基于SVR与微分进化策略的话务量预测

采用支持向量回归机(SVR)与微分进化策略相结合的方法,对新疆2个地区的月平均忙时话务量进行预测。由微分进化策略良好的全局搜索性质,以预测平均相对误差为目标函数,对SVR的超参数进行寻优,利用优化后的SVR月平均忙时话务量进行预测。与传统的网格寻优算法和RBF神经网络方法进行比较,结果表明,SVR的泛化能力与微分进化策略的搜索能力相结合,可以得到更好的预测 效果。     

支持向量回归用于预测锰系钙钛矿型氧化物奈尔温度

有效预测锰系钙钛矿型氧化物的奈尔温度(T_N)有助于该材料的理性设计。在本文中,支持向量回归(SVR)用于关联T_N与锰系钙钛矿型氧化物主要原子参数之间的关系。最大相关最小冗余(mRMR)用于选择建模中的主要描述符,特征变量选择表明包括分子质量(M),A-位离子半径(R_a),A-位离子电负性(E_a)在内的三个描述符对模型建立非常重要。留一法交叉验证(LOOCV)用于核函数的选择和参数优化。用基于径向基核函数的支持向量回归算法,构建了T_N与上述三个描述符之间的非线性关系。LOOCV和外部验证测试的结果表明,构建的模型具有很强的泛化能力,平均相对误差(MRE)分别为8.0%和16.4%。因此,SVR模型是预测锰系钙钛矿型氧化物T_N的有前景的工具。     

基于WLR和PSO-AFS-SVR的滚动轴承可靠度预测方法

在训练数据缺乏的情况下,为了提高支持向量回归机(SVR)对滚动轴承可靠度的预测精度,提出了一种基于威布尔线性回归(WLR)组合可靠度模型结合粒子群人工鱼群-支持向量回归机(PSO-AFS-SVR)的预测方法。首先,使用威布尔统计模型与线性回归（LR）的组合模型作为可靠度模型,利用测量滚动轴承振动信号的加速度计频谱,依据峰值频率分布的变化,分割其性能衰退的各个阶段,对每个阶段单独建模,以便最大程度地挖掘小样本信息;其次,采用k-折交叉验证(k-fold)的平均绝对误差(MAE)和平均相对误差(MAPE)之和作为适应度函数,利用PSO-AFS优化SVR参数,提高其泛化能力和预测精度;最后,采用滚动轴承全寿命周期试验数据进行了验证试验。试验结果表明,所提方法可以对滚动轴承的可靠度进行更准确的预测。     

在QSAR中应用SVR的非线性组合预测

为提高定量构效关系(quantitative structure-activity relationship,QSAR)模型预测的精度,以支持向量回归(support vector regression,SVR)全局与局部核函数,发展出1种非线性组合方法GK-LK-SVR,其基本思路为:依均方误差(MSE)最小原则,分别基于SVR的全局与局部核函数筛选描述符后预测,实测值与不同核函数的预测值组合成混合样本,然后再依MSE最小原则基于SVR对混合样本实施核函数寻优及子模型筛选,最后以留一法完成预测。对2种化合物QSAR建模结果表明:GK-LK-SVR方法预测精度高,有望在QSAR研究中得到广泛应用。     

基于改进灰狼优化算法的支持向量回归预测

为了提高支持向量回归(SVR, Support Vector Regression)进行数据驱动预测的精度,针对SVR存在的参数优化问题,通过引入Tent混沌映射进行种群初始化、改进收敛方式、并结合模拟退火算法,改进了传统的灰狼优化算法(GWO, Grey Wolf Optimization)来优化SVR超参数,并基于改进后的GWO算法提出了一种IGWO-SVR预测模型。将提出的IGWO-SVR模型应用于NASA锂电池数据集仿真SOH预测以及实际生产中的车灯电流预测实验后,实验结果表明IGWO-SVR预测模型在NASA锂电池数据集上进行预测的误差相较GWO-SVR模型降低了23％,相较粒子群算法和遗传算法优化的SVR模型均存在明显优势,误差分别降低了39%和51%;在实际工作中使用IGWO-SVR模型进行车灯电流预测也取得良好效果,与实测值之间的相对误差达到2.67%,相较GWO-SVR模型误差降低了近7个百分点,证明了模型在实际应用中的具有良好的价值。     

