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人工神经网络用于锕系离子An^(3+)水解常数pK_1预测研究 被引量:1

Study on Prediction of Hydrolysis Co nstant of Actinide Elements Ions An^(3+) by Using Artificial Neural Network
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摘要 A set of parameters such as ionic radi i,electronegativity,base state L v alues,and periodic factors,defined in this work,were used to nonlinearly c orrelate hydrolysis constants p K1of the lanthanide and actinide metal ions(Ln3?and An 3?£(c)with the functional£-link net£¨FLN£(c)£(r)Training the functional£-link net£¨FLN£(c)with a group mix stylebooks make up of 13Ln3? and 4An3?,10An 3?p K 1 were predicted by FLN£(r) A set of parameters such as ionic radii, electronegativity, base state L values, and periodic factors, defined in this work, were used to nonlinearly correlate hydrolysis constants pK, of the lanthanide and actinide metal ions (Ln(3+) and An(3+)) with the functional-link net(FLN). Training the functional-link net (FLN) with a group mix stylebooks make up of 13 Ln(3+) and 4 An(3+), 10 An(3+) pK(1) were predicted by FLN.
出处 《无机化学学报》 SCIE CAS CSCD 北大核心 2002年第6期627-630,共4页 Chinese Journal of Inorganic Chemistry
基金 国家自然科学基金资助课题(No.29775001)。
关键词 人工神经网络 锕系离子 水解常数 函数连接型 神经网络 预测 水溶液化学 lanthanide metal ions actinide metal ions hydrolysis constants functional-link net predict
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参考文献11

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