基于Vague集的道路交通状态决策信息融合

为了获取更加合理、准确的交通状态决策信息,针对交通状态决策信息的多源、模糊、时变特性,基于vague集建立了浮动车、感应线圈与人工报告作为信息源的模糊信息融合模型,能够实现路段与区域路网的交通状态判别。给出了一个路段多源交通状态决策信息融合的算例,验证了该方法的有效性。该方法同时为主客观信息融合提供了一种实现途径。     

一种基于路段惩罚法的合理路径集生成算法

为了给路径选择模型提供合理的路径集输入,使路径集能够包含更多驾驶员实际选择的路径,提出了一种基于路段惩罚法的路径集生成算法.根据发生拥堵的频率定义路段的拥堵指数,然后根据拥堵指数确定新算法的惩罚规则:在上一次计算的最优路径中需要增加阻抗的路段,是拥堵指数较大路段,而不是原始算法提出的所有路段.通过定义合理的指标评价路径集生成算法的有效性,根据实测的驾驶员出行路径数据评价改进的路段惩罚算法、原始的路段惩罚法以及应用较广泛的随机分类组合法.结果表明,在几种算法中本文提出算法生成的路径与实测路径完全一致的比例最大.     

Application of support vector machine to ship steering

System identification is an effective way for modeling ship manoeuvring motion and ship manoeuvrability prediction. Support vector machine is proposed to identify the manoeuvring indices in four different response models of ship steering motion, including the first order linear, the first order nonlinear, the second order linear and the second order nonlinear models. Predictions of manoeuvres including trained samples by using the identified parameters are compared with the results of free-running model tests. It is discussed that the different four categories are consistent with each other both analytically and numerically. The generalization of the identified model is verified by predicting different untrained manoeuvres. The simulations and comparisons demonstrate the validity of the proposed method.     

Support vector machine-based fuzzy rules acquisition system

This paper proposes a support vector machine-based fuzzy rules acquisition system (SVM-FRAS). The character of SVM in extracting support vector provides a mechanism to extract fuzzy If-Then rules from the training data set. We construct the fuzzy inference system using fuzzy basis function (FBF). The gradient technique is used to tune the fuzzy rules and the inference system. Theoretical analysis and comparative tests are performed comparing with other fuzzy systems. Experimental results show the SVM-FRAS model possesses good generalization capability as well as high comprehensibility.     

普通机床的数控改造策略

本文以西门子802D数控系统为例,介绍数控机床改造时需要进行的准备、数控系统和伺服系统选择以及电气控制系统设计改造等内容。     

一个基于TSVM的GIF图像通用隐写检测方法

直推式支持向量机（TSVM）是一种从标记样本出发,对特定的未标记样本进行识别和分类的技术.本文分析了将TSVM应用到图像通用隐写检测中的可行性,提出并实现了基于TSVM的GIF图像通用隐写检测方法.实验结果表明,针对不同的GIF图像隐写工具,本文方法在较少标记样本条件下引入大量未标记样本,得到接近监督学习的通用检测效果.从而提高了GIF图像通用隐写检测的实用性.     

基于半监督学习的SVM-KNN

提出一种新的基于半监督的SVM—KNN分类方法,当可用的训练样本较少时,使用SVM进行分类,不能得到准确的分类边界,本文采用半监督学习策略从大量未标记样本中提取边界向量来改善SVM-KNN分类器的引进不仅扩充了SVM的训练样本数目,而且优化了迭代过程中训练样本的标记质量,可不断修复SVM的分类边界．实验结果表明,所提出的方法能提高SVM算法的分类精度,通过调整参数能够获得更好的分类效果,同时也减小了标记大量未标记样本的代价．     

High speed tensile test of steel sheets for the stress-strain curve at the intermediate strain rate

This paper presents stress-strain curves of steel sheets for an auto-body obtained at intermediate strain rates with a servo-hydraulic type high speed tensile testing machine. The apparatus has the maximum stroke velocity of 7.8 m/sec to obtain the tensile material properties at a strain rate of up to 500/sec. A special jig fixture is specially designed for accurate acquisition of tensile loads with reduction of the load-ringing phenomenon induced by unstable stress wave propagation at high strain rates. Tensile testing of steel sheets for an auto-body was carried out to obtain stress-strain curves of mild steel and advanced high strength steels at strain rates ranged from 1/sec to 200/sec. The test results provide interesting information regarding the stress-strain curves at intermediate strain rates ranged from 1/sec to 200/sec and demonstrate that strain rate hardening is strongly coupled with strain hardening.     

港口机械安全性与港口生产安全

介绍国内港口机械安全性与港口生产安全状况,并从港口机械的安全性、港口机械对作业人员安全 的影响和装卸货物安全的影响3个方面,论述港口机械安全性与港口生产安全的关系。     

基于支持向量机的船舶柴油机故障诊断

介绍了支持向量机(SVM)的机理,应用SVM对船舶电站主柴油机进行故障诊断,研究了SVM参数的选择方法,仿真结果表明,SVM具有较好的诊断效果和较强的抗噪声能力;对复合故障样本诊断准确度较RBF神经网络高.