The Prediction of Cation Exchange Distribution Coefficients with Artificial Neural Network

Abstract

Abstract: The ion exchange distribution coefficients of cat ions having characteristie valence in main groups were predicted by using extented delta-bar-delta neural networks, The effect of structure of network, the learning Epochs and the size of learning set on predicted results was investigated.The suitable conditions are;input nodes 4; output node; 1; the learning epochs; 3000; the size of learning set;112.The RMS(root-mean-square error) is smaller than 7%under the suitable conditios.

Key words: Cation exchange, Distribution coefficient, Artificial neural networks

TrendMD:

LIU Man-Cang, ZHANG Hai-Xia, ZHANG Rui-Sheng, ZHANG Li-Hua, HU Zhi-De. The Prediction of Cation Exchange Distribution Coefficients with Artificial Neural Network[J]. Chem. J. Chinese Universities, 1996, 17(5): 698.

[1]	QUAN Yao, BI Erping. Adsorption Characteristics of Different Forms of Ofloxacin to Attapulgite^† [J]. Chem. J. Chinese Universities, 2017, 38(4): 622.
[2]	LIN Yifeng, HUANG Xuehong, ZHENG Rongxue, LIN Juan, DING Fuchuan, LING Qidan. Synthesis and Properties of Comb-shaped Sulfonated Poly(ether ether ketone) as Cation Exchange Membrane by RAFT^† [J]. Chem. J. Chinese Universities, 2014, 35(3): 633.
[3]	ZHANG Xiao-Meng¹, LI Jun^1, LIU Zheng-Ping^2, ZHANG Li-Xin¹. Cation Exchange Reaction of Poly(lithium acrylate) with 1-Butyl-3-methylimidazolium Bromide [J]. Chem. J. Chinese Universities, 2009, 30(3): 638.
[4]	QI Yu-Hua, ZHANG Qing-You, LUO Cao-Cao, WANG Jun, XU Lu. Application of Tree Structured Fingerprint to the Prediction of pK_a of Pyridine Derivatives [J]. Chem. J. Chinese Universities, 2004, 25(6): 1100.
[5]	ZHANG Qing-You, QI Yu-Hua, WANG Jun, LUO Cao-Cao, XU Lu. Applications of the Periphery of Projection in Studies of the Quantitative Structure-activity Relationship of Nitrobenzenes [J]. Chem. J. Chinese Universities, 2004, 25(4): 622.
[6]	SHEN Wen-Hao, XIE Yi-Min, LIU Huan-Bin . The Application of Artificial Neural Networks in Optical Quantitative Determination of Pulp Kappa Number [J]. Chem. J. Chinese Universities, 2000, 21(8): 1208.
[7]	HE Yang, XIE Yu-Bing, WANG Yong, LIU Qun, MA Xiao-Jun. Improved Mathematical Model of APA Microcapsules [J]. Chem. J. Chinese Universities, 2000, 21(2): 278.
[8]	YU Ke-Qi, DONG She-Ying, TANG Hong-Sheng, GAO Hong . Studies on Artificial Neural Networks Used in A.C.Oscillographic Chronopotentiometry [J]. Chem. J. Chinese Universities, 1999, 20(9): 1367.
[9]	NI Yong-Nian, LIU Chao . Kinetic Spectrophotomatric Determinations of Mixtures of Iron, Zinc and Copper Using Artificial Neural Networks [J]. Chem. J. Chinese Universities, 1999, 20(4): 529.
[10]	LIN Yong-Jing, ZHU Er-Yi, LI Quan-Long, YANG Peng-Yuan. Application of Artificial Neural Networks for Hydrocarbon Gas Mixture Analysis [J]. Chem. J. Chinese Universities, 1997, 18(6): 886.
[11]	ZHANG Rui-Sheng, YAN Ai-Xia, LIU Man-Cang, HU Zhi-De. The Classification of Acidic Dyes with Artificial Neural Network [J]. Chem. J. Chinese Universities, 1997, 18(11): 1783.
[12]	WANG Xia, YUAN Man-Xue, LAI Cheng-Ming, LIU Jie, LI Zheng-Ming. Using Molecular Graphics, Molecular Mechanics, Quantum Chemistry and Electrostatic Potential Methods to Study Structure-Property Relationship on Pesticides(Ⅸ)─Effect of Selecting Structural Parameters and Calculating Methods on Improving the Acc [J]. Chem. J. Chinese Universities, 1997, 18(1): 60.
[13]	CNANG Jian-Hua. Studies on the New Packings of High Performance Ion Exchange Chromatography for the Separation of Proteins(Ⅲ)──The Characteristics or the Packings of Cation Exchange Chromatography with Phospbono Group [J]. Chem. J. Chinese Universities, 1995, 16(12): 1911.
[14]	CHANG Jian-Hua, HAN Ya-Ping. Studies on the New Packings of High Performance Ion Exchange Chromatography for the Separation of Proteins(Ⅱ)─The Synthesis and Characteristics of the New Packings or Weak Cation Exchange Chromatography [J]. Chem. J. Chinese Universities, 1994, 15(9): 1317.
[15]	YAN Liu-Ming, ZHANG Wei-Ming, QIN Pei, CHEN Nian-Yi . Multi-dimensional Bond-Parametric Analysis of Molten Salt Conductance [J]. Chem. J. Chinese Universities, 1994, 15(5): 721.

The Prediction of Cation Exchange Distribution Coefficients with Artificial Neural Network

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments