玉米在生长期时植株高度预测数据

可以用于玉米植株高度预测，输入为土壤类型、肥料使用、灌溉方式、玉米茎粗(cm)、叶面积指数、根系长度(cm)、玉米产量（亩产量）、根系主要分布范围(cm)、玉米根系数量、根茎长(cm)、叶绿素含量（mg/g）、叶片数量。输出为植株预测高度。该模型帮助解决了玉米植株预测高度和玉米状况的关系建模的问题。预测玉米植株高度对玉米的生长有着重要的影响，通过预测数据保证其健康生长，保证玉米的生长和品质，提高其生产效益。通过调查采集玉米数据，并使用传统算法和多元线性回归算法预测玉米植株高度。该模型的输入为土壤类型、肥料使用、灌溉方式、玉米茎粗(cm)、叶面积指数、根系长度(cm)、玉米产量（亩产量）、根系主要分布范围(cm)、玉米根系数量、根茎长(cm)、叶绿素含量（mg/g）、叶片数量。多元线性回归算法通过分析这些输入变量与玉米植株预测高度之间的线性关系，确定每个变量的权重系数。在模型训练过程中，算法会利用玉米植株实际高度进行优化，调整权重系数以最小化预测误差。模型通过最小二乘法等技术，根据输入的数据计算玉米植株预测高度，从而得出最终结果。通过这样的过程，模型能够将多个输入变量综合考虑，准确预测玉米植株高度，有98%以上的概率预测植与实际值相差在1.5%以内。

This dataset is applicable to maize plant height prediction. The input features include soil type, fertilizer application, irrigation method, maize stem diameter (cm), leaf area index, root length (cm), maize yield per mu, main root distribution range (cm), number of maize roots, rhizome length (cm), chlorophyll content (mg/g), and number of leaves, while the output is the predicted plant height.

This model addresses the problem of modeling the correlation between maize plant height prediction and maize growth status. Predicting maize plant height is critical for maize cultivation: it ensures healthy crop growth, guarantees grain yield and quality, and improves production efficiency.

Maize-related data was collected through field surveys, and both conventional algorithms and multiple linear regression algorithms were employed to predict maize plant height. The multiple linear regression algorithm analyzes the linear relationship between these input variables and the target predicted plant height, and determines the weight coefficient for each input feature. During model training, the algorithm uses the actual measured maize plant height for optimization, adjusting the weight coefficients to minimize prediction errors. The model calculates the predicted maize plant height based on input data using techniques such as the least squares method, to produce the final prediction result.

Through this workflow, the model comprehensively considers multiple input variables to achieve accurate maize plant height prediction, with a probability of over 98% that the difference between the predicted value and the actual measured value is within 1.5%.

搜集汇总

数据集介绍

特点

该数据集由杭州灵煜生物科技有限公司提供，包含4085条玉米生长期相关数据，每月更新。通过多元线性回归算法预测玉米植株高度，输入包括土壤类型、肥料使用等12个变量，预测准确率高达98%以上，误差在1.5%以内，适用于玉米生长状况建模和高度预测。