用亚图参数与回归技术估计和预测烷烃的核磁共振碳谱

系统研究了分子建模在波谱分析中的应用.采用多元线性回归算法(MLR)估计和预测了60余种烷烃的碳谱化学位移.烷烃中碳原子由十余种对应于所谓根亚树的相嵌频率描述子所决定.这些描述子等于由2~5个碳原子组成的更小结构骨架组成.说明了所用描述子作为很有用的工具可适当地描述烷烃中碳所处微观环境.同时还比较了与神经网络的计算结果.     

神经网络法用于多元混酸同时测定

利用多层神经网络误差反向传播算法处理酸碱电位滴定数据，求得出多元混合酸各组分的浓度，优化了神经网络的结构和参数，测定了三组分有机酸混合样品，结果良好，平均相对偏差ＲＳＤ≤４％。     

Determination of Optical Properties of Turbid Media from Spatially Resolved Diffuse Reflectance by Neural Network

A backpropagation (BP) network is applied to the inversion of spatially resolved diffuse reflectance from turbid media and then to determine its optical properties. A standard BP network may be trapped to the local minimum. A BP network with variable momentum and variable leaning rate can reduce this effect. After being trained, this network will produce reduced scattering coefficients and absorption coefficients when the spatially resolved diffuse reflectance are fed to its input.     

神经网络在波谱分析中的应用：用亚图估计和预测烷烃的^13C NMR

系统研究了神经网络在波谱分析中的应用，采用多层／三层前馈神经网络以误差反传及改进算法估计和预测Ｃ１－Ｃ１０的６０余种烷烃的化学位移。烷烃中碳原子由十余种对应于所谓根亚树的相嵌频率描述子所决定。这些描述子等于由１至６个碳原子组成的更小结构骨加组成。     

基于实数编码遗传算法的多层神经网络BP算法

提出用实数编码的遗传算法来优化多层神经网络的权值，并且将遗传算法与ＢＰ算法结合，能有效地避免ＢＰ算法陷入局部极小和遗传算法过早收敛，实验结果令人满意．     

An adaptive learning rate backpropagation‐type neural network for solving n × n systems on nonlinear algebraic equations

This paper presents an MLP‐type neural network with some fixed connections and a backpropagation‐type training algorithm that identifies the full set of solutions of a complete system of nonlinear algebraic equations with n equations and n unknowns. The proposed structure is based on a backpropagation‐type algorithm with bias units in output neurons layer. Its novelty and innovation with respect to similar structures is the use of the hyperbolic tangent output function associated with an interesting feature, the use of adaptive learning rate for the neurons of the second hidden layer, a feature that adds a high degree of flexibility and parameter tuning during the network training stage. The paper presents the theoretical aspects for this approach as well as a set of experimental results that justify the necessity of such an architecture and evaluate its performance. Copyright © 2015 John Wiley & Sons, Ltd.