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学科主题: 物理有机化学
题名: NONLINEAR FITTING BY USING A NEURAL NET ALGORITHM
其他题名: NONLINEAR FITTING BY USING A NEURAL NET ALGORITHM
作者: Li Z(李正) ; CHENG ZHAONIAN ; XU LI ; LI TONGHUA
通讯作者: 李正
刊名: Anal. Chem.
发表日期: 1993-01-01
卷: 65, 期:4, 页:393-396
收录类别: SCI
部门归属: 中国科学院上海有机化学研究所; 中国科学院上海冶金研究所; 同济大学
英文摘要: A novel transfer function which is very suitable for normalized data set and a modified conjugate gradient algorithm which converges much faster we proposed to improve the performance of the neural network training procedure. The overfitting problem is discussed in detail. The optimal fitting model can be obtained by adjusting the number of hidden nodes. A data set of furnace lining durability was used as an example to demonstrate the method. The predictive results were better then that of principal component regression and partial least square regression.
语种: 英语
相关网址: 查看原文
内容类型: 期刊论文
URI标识: http://ir.sioc.ac.cn/handle/331003/27291
Appears in Collections:上海有机化学研究所_期刊论文

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Recommended Citation:
Li Z,CHENG ZHAONIAN,XU LI,et al. NONLINEAR FITTING BY USING A NEURAL NET ALGORITHM[J]. Anal. Chem.,1993,65(4):393-396.
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