自组织人工神经网络在氟化物非晶态形成的判别条件中的应用
AN APPLICATION OF T.KOHONEN SELF ORGANIZATION ARTIFICIAL NEURAL NETWORK TO THE ESTIMATION OF THE FORMATION CONDITION FOR AMORPHOUS PHASE OF TRINAL FLUORIDE
作者单位
蔡煜东  
许伟杰  
陈念贻  
摘要: 本文运用T. Kohonen自组织人工神经网络,利用化学健参数法,研究了三元系氟化物非晶态形成的判别条件,建立了相应的计算法判别智能软件。识别成功率较高。结果表明,该方法性能良好,可望成为研究化合物非晶态形成条件的有效的辅助手段。
关键词: 氟化物  非晶态形成条件  人工神经网络  T. Kohonen自组织模型
基金项目: 
Abstract: In this paper, T. Kohoncn self-organization artificial neural Network was applied to the estimation of the formation condition for amorphous phase of trinal fluoride'by using the parameters method of chemical bonds, and the intelligential sorfware for estimation was established. The successful rate is high. The results showed that the performance of the neural network was good, arid therefore it might be referred as an effective assistant technique for formahon condition for amorphous phase of compounds.
Keywords: fluoride  condition for amorphous formation  artifical neural network  T. Kohonen self-organization model
投稿时间:1993-03-20 
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蔡煜东,许伟杰,陈念贻.自组织人工神经网络在氟化物非晶态形成的判别条件中的应用[J].无机化学学报,1994,10(2):151-154.
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