基于物理信息神经网络的智能温室控制系统研究  

Research on intelligent greenhouse control system based on physical information neural network

作　　者：林悦 刘志东[1] 胡宇博 Lin Yue;Liu Zhidong;Hu Yubo(Jilin Agricultural Science and Technology University,Jilin 132101,China)

机构地区：[1]吉林农业科技学院,吉林吉林132101

出　　处：《无线互联科技》2023年第21期75-77,共3页Wireless Internet Technology

基　　金：吉林省大学生创新创业训练计划项目,项目编号:S202311439084。

摘　　要：智能温室控制系统是一种利用现代技术和自动化手段来监测、管理和调控温室环境的系统,以实现对温度、湿度、光照、二氧化碳浓度等关键环境参数的精确控制。文章在传统智能温室控制系统上加入基于物理信息神经网络(PINN)的智能温室控制系统,以提高温室环境管理的效率和精确性。PINN将物理方程融入神经网络,用物理学的规律和性质来增强神经网络的性能、稳定性或泛化能力,实现环境参数的精确预测和智能控制。文章重点研究了PINN的数据采集与预处理、神经网络训练与优化以及智能控制策略的实施,为现代温室农业提供了新思路,具有推动农业技术升级和可持续发展的重要意义。The intelligent greenhouse control system is a system that utilizes modern technology and automation methods to monitor,manage,and regulate the greenhouse environment,in order to achieve precise control of key environmental parameters such as temperature,humidity,light,and carbon dioxide concentration.The article adds a physical information neural network(PINN)based intelligent greenhouse control system to the traditional intelligent greenhouse control system to improve the efficiency and accuracy of greenhouse environmental management.PINN integrates physical equations into neural networks,using the laws and properties of physics to enhance the performance,stability,or generalization ability of neural networks.Realize accurate prediction and intelligent control of environmental parameters.The article focuses on the data collection and preprocessing,neural network training and optimization,and implementation of intelligent control strategies of PINN,providing new ideas for modern greenhouse agriculture and of great significance in promoting agricultural technology upgrading and sustainable development.

关 键 词：物理信息神经网络 智能温室控制 温室建模 神经网络 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]