关键词： 异音检测   支持向量机   电机故障  

摘要： 在大批量小型电机生产线上,普遍采用的听音质检工序需要大量训练有素的工人。针对电机质检工序声音信号的统计特征及质检工艺的特点,提出基于一类学习的异响检测的方法。该方法以正常样本为基础建立质检判别函数,避免了其他分类算法要求训练样本类别全面和覆盖广泛的条件。给出了该方法的实现过程,并通过大量实测样本验证了该方法的有效性。

关键词： NLP   k-means   clustering   用户反馈   单词云  

摘要： 了解用户反馈信息对于改进购物网站的服务质量非常重要,但工作量很大。通过机器学习与自然语言处理的方法,可以将用户评论进行聚类,并构造一种可视化界面工具,有助于网站分析师与项目经理提升工作效率,简化工作流程。基于此,将对聚类算法,自然语言处理过程以及用户反馈信息处理工具中的一些重要功能进行介绍。

关键词： Research Article  

摘要： The adaptive immune response to vaccination or infection can lead to the production of specific antibodies to neutralize the pathogen or recruit innate immune effector cells for help. The non-neutralizing role of antibodies in stimulating effector cell responses may have been a key mechanism of the protection observed in the RV144 HIV vaccine trial. In an extensive investigation of a rich set of data collected from RV144 vaccine recipients, we here employ machine learning methods to identify and model associations between antibody features (IgG subclass and antigen specificity) and effector function activities (antibody dependent cellular phagocytosis, cellular cytotoxicity, and cytokine release). We demonstrate via cross-validation that classification and regression approaches can effectively use the antibody features to robustly predict qualitative and quantitative functional outcomes. This integration of antibody feature and function data within a machine learning framework provides a new, objective approach to discovering and assessing multivariate immune correlates.

关键词： Fecal pollution   Bacteria   Bacteriophages   Bifidobacterium   Bacteroides   Machine learning   Microbial source tracking  

摘要： In this study we use a machine learning software (Ichnaea) to generate predictive models for water samples with different concentrations of fecal contamination (point source, moderate and low). We applied several MST methods (host-specific Bacteroides phages, mitochondrial DNA genetic markers, Bifidobacterium adolescentis and Bifidobacterium dentium markers, and bifidobacterial host-specific qPCR), and general indicators (Escherichia colt, enterococci and somatic coliphages) to evaluate the source of contamination in the samples. The results provided data to the Ichnaea software, that evaluated the performance of each method in the different scenarios and determined the source of the contamination. Almost all MST methods in this study determined correctly the origin of fecal contamination at point source and in moderate concentration samples. When the dilution of the fecal pollution increased (below 3 log(10) CPU E. coli/100 ml) some of these indicators (bifidobacterial host-specific qPCR, some mitochondrial markers or B. dentium marker) were not suitable because their concentrations decreased below the detection limit. Using the data from source point samples, the software Ichnaea produced models for waters with low levels of fecal pollution. These models included some MST methods, on the basis of their best performance, that were used to determine the source of pollution in this area. Regardless the methods selected, that could vary depending on the scenario, inductive machine learning methods are a promising tool in MST studies and may represent a leap forward in solving MST cases. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： 机器博弈   机器学习   智能  

摘要： 该文介绍了机器博弈技术,给出了提升计算机的智能程度是研究机器博弈技术的重点。设计了五子棋游戏算法,由于算法设计决定了计算机的智能程度,该算法没有用到机器学习,计算机不具有智能。分析了卡斯帕罗夫和＂深蓝＂的不同特点,给出了＂深蓝＂战胜世界冠军的启示,只有利用机器学习技术开发的具备学习能力的计算机才具有智能。

关键词： Multipole moments   Hydrogen bonding   Force fields   QTAIM   QCT   Kriging  

摘要： As intermolecular interactions such as the hydrogen bond are electrostatic in origin, rigorous treatment of this term within force field methodologies should be mandatory. We present a method able of accurately reproducing such interactions for seven van der Waals complexes. It uses atomic multipole moments up to hexadecupole moment mapped to the positions of the nuclear coordinates by the machine learning method kriging. Models were built at three levels of theory: HF/6-31C**, B3LYP/aug-cc-pVDZ and M06-2X/aug-cc-pVDZ. The quality of the kriging models was measured by their ability to predict the electrostatic interaction energy between atoms in external test examples for which the true energies are known. At all levels of theory, >90% of test cases for small van der Waals complexes were predicted within 1 kJ mol(-1), decreasing to 60-70% of test cases for larger base pair complexes. Models built on moments obtained at B3LYP and M06-2X level generally outperformed those at HF level. For all systems the individual interactions were predicted with a mean unsigned error of less than 1 kJ mol(-1). (C) 2013 Elsevier B.V. All rights reserved.

