2真实齿面对应点的求解算法

针对真实齿面数学模型为自由型参数化隐式递推公式，不易于用一般方法进行迭代求解的问题，提出了将求2齿面对应点问题转换成求直线与齿面交点的王角形判断法，并进一步提出运用三角形减半法确定真实齿面精确对应点的迭代初值，得到了一种稳定、可靠、精度高且运算速度较快的求解算法。     

An oligonucleotide microarray-based assay for identification of phytoplasma 16S ribosomal groups

A method using consensus PCR followed by oligonucleotide microarray hybridization was developed for identification of phytoplasma 16Sr ribosomal groups. The array consisted of 21– to 33-nt-long oligonucleotides which were designed to hybridize to individual 16Sr groups. Two oligonucleotides were designed to detect all phytoplasma groups. The array could efficiently identify samples from 16SrI, 16SrII, 16SrIII, 16SrV, 16SrVI, 16SrVII, 16SrIX, 16SrX and 16SrXII ribosomal groups. This microarray-based test represents a rapid method for detection of phytoplasmas in unknown samples and for identification of most 16Sr groups.     

基于神经网络的电力系统谐波测量方法研究

提出了一种新的基于三角基函数神经网络的电力系统谐波测量方法，给出了该神经网络算法的收敛定理，并采用加窗插值算法修正基波频率的准确度．该方法不需要同步采样和整周期截断，可一次性获得电力系统基波及各次谐波的频率、幅值和相位．计算机仿真结果表明，该方法计算精度高，计算量小，收敛速度快．     

圆弧插补对数算法及误差分析

提出了一种采用对数算法的圆弧插补方法，并对插补误差进行了分析，插补软件利用ＭＣＳ－５１汇编语言编制。     

RAID系统的并行优化及性能分析

介绍了磁盘阵列技术 ,重点论述了命令合并并行控制算法在磁盘阵列中的实现 ,并对合并算法进行了性能分析 ,最后简述了合并算法在分布式阵列中的应用。     

微生物降解动力学参数估计新算法的比较

为了有效地估计较大范围变化的微生物降解动力学参数,发展了基于瞬时精英保护策略的遗传算法(IEPGA)和简单改进遗传算法(IGA),并和多次在参数区间内获取随机初值联用Matlab的lsqnonlin搜寻的算法进行了比较.这些算法利用模拟数据和文献数据,估计了积分形式的Monod模型参数.结果表明,虽然三者均能较好解决这一问题,但考虑到实际运行规模、时间以及最终结果精度,对于较大范围变化的微生物降解参数估计问题,多次(>20次)随机初值联用lsqnonlin的方法相对两种遗传算法更为可行.     

基于RETE算法的速生丰产林培育知识系统的设计

本文应用实现产生式系统的高效模式匹配算法—RETE算法,分析设计了速生丰产林生长培育知识系统。该系统的特点是使用相似性方法来处理模糊问题,能够较为理想地实现速生丰产林生长培育过程中的推理机制。     

Application of Artificial Neural Network in Elastic Internal Force Analysis of Two Way Slab

In this paper, the Artificial Neural Network (ANN) is applied to the internal force analysis of structure. After introducing the model and algorithm of back-propagation network, a trained BP network of three layers is used to calculate the maximum of elastic moment of middle span of two-way slab. In order to enhance the generalized capability of network, the modified value of weight should be regarded as convergence standard and in order to accelerate the learning process without vibration, the method of adding momentum coefficient is adopted. The analysis program of BP network is carried out with the software of Matlab. The result demonstrates that application of ANN in structure analysis is feasible.     

Improvement and Application on Back Propagation Network Based on Partial Least-squares Algorithm

This paper proposes a novel BP network model based on nonlinear iterative partial least-squares algorithm which can fit nonlinear data. The novel BP network model can reduce iterative step number and advance learning effieieney. This paper pretreats data by nonlinear iterative partial least-squares algorithms. The weights initialization of input floor and output floor are set by applying the loading weights of dependent variable and cause variable, the member of hidden nodes are set by applying factor numbers of nonlinear iterative partial leastsquares algorithm, the connection co- efficient is set by applying the connection matrix B. Performances of the BP, PLS, and PLS-BP are analyzed and compared. The results show that the PLS-BP has better fitting and forecasting than BP and PLS.