结合PCA的SVM方法在学校财务风险预警中的运用

利用支持向量机方法对中职学校财务风险进行预测,设置22个评价指标,运用主成分分析降维处理数据,然后通过Libsvm进行实验。通过对评价指标的主成分分析,发现前8个主分量的累计贡献率为89.18%,占有绝对重要的比重。选取前8个主分量为支持向量机的输入,最后得到5组实验数据,平均预测分类精度为93.75%,表明支持向量机方法在财务风险预测中的可行性和实用性。     

基于GA-LSSVR算法的回采工作面瓦斯涌出量预测

针对回采工作面瓦斯涌出量问题的小样本、非线性、影响因素关系复杂等特点,采用遗传-最小二乘支持向量回归算法对瓦斯涌出量进行预测,利用定量方法进行分析,避免了定性分析的局限性,有效提高了预测的精度。该模型首先利用遗传算法对最小二乘支持向量回归机中的参数进行训练和优化,然后运用遗传-最小二乘支持向量回归模型对测试样本进行了回采工作面瓦斯涌出量测试。测试结果表明:与支持向量回归机以及最小二乘支持向量回归机的预测值相比,遗传-最小二乘支持向量回归的回采工作面瓦斯涌出量预测可靠性和精确性更高。     

枝向量矩阵反馈环算法的MATLAB实现*

找到系统中的全部反馈环是系统动力学模型分析的基础。针对这一问题,比较了几种常见的反馈环计算方法,得出在时间复杂度上矩阵算法优于行列式算法。在计算机上用MATLAB实现了基于流率基本入树和强简化流率基本入树枝向量矩阵计算所有反馈环的矩阵算法,分析了算法的复杂性,并给出了相应的算例。     

现代织构分析的进展

本文系统阐述了材料现代织构分析的进展。     

Automatic classification of defects on the product surface in grinding and polishing

Grinding and polishing are standard operations in material processing. It is important to inspect and classify the potential defects existing on the product surfaces after grinding and polishing in order to obtain high quality in both functionality and aesthetics. Post-processing handling can be carried out after the defects have been correctly classified. A vision system already exists to detect and classify defects based on captured grayscale images automatically. The system is able to find and locate the defects precisely, but is incapable of placing those defects into the right predefined classes. The old system classifies the defects 30% of the time into the 15 predefined classes based on shape features. In this paper, a new classification strategy has been introduced using diverse extracted features. In addition to shape features, some other feature extraction methods were tried, e.g. Laws filter bank, DCT (Discrete Cosine Transformation) filter bank, Gabor filter bank, and statistical features based on co-occurrence matrix. The Support Vector Machine (SVM) was used as a multi-class classifier with input of the extracted features. By combining the Gabor filter features and the statistical features, the classification rate of the system can reach 82% overall right rate, which is applicable practically.     

An efficient method for solving the Signorini problem in the simulation of free-form surfaces produced by belt grinding

Industrial robots are recently introduced to the belt grinding of free-form surfaces to obtain high productive efficiency and constant surface quality. The simulation of belt grinding process can facilitate planning grinding paths and writing robotic programs before manufacturing. In simulation, it is crucial to get the force distribution in the contact area between the workpiece and the elastic contact wheel because the uneven distributed local forces are the main reason to the unequal local removals on the grated surface. The traditional way is to simplify this contact problem as a Signorini contact problem and use the finite element method (FEM) to calculate the force distribution. However, the FEM model is too computationally expensive to meet the real-time requirement. A new model based on support vector regression (SVR) technique is developed in this paper to calculate the force distribution instead of the FEM model. The new model approximates the FEM model with an error smaller than 5%, but executes much faster (1 s vs 15 min by FEM). With this new model, the real-time simulation and even the on-line robot control of grinding processes can be further conducted.     

基于小波包和支持向量机的滚动轴承故障模式识别

为了解决对故障轴承的特征提取和故障特征准确分类问题,提出了应用小波包变换和支持向量机相结合进行滚动轴承故障诊断的方法.小波包变换具有良好的时-频局部化特征,非常适于对瞬态或时变信号进行特征提取.而支持向量机可完成模式识别和非线性回归.利用上述原理根据轴承振动信号的频域变化特征,采用小波包变换对其提取频域能量特征向量,然后利用建立的支持向量机多故障分类器完成滚动轴承故障模式的识别.试验结果表明,支持向量机可以有效、准确地识别轴承的故障模式,为轴承故障诊断向智能化发展提供了新的途径.     

基于曲线拟合和SVM的眼动信号分类算法研究

为提高基于EOG的眼动信号分类算法精度,改进基于EOG的人—机交互系统性能,提出了一种基于曲线拟合(curve fitting)与支持向量机(SVM)的眼动信号分类算法(CF-SVM),并设计了新的实验范式,增加了“扫视保持”环节.该算法采用曲线拟合方法进行特征提取,在此基础上,使用SVM分类器对眼动信号进行分类.实验室环境下,对9名眼部活动正常的受试者进行了眼动数据采集与识别,CF-SVM算法的平均分类准确率达到98.3％,与其他几种眼动识别方法相比较,其平均正确率分别提升了9.4％、5.9％、1.0％.实验结果表明,CF-SVM算法在眼动信号识别中表现了良好的性能,具有高的分类精度和鲁棒性.     

改进混合蛙跳算法在蔬菜总黄酮软测量中的应用

针对蔬菜总黄酮化学物提取过程复杂、非线性和生物参数难以在线测量等特点,提出了基于改进混合蛙跳算法优化最小二乘支持向量机的蔬菜总黄酮软测量模型。该模型对标准混合蛙跳算法进行改进,采用反向学习的种群初始化策略,确保个体分布的均匀性;并根据群体适应度方差大小,动态调整变异概率,使算法避免陷入局部最优;最后采用改进的混合蛙跳算法对最小二乘支持向量机的参数进行寻优,实现蔬菜总黄酮软测量。仿真结果表明,基于改进混合蛙跳算法的最小二乘支持向量机软测量模型具有测量精度高,稳定性好的优点,有利于蔬菜总黄酮化学物测量工程的实际应用。     

基于加密编码矢量的农业无线传感网数据安全存储方法

无线传感网为精准农业生产环境监测提供了一种有效的解决方案。针对当前农业生产中无线传感网感知数据传输和存储过程中存在的安全性不高、存储效率不佳的问题,在研究农业无线传感网主要特征的基础上,分析了云存储技术对农业传感器感知数据存储的有效性,利用改进的网络编码技术降低了传感器感知数据在传输汇聚时对无线网有限带宽的占用率,给出了基于加密编码矢量方法的农业无线传感网感知数据传输、存取安全性和效率分析,提出了一种基于加密编码矢量的农业无线传感网感知数据信息的安全存储新方法。大田生产环境测试结果表明,基于网络编码的加密编码矢量方法安全性较高,在数据量显著增加的情况下传输性能可进一步得到提升,从而验证了本方法的合理性和实用性。