Authors

Abstract

This paper evaluates linear regression analysis, BP neural network, and a random forest prediction model for the prediction of jujube water demand. The results highlight that the R2 of the random forest is 0.941 and the residual distribution is the most stable. Hence, the random forest is more suitable for prediction, and therefore, an intelligent irrigation system is established employing random forest, where the cloud server is the upper computer and a Raspberry Pi is the lower computer, and at the same time, a PC and a mobile interface was built to present various information about the developed irrigation system.

Abstract in Chinese

本文搭建线性回归分析、BP神经网络与随机森林预测模型预测枣树需水量，结果表明随机森林的R2为0.941且残差分布最稳定，随机森林更适合用于预测。利用随机森林建立一套智能灌溉系统，使用云服务器作为上位机，树莓派作为下位机，同时搭建PC端与移动端操作页面。