In this paper, we analyzed the deep neural network (DNN) model and proposed a DNN-based method to build the training model for professional farmers. This paper aims to construct the vocational farmer cultivation model and seek a better path for transforming farmers into new experienced farmers by analyzing each training body involved in the cultivation of vocational farmers and studying their respective problems and reasons. The conceptual and logical structures of the system database were designed, and MySQL was selected for database implementation to complete the information of professional farmers. The system network topology and logical architecture are created, and the functions of view, control, business logic and data access layers are divided. This paper combines the DNN with the vocational farmer training enhancement decision tree. The experimental results of this model are most intuitive and accurate. This paper reconstructs the neural network model using the global average pooling layer to better model the vocational farmer training model to replace the fully connected layer in the original convolutional neural network. At the same time, to make the network model produce a lower probability of overfitting, a dropout layer is added to the layer after the fully connected layer to improve the efficiency of the neural network further to enhance vocational farmer training. The experimental content of this paper provides a new research direction for the estimation of vocational farmer cultivation. The above modeling is used to improve the vocational farmer cultivation model and accelerate the process of vocational farmer cultivation.

在本文中，我们分析了深度神经网络（DNN）模型，并提出了一种基于 DNN 的方法来构建专业农民的培训模型。本文旨在通过对参与职业农民培养的各培训机构进行分析，研究各自存在的问题和原因，构建职业农民培养模式，寻求更好的农民向新经验农民转化的路径。设计了系统数据库的概念和逻辑结构，选择MySQL进行数据库实现，完成专业农户信息。创建系统网络拓扑和逻辑架构，划分视图层、控制层、业务逻辑层和数据访问层等功能。本文将 DNN 与职业农民培训增强决策树相结合。该模型的实验结果最为直观准确。本文使用全局平均池化层重构神经网络模型，以更好地建模职业农民培训模型，以取代原始卷积神经网络中的全连接层。同时，为了使网络模型产生较低的过拟合概率，在全连接层之后的层增加了一个dropout层，进一步提高神经网络的效率，加强职业农民培训。本文的实验内容为职业农民培育的估算提供了一个新的研究方向。上述模型用于完善职业农民培育模式，加快职业农民培育进程。