蚕豆在成熟期时种植密度预测数据

蚕豆在成熟期的种植密度直接影响作物的生长条件、病虫害发生率以及最终产量。合理预测蚕豆在成熟期时种植密度，从而能够在分蘖期适时调整种植密度对于提高单位面积产量、优化资源使用及减少病虫害具有重要意义。该模型有效的解决了蚕豆生长状况与种植密度之间的预测关系。通过调查采集蚕豆在分蘖期的相关数据，并使用多元线性回归模型预测蚕豆种植密度，该模型的输入量依次为抗病评分、发病率(%)、叶片颜色指数(SPAD)、株高(cm)、病虫害类型、生育期(天)、分蘖数，多元线性回归算法通过分析这些输入量与蚕豆种植密度之间的线性关系，确定每个输入量相关的权重系数，使用深度学习框架构建模，模型通过最小二乘法等技术，根据输入的数据从而计算出蚕豆种植密度预测值。在模型训练过程中，算法会利用最终在成熟期测得的蚕豆种植密度实际值进行优化，调整上述的权重系数以最小化预测误差，因此上述每个权重系数在成熟期后，算法会根据实际值与预测值进行比较后再进行动态调整的。

Planting density of faba beans at maturity directly affects crop growth conditions, pest and disease incidence, and final yield. It is of great significance to reasonably predict the planting density of faba beans at maturity, so as to timely adjust the planting density during the tillering stage, thereby increasing yield per unit area, optimizing resource utilization, and reducing pests and diseases. This model effectively establishes the predictive correlation between the growth status of faba beans and their planting density.

Relevant data of faba beans during the tillering stage is collected via field surveys, and a multiple linear regression model is employed to predict the planting density of faba beans. The input variables of this model are, in sequence: disease resistance score, incidence rate (%), leaf color index (SPAD), plant height (cm), pest and disease type, growth period (days), and tiller number. The multiple linear regression algorithm determines the weight coefficients associated with each input variable by analyzing the linear correlation between these inputs and the planting density of faba beans. The model is developed using a deep learning framework, and computes the predicted planting density of faba beans from the input data through techniques such as the least squares method.

During the model training phase, the algorithm utilizes the actual planting density values of faba beans measured at final maturity for optimization, adjusting the aforementioned weight coefficients to minimize prediction errors. Consequently, each of the above weight coefficients will be dynamically adjusted after the maturity stage by comparing the actual measured values with the predicted values.

搜集汇总

数据集介绍

特点

该数据集专注于蚕豆成熟期的种植密度预测，包含4089条记录，每月更新。通过多元线性回归模型分析多个生长指标与种植密度的关系，旨在优化蚕豆的生长条件和提高产量。