BP神经网络在TiO_2太阳能电池天然染料敏化剂研究中的应用  

Application of BP neural network in study of TiO_2 solar cell sensitizer of natural dyes

作　　者：李春梅[1] 王刚[1] 杨桂军[1] 韦浩民[1] 

机构地区：[1]青海大学现代教育技术中心,青海西宁810016

出　　处：《实验技术与管理》2015年第3期50-52,56,共4页Experimental Technology and Management

基　　金：青海省科技能力建设计划项目(2011-H-802)

摘　　要：介绍了BP神经网络和燃料敏化太阳能电池的原理,着重阐述了在原特殊植物中提取的色素作为敏化剂原料的实验中结合BP神经网络将实验数据进行分析的过程。在填充因子FF不变的前提下,以短路电流、开路电压作为神经网络的输入节点,对应的光电转换效率作为神经网络输出为例,介绍了神经网络的设计、训练和测试的过程,证明了BP神经网络在燃料敏化剂制作过程中的应用是可行的。This article introduces the principle of BP neural network and dye-sensitized solar cell,and elaborates on the extraction of pigment in Qinghai plateau special plants as sensitizer in the experiment.The experimental data are analyzed in combination with the BP neural network.On the premise of the fill factor FF invariant,the short-circuit current,and open circuit voltage as the input nodes of the network,this article describes that the photoelectric conversion efficiency corresponding to the output of neural network is the neural network as an example,and introduces the process of design,training and testing of neural network.The results show that the application of BP neural network in fuel sensitizer in the production process is feasible.

关 键 词：BP神经网络 短路电流 开路电压 光电转换效率 

分 类 号：TB381[一般工业技术—材料科学与工程]