度州级MODIS NDVI与机器学习比较作物产量预测，随机森林优于梯度提升。
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An Optimized Temporal Attention-based Deep Learning Framwork for Accurate Crop Yield Prediction from Multi-source Agricultural Data
提出TA-ABC-Bi-LSTM模型，用多源农业数据精准预测水稻产量。
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APPLICATION OF ARTIFICIAL INTELLIGENCE IN SOIL FERTILITY ASSESSMENT AND CROP YIELD PREDICTION IN SOUTHWEST NIGERIA: A STATISTICAL APPROACH
研究AI在尼日利亚西南部土壤肥力评估和作物产量预测中的应用，发现随机森林模型表现最佳。
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