混合多个SVR模型的金融时间序列预测

基于支持向量回归(SVR)进行金融时间序列预测,使用PSO算法确定SVR超参数,并用实验的方法选择合适的SVR输入向量。为了解决金融时间序列非平稳性导致的单一SVR模型预测精度不稳定的问题,提出一种混合多个SVR模型的预测算法,选取训练数据的不同子集训练出多个SVR模型,采用对多个模型的预测结果加权求和的方法进行预测,各个模型的权重根据其预测误差动态调整。在全球5大股指上的实验表明,该算法的预测能力明显优于单一SVR模型。     

基于SVR的煤矿地下水位预测模型

将SVR(Support Vector Regression)回归算法应用于煤矿地下水位预测.基于SVR回归算法分析.筛选了合适的核函数及其参数,提出了基于SVR回归算法的煤矿地下水位预测模型,并根据所选矿区的自然地理和水文地质情况.确定了预测输入因子和输出因子.数值实验表明:预测结果与实际测量结果具有较好的一致性.验证了煤矿地下水位预测模型是有效的.为煤矿地下水位的预测提供了一个新的有效方法.     

基于支持向量回归机的区域物流需求预测模型及其应用*

为了提高区域物流需求预测的能力,从区域经济等影响因素指标与区域物流需求之间的内在关系的角度,应用基于结构风险最小化准则的支持向量回归机（SVR）方法, 建立“影响因素—区域物流需求” SVR预测模型来研究预测区域物流需求问题。在选择适当的参数和核函数的基础上,对上海市物流需求量进行预测,发现该方法能获得较小的训练相对误差和测试相对误差。     

基于支持向量机回归的抗癌药物活性研究

采用支持向量机回归(SVR)方法研究了40个抗癌化合物-二取代[(吖啶-4-酰胺基)丙基]甲胺类衍生物的定量构效关系,基于留一法交叉验证的结果,其平均相对误差是6.56％.结果表明,所建SVR模型的精度高于逆传播人工神经网络(BPANN)、多元线性回归(MLR)和偏最小二乘法(PLS)所得的结果.     

一种改进的组合SOFM-SVR股票价格预测模型

股票市场价格预测一直以来都被认为是金融时序预测领域的一项具有挑战性的工作。综合回归支持向量机SVR和自组织特征函数(SOFM)技术,并引入基于过滤的特征选择算法确定重要的输入变量,在SVR核函数的参数选择上采用粒子群优化算法(PSO)。SOFM算法将训练样本聚类,然后分别应用SVR来预测股票价格走势。最后应用上海A股的浦发银行日数据来做股票价格日预测,实验结果表明,经过改进的SOFM-SVR模型与之前的SOFM-SVR模型相比,在预测精度和训练时间上都有了较大的提高。     

Only connect: teaching, technology and telesis

Abstract This paper describes an approach to the design of interactive multimedia materials being developed in a European Community project. The developmental process is seen as a dialogue between technologists and teachers. This dialogue is often problematic because of the differences in training, experience and culture between them. Conditions needed for fruitful dialogue are described and the generic model for learning design used in the project is explained.     

European Community policy and the market

Abstract This paper starts with some reflections on the policy considerations and priorities which are shaping European Commission (EC) research programmes. Then it attempts to position the current projects which seek to capitalise on information and communications technologies for learning in relation to these priorities and the apparent realities of the marketplace. It concludes that while there are grounds to be optimistic about the contribution EC programmes can make to the efficiency and standard of education and training, they are still too technology driven.     

一种自适应子融合集成多分类器方法

融合集成方法已经广泛应用在模式识别领域,然而一些基分类器实时性能稳定性较差,导致多分类器融合性能差,针对上述问题本文提出了一种新的基于多分类器的子融合集成分类器系统。该方法考虑在度量层融合层次之上通过对各类基多分类器进行动态选择,票数最多的类别作为融合系统中对特征向量识别的类别,构成一种新的自适应子融合集成分类器方法。实验表明,该方法比传统的分类器以及分类融合方法识别准确率明显更高,具有更好的鲁棒性。     

Avoiding semantic and temporal gaps in developing software intensive systems

Development of software intensive systems (systems) in practice involves a series of self-contained phases for the lifecycle of a system. Semantic and temporal gaps, which occur among phases and among developer disciplines within and across phases, hinder the ongoing development of a system because of the interdependencies among phases and among disciplines. Such gaps are magnified among systems that are developed at different times by different development teams, which may limit reuse of artifacts of systems development and interoperability among the systems. This article discusses such gaps and a systems development process for avoiding them.     

