作者：熊保平1,2,4, 甘振华1,3, 高跃明2, 杜民2,3
作者单位：1. 福建工程学院数理系, 福建 福州 350108;
2. 福州大学物理与信息工程学院, 福建 福州 350116;
3. 福州大学电气工程与自动化学院, 福建 福州 350116;
4. 福建省大数据挖掘与应用技术重点实验室, 福建 福州 350108
关键词：金免疫层析试条;定量检测;曲线拟合;约束优化;神经动力学优化算法;最小二乘法
摘要：
针对金免疫层析试条定量检测系统中OD（光密度）-浓度的拟合曲线会出现检测值与实际值偏差较大，容易导致定性结果错误的情况，提出以最大绝对误差最小为评价指标的曲线拟合方案，并转化为相应的约束优化问题使用神经动力学优化算法进行求解。仿真数据实验表明神经动力学曲线拟合方法明显优于插值法和三次样条，与最小二乘法相比在等同条件下50次曲线拟合的平均最大绝对误差降低14%；通过金免疫层析试条定量检测仪的一组标定数据实验表明三次多项式基本符合OD值与浓度正相关关系，且此时神经动力学拟合曲线的最大误差与最小二乘法相比降低25%；实验结果表明该文提出的神经动力学曲线拟合方法结果收敛稳定，且有效降低最大绝对误差，为金免疫层析试条定量检测提供一种新的较简单和精确的曲线拟合方法。
Neural dynamics fitting of the OD-concentration curve of gold immunochromatography strip
XIONG Baoping1,2,4, GAN Zhenhua1,3, GAO Yueming2, DU Min2,3
1. Department of Mathematics and Physics, Fujian University of Technology, Fuzhou 350108, China;
2. College of Physics and Information Engineering, Fuzhou University, Fuzhou 350116, China;
3. College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China;
4. Key Laboratory of Big Data Mining and Applications of Fujian Province,, Fuzhou 350108, China
Abstract: Incorrect qualitative result is easy to be caused by large deviation between detection value and actual value on the OD (optical density)-concentration fitting curve,which may result in inaccurate result of gold immunochromatographic strip qualitative detection system.A curve fitting scheme of taking the maximum absolute error minimum as evaluation index is hereby proposed.Corresponding constrained optimization problem is converted to neural dynamics optimization algorithm for solution.Simulation data experiment shows that neural dynamical curve fitting method is obviously superior to the interpolation method and cubic spline.Compared with the least square method,the average maximum absolute error of 50-times curve fitting under the same condition is reduced by 14%; the experimental results of a set of calibration data from quantitative detection instrument of the gold immunochromatographic strip show that cubic polynomial basically complies with normal phase relation between OD value and concentration,and the maximum error of the fitting curve is reduced by 25% compared with that of the least square method; the experimental results show that neural dynamical curve fitting method put forward in the paper features stable convergence and the maximum absolute error is reduced effectively; a new curve fitting method for quantitative detection of gold immunochromatographic strip is provided.
Keywords: gold immunochromatographic strip;quantitative detection;curve fitting;constrained optimization;neuro-dynamical optimization algorithm;least square method
2016, 42(11): 126-130 收稿日期: 2016-5-18;收到修改稿日期: 2016-5-18
基金项目: 科技部港澳台合作项目（2012DFM30040）；福建省科技重大专项（2013YZ0002，2014YZ0001）
作者简介: 熊保平(1980-),男,江西南昌市人,讲师,博士,主要研究方向为深度图像学习与生物信息挖掘。
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