茶树生长过程监控数据集

1.数据采集：通过采集茶树植株株高、叶片长势等生长指标数据；2. 预处理：采用人工统计方式实现数据标准化；3. 核心算法：运用 LSTM 时序模型预测生长趋势，通过随机森林算法分析环境因子与生长的关联性，结合 YOLO 目标检测识别病虫害早期特征，保障数据可靠性与分析精准度。

1. Data Collection: Collect growth indicator data such as plant height and leaf growth status of tea plants; 2. Preprocessing: Implement data standardization through manual statistical methods; 3. Core Algorithms: Apply the LSTM time series model to predict growth trends, use the Random Forest algorithm to analyze the correlation between environmental factors and tea plant growth, and combine YOLO object detection to identify early characteristics of pests and diseases, so as to ensure data reliability and analysis accuracy.