营造有利作物生长的光环境是设施园艺发展亟待解决的重要问题，其优化调控的难点在于需考虑作物生理与外部环境等多因子关联的影响，拟基于智能控制理论进行设施园艺光环境多因子耦合智能调控模型与方法研究。分析影响作物光合速率的主要因素，设计多阶段多因子嵌套试验获取多维大样本数据，探寻基于遗传神经网络的多因子耦合作物光合速率建模方法，以设施番茄为对象构建光合速率模型实例；以光合速率最优为目标，研究多因子约束条件下基于遗传蚁群的光合速率寻优算法，进而建立基于BP神经网络的光环境调控目标值模型；研究多因子动态变化条件下光环境参数动态定量调控算法与闭环调控机制，提出基于多传感器融合的分阶段设施光环境智能调控方法，优化模型与方法验证平台，以设施番茄为对象开展验证与完善。研究成果对阐明多因子关联影响下的光环境调控原理具有重要意义，为提高光环境调控效率，推动现代设施园艺快速发展奠定基础。

Creating a favorable light environment for crop growth is an important issue in facility horticulture development. The correlation effluences between crop biological condition and multiple external environment factors are the keys in optimal regulation. In this project, based on intelligent control theory, a multi-factor coupling regulation model and method for facility horticulture light environment adjustment are adopted. First, main affecting factors of crop photosynthetic rate are analyzed, and a multistage and multidimensional large-scale sample data is obtained through nested tests. The multi-factor coupling crop photosynthetic rate modeling method based on genetic neural network are implemented, taking the photosynthetic rate model in facility tomato planting process as the research example. In order to get the optimal photosynthetic rate, the photosynthetic rate optimization algorithm under multi-factor constraints are also studied based on genetic ant colony algorithm. According to the BP neural network, the light environment control factors model are established. The quantitative control algorithm and closed-loop control mechanism of light environment parameters are researched under dynamic multi-factor environment. Finally, based on multi-sensor fusion, an intelligent regulation method for facility horticulture light environment is proposed. The verification and perfection of the models and methods are validated through facility tomato planting process. The research results can be of important significance to understand the multi-factor coupling light environment regulation principle and method, and provide theoretical foundation for improving light environment regulation efficiency and the rapid development of modern facility horticulture.