基于嵌入式电脑横机控制系统

本文分析了电脑横机的结构与功能,提出了基于嵌入式的电脑横机控制系统,采用了S3C2410为主处理芯片,通过FPGA扩展端口,系统读取织物花型数据,控制横机各个动作子系统来完成编制动作,该电脑横机控制系统与传统电脑横机系统相比较,工作效率高,可移植性强。     

随机森林理论浅析

随机森林是一种著名的集成学习方法,被广泛应用于数据分类和非参数回归。本文对随机森林算法的主要理论进行阐述,包括随机森林收敛定理、泛化误差界以和袋外估计三个部分。最后介绍一种属性加权子空间抽样的随机森林改进算法,用于解决超高维数据的分类问题。     

EBZ260H型掘进机在隧道施工中的应用

以某工程为具体实例,介绍了EBZ2260H掘进机的适用范围、技术参数和主要配置;从掘进机的截割方法、维护和保养、除尘装置的正确使用等多个方面,对EBZ260H掘进机暗挖工艺和技术进行了详细阐述;归纳总结了EBZ260H掘进机的各项优点.     

技术防范电信欠费

电信用户欠费是当今电信业者面临的日益严峻的问题,本文主要阐述如何利用电信企业拥有的数据仓库,依靠技术手段分析追踪和预防用户异常行为,达到防范电信欠费的效果。     

电磁搅拌技术在莱钢六号合金钢连铸机上的设计与应用

介绍结晶器电磁搅拌在矩形坯连铸机上的应用。采用内置式结晶器电磁搅拌后,连铸坯低倍组织大为改善,质量明显提高。     

Single machine scheduling with simple linear deterioration to minimize total absolute deviation of completion times

We consider a single machine scheduling problem with simple linear deterioration. Job processing times are assumed to be a simple linear function of a job-dependent growth rate and the job's starting time. We seek an optimal schedule, so as to minimize the total absolute deviation of completion times (TADC). We prove several interesting properties of an optimal schedule, and introduce two efficient heuristics which are tested against a lower bound.     

Evaluation of tile–wall bonding integrity based on impact acoustics and support vector machine

It is well recognized that the impact-acoustic emissions contain information that can indicate the presence of the adhesive defects in the bonding structures. In our previous papers, artificial neural network (ANN) was adopted to assess the bonding integrity of the tile–walls with the feature extracted from the power spectral density (PSD) of the impact-acoustic signals acting as the input of classifier. However, in addition to the inconvenience posed by the general drawbacks such as long training time and large number of training samples needed, the performance of the classic ANN classifier is deteriorated by the similar spectral characteristics between different bonding status caused by abnormal impacts. In this paper our previous works was developed by the employment of the least-squares support vector machine (LS-SVM) classifier instead of the ANN to derive a bonding integrity recognition approach with better reliability and enhanced immunity to surface roughness. With the help of the specially designed artificial sample slabs, experiments results obtained with the proposed method are provided and compared with that using the ANN classifier, demonstrating the effectiveness of the present strategy.     

一种多分类器集成的手写体汉字识别方法

多分类器集成是手写体汉字识别领域的新方向。本文提出的多分类器集成方法通过改进的欧氏距离分类器将待识别汉字分类到某个粗分结果集中,然后根据粗分结果集选择1-N(one-against-rest)的SVM分类器对待识别汉字进行细分,最后用贝叶斯集成两级分类器。实验对国标一级汉字中的1034个手写汉字进行识别,证明了方案的有效性。     

基于主次原型超平面最接近支持向量机

基于广义特征值的最接近支持向量机GEPSVM是一种新的具有与SVM性能相当的两类分类方法,通过求解广义特征值来获得两个彼此不平行的拟合两类样本的超平面,其决策规则是将测试样本归为距其最近的超平面所在的类。然而,该规则在某些情形会导致较差的分类结果。对此,本文提出了在利用GEPSVM产生一个主原型超平面的基础上,再利用主原型超平面及它类样本的信息构造一个次原型超平面,形成一个由主次原型超平面共同决策的最接近支持向量机。该方法不仅简单且易于实现,而且具有较GEPSVM更优的分类性能。在UCI数据集上的实验验证了它的有效性。     

集成学习算法在不平衡分类中的应用研究

提出一种基于训练集分解的不平衡分类算法,该算法使用能输出后验概率的支持向量机作为分类器,使用基于测度层次信息源合并规则实现分类器的集成.在4个不同领域的不平衡数据集上的仿真实验表明:该算法有效提高分类器对正类样本的正确率,同时尽量减少对负类样本的误判.实验结果验证集成学习算法处理不平衡分类问题的有效性.