Designing economic np control charts: A programmed simulation approach

This paper presents control charts models and the necessary simulation software for the location of economic values of the control parameters. The simulation program is written in FORTRAN, requires only 10K of main storage, and can run on most mini and micro computers. Two models are presented - one describes the process when it is operating at full capacity and the other when the process is operating under capacity. The models allow the product quality to deteriorate to a further level before an existing out-of-control state is detected, and they can also be used in situations where no prior knowledge exists of the out-of-control causes and the resulting proportion defectives.     

The development of robot art

Going through a few examples of robot artists who are recognized worldwide, we try to analyze the deepest meaning of what is called “robot art” and the related art field definition. We also try to highlight its well-marked borders, such as kinetic sculptures, kinetic art, cyber art, and cyberpunk. A brief excursion into the importance of the context, the message, and its semiotics is also provided, case by case, together with a few hints on the history of this discipline in the light of an artistic perspective. Therefore, the aim of this article is to try to summarize the main characteristics that might classify robot art as a unique and innovative discipline, and to track down some of the principles by which a robotic artifact can or cannot be considered an art piece in terms of social, cultural, and strictly artistic interest. This work was presented in part at the 13th International Symposium on Artificial Life and Robotics, Oita, Japan, January 31–February 2, 2008     

Explanation and prediction: an architecture for default and abductive reasoning

Although there are many arguments that logic is an appropriate tool for artificial intelligence, there has been a perceived problem with the monotonicity of classical logic. This paper elaborates on the idea that reasoning should be viewed as theory formation where logic tells us the consequences of our assumptions. The two activities of predicting what is expected to be true and explaining observations are considered in a simple theory formation framework. Properties of each activity are discussed, along with a number of proposals as to what should be predicted or accepted as reasonable explanations. An architecture is proposed to combine explanation and prediction into one coherent framework. Algorithms used to implement the system as well as examples from a running implementation are given.     

Three Process Perspectives: Organizations, Teams, and People

This paper provides the author's personal views and perspectives on software process improvement. Starting with his first work on technology assessment in IBM over 20 years ago, Watts Humphrey describes the process improvement work he has been directly involved in. This includes the development of the early process assessment methods, the original design of the CMM, and the introduction of the Personal Software Process (PSP)^SM and Team Software Process (TSP){^SM}. In addition to describing the original motivation for this work, the author also reviews many of the problems he and his associates encountered and why they solved them the way they did. He also comments on the outstanding issues and likely directions for future work. Finally, this work has built on the experiences and contributions of many people. Mr. Humphrey only describes work that he was personally involved in and he names many of the key contributors. However, so many people have been involved in this work that a full list of the important participants would be impractical.     

基于复小波噪声方差显著修正的SAR图像去噪

提出了一种基于复小波域统计建模与噪声方差估计显著性修正相结合的合成孔径雷达(Synthetic Aperture Radar,SAR)图像斑点噪声滤波方法。该方法首先通过对数变换将乘性噪声模型转化为加性噪声模型,然后对变换后的图像进行双树复小波变换(Dualtree Complex Wavelet Transform,DCWT),并对复数小波系数的统计分布进行建模。在此先验分布的基础上,通过运用贝叶斯估计方法从含噪系数中恢复原始系数,达到滤除噪声的目的。实验结果表明该方法在去除噪声的同时保留了图像的细节信息,取得了很好的降噪效果。     

基于QTE的蒙古文显示机制研究与实现

蒙古语言是中国蒙古族使用的通用语言,由于蒙古文区别于其他文字的书写方式和其自身变形机制等特点,在很多通用的文字处理引擎中都不被支持。在嵌入式产品开发与应用领域中Linux加QTE已经成为流行方式。该文给出了一种在QTE环境上实现基于标准Unicode的蒙古文点阵显示和变形算法, 并自定义了支持蒙古文的QTE组件,扩展了QTE功能,为在Linux加QTE方式的嵌入式体系结构中处理蒙古文提供了一种解决方法。