基于信息融合的温室CO2调控量决策方
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-making on Greenhouse CO2 Control Quantity Based on Information Fusion
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    摘要:

    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,运用神经网络建立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2004~2006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。

    Abstract:

    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.

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张荣标,项美晶,李萍萍,白斌.基于信息融合的温室CO2调控量决策方[J].农业机械学报,2009,40(6):175-178.

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