摘要
温室易受各种环境因素影响,从而可能导致在室内不同点的温度、湿度、光照度值不均匀,为了获得温度的准确值,将PSO算法的全局优化能力和CMAC网络局部逼近、学习速度快的能力相结合,优化CMAC网络的权值,提出了一种基于PSO的CMAC网络数据融合算法,使得最终得到的数据更加准确、有效,为温室管理提供了精确的信息。仿真结果表明,采用该方法提高了温室各监测量采集的准确性、有效地避免了由于传感器失效引起的误差,能够获得温室准确有效的信息,提高温室控制的有效性与准确性。
Greenhouse is very easy to be impacted by various environmental factors,which may lead to the unevenness of temperature,humidity and illumination value in different points of the indoor environment.In order to obtain the accurate value of the temperature,the global optimization ability of the PSO algorithm and the local approximation and fast learning ability of CMAC is combined,and the weights of CMAC network are optimized.At the same time,a CMAC network data fusion algorithm based on PSO is proposed,which can make the final data more accurate and efficient,and provides accurate information for greenhouse management.The simulation results show that this method can increase the accuracy of each collected data from the greenhouse,avoid the errors caused by sensor failure effectively,obtain accurate and effective information of greenhouse,and improve the effectiveness and accuracy of the greenhouse control.
出处
《黑龙江水专学报》
2010年第2期109-112,共4页
Journal of Heilongjiang Hydraulic Engineering College
