基于信息融合的温室CO_2调控量决策方法

Decision-making on Greenhouse CO_2 Control Quantity Based on Information Fusion

提出一种以利润最大化为目标的温室CO2调控量决策方法。以生菜为研究对象，运用神经网络建丑非线性的植物生长速率预测模型，采用多项式函数拟合得到植物市场价格规律模型，并考虑CO2施肥的成本，寻求最优CO2体积比的调控量。以生菜生长过程中的实验数据和20042006年凌家塘批发市场提供的生菜价格季节性变化规律为依据，结合实际情况建立预测模型并实现了多信息的融合，为温室测控系统CO2调控量的决策提供了依据。

In view of the factors affecting profit maximization, such as the relation between photosynthetic rate and CO2 concentration in greenhouse, the plant market price and the cost of CO2 enrichment, a decision-making method for CO2 control quantity was presented to achieve the profit maximization. Taking lettuce planting as an example, a non-linear model was set up for forecasting plant growth＇rate by neural network, and a market price model was established for forecasting plant market price by polynomial fitting function. In terms of the above two models and the cost of CO2 enrichment, the optimal set-point of CO2 concentration was found out. According to the experimental data of lettuce growth and the seasonal changes of market prices from 2004--2006 offered by Ling Jiatang wholesale market, prediction models were established and finally information fusion was achieved, which provided a theory for the decision-making of CO2 control quantity in greenhouse control system.