| 人工神经网络用于交流示波计时电位法的研究 |
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| 引用本文： | 于科岐,董社英,汤宏胜,高鸿.人工神经网络用于交流示波计时电位法的研究[J].高等学校化学学报,1999,20(9):1367-1370. |
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| 作者姓名： | 于科岐 董社英 汤宏胜 高鸿 |
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| 作者单位： | 1. 西北大学分析科学研究所,西安,710069
2. 山西省长治医学院 |
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| 基金项目： | 国家自然科学基金!29775018，陕西省教委基金!98JK114 |
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| 摘 要： | 提出了交流示波计时电位法的人工神经网络校正方法，并对其可行性和适用性进行了探讨，用此方法分别解析了大量Ｔｌ＾＋存在时Ｐｂ＾２＋和大量Ｉｎ＾２＋存在时Ｃｄ＾２＋的交流地波计时电位法的ｄＥ／ｄｔ－Ｅ曲线，结果表明，对Ｐｂ＾２＋和Ｃｄ＾２＋和Ｃｄ２＋的预测最大相对误差不超过５％，其性能良好。
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| 关 键 词： | 交流示波计时电位法 人工神经网络 铅 镉 |
Studies on Artificial Neural Networks Used in A.C. Oscillographic Chronopotentiometry |
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| YU Ke-Qi,DONG She-Ying,TANG Hong-Sheng,GAO Hong.Studies on Artificial Neural Networks Used in A.C. Oscillographic Chronopotentiometry[J].Chemical Research In Chinese Universities,1999,20(9):1367-1370. |
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| Authors: | YU Ke-Qi DONG She-Ying TANG Hong-Sheng GAO Hong |
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| Abstract: | A new calibration method of A. C. oscillographic chronopotentiometry with artificial neural networks has been developed, and its feasibility and adaptability were discussed.This method was applied to the determination of Pb2+ in excess of T1+, and Cd2+ in excess of In3+ system. The maximum relative error of Pb2+ and Cd2+ was not more than 5%. This study indicates that artificial neural networks may provide a new approach to determine the content for multi-component with A. C. oscillographic chronopotentiometry. |
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| Keywords: | A C oscillographic chronopotentiometry Artificial neural networks Lead Cadmium |
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