关键词： 交通安全   事故预测   数据分类   高速铁路   神经网络   灰色模型  

摘要： 高速铁路运营事故预测方法是度量铁路安全管理水平的重要指标。为提高高速铁路的安全运营水平,引入工业数据分类方法,分析反向传播(BP)神经网络和灰色模型在高速铁路安全运营事故预测过程中的适应性。首先,运用事故次数、事故联动系数、月均事故率3个参数对高速铁路安全运营水平进行度量;然后,根据工业数据分类方法判别高速铁路运营事故数据属于块状型,据此建立反向传播(BP)神经网络运营事故预测模型;针对运营事故数据具有波动大的特点,利用均值聚类方法建立K-GM(1,3)预测模型。以近年来高速铁路运营事故数据为样本对模型进行训练和分析,结果表明:BP神经网络、K-GM(1,3)、GM(1,3)预测模型的预测误差分别为8.92%,13.68%,345.25%,BP神经网络在高速铁路安全运营事故预测过程中的适应性要优于灰度模型。

关键词： Feature selection   Multiple linear regression   Multilayer perceptron   Sequential minimal optimisation   Gaussian processes for regression   Environmental-noise prediction  

摘要： The prediction of environmental noise in urban environments requires the solution of a complex and non-linear problem, since there are complex relationships among the multitude of variables involved in the characterization and modelling of environmental-noise and environmental-noise magnitudes. Moreover, the inclusion of the great spatial heterogeneity characteristic of urban environments seems to be essential in order to achieve an accurate environmental-noise prediction in cities. This problem is addressed in this paper, where a procedure based on feature-selection techniques and machine-learning regression methods is proposed and applied to this environmental problem. Three machine-learning regression methods, which are considered very robust in solving nonlinear problems, are used to estimate the energy-equivalent sound-pressure level descriptor (L-Aeq). These three methods are: (i) multilayer perceptron (MLP), (ii) sequential minimal optimisation (SMO), and (iii) Gaussian processes for regression (GPR). In addition, because of the high number of input variables involved in environmental-noise modelling and estimation in urban environments, which make L-Aeq prediction models quite complex and costly in terms of time and resources for application to real situations, three different techniques are used to approach feature selection or data reduction. The feature-selection techniques used are: (i) correlation-based feature-subset selection (CFS), (ii) wrapper for feature-subset selection (WFS), and the data reduction technique is principal-component analysis (PCA). The subsequent analysis leads to a proposal of different schemes, depending on the needs regarding data collection and accuracy. The use of WFS as the feature-selection technique with the implementation of SMO or GPR as regression algorithm provides the best L-Aeq estimation (R-2 = 0.94 and mean absolute error (MAE) = 1.14-1.16 dB(A)). (C) 2014 Elsevier B.V. All rights reserved.

关键词： MACHINE learning   COMPUTATIONAL biology   CANCER  

摘要： A correction notice to the article 'Machine learning methods in the computational biology of cancer' that was published in a 2014 issue of the periodical is presented.

关键词： 农业数据库   数据挖掘   分类预测   程序语言  

摘要： 目前，随着互联网的迅猛发展，农业网站也在不断进步，而农业网站中农业数据每天都以惊人的速度不断地持续增长。并且农业数据的种类丰富多彩，有宏观的农业数据、科技数据、市场数据和科学文化数据等。但是这些农业数据只是具有大量不确定的、不完整的、带有噪声以及冗杂数据的原始资料,无法直接为人们提供有价值的信息和知识。我们迫切需要一种技术帮助我们从茫茫无际的农业数据海洋中获取与农业生产、管理、经营相关的信息，从而做出正确的农业决策，引导农业高效生产。数据挖掘技术对数据进行深层次的分析与挖掘的一种技术,是伴随现代科学技术应运而生。因此，本文采用数据挖掘技术对农业数据进行有效的采集，进而深度分析数据，为用户提供方便的分类预测，为用户提供有利的农业决策，提高农业数据的利用率。\n 本研究主要内容包括：⑴介绍了农业网站中农业数据的特征以及对农业数据的使用现状，描述了数据挖掘技术的基本理论和思想，通过分析农业数据的特征和数据挖掘技术处理数据的思想,探讨了数据挖掘技术在农业方面的应用研究。⑵提出了加权的极限学习机分类算法。对基于朴素贝叶斯、支持向量机和极限学习机的农业数据分类预测算法的进行了分析和比较后，提出了的加权极限学习机分类算法，通过与极限学习机分类算法的实验对比，证明了其较好的分类效果。⑶设计了农业数据分类预测模型。分析农业数据分类预测流程，采用了基于缠绕法的农业数据属性筛选，进行对农业数据的预处理；通过分析作为数据源的农业网站的Web页面结构特征和HTML语言的结构特征，提出针对农业网站的Web页面提出用于抽取Web页面中相关农业数据的抽取算法，并应用于农业数据分类预测模型的设计。⑷实现了农业数据分类预测模型。采用C#编程语言，***技术完成农业数据分类预测模型中的分类预测模块，选择Visual Studio2013作为为前端开发环境，设计系统界面，并显示和输出价格预测结果。