基于SVR的混沌时间序列预测

支持向量机是一种基于统计学习理论的新颖的机器学习方法,由于其出色的学习性能,该技术已成为当前国际机器学习界的研究热点。这种方法已广泛用于解决分类和回归问题。论文介绍了支持向量回归算法的各种版本,同时将它们应用到混沌时间序列预测中,并且比较了它们的预测性能,为实际应用合理选择模型提供一定的依据。     

基于机器学习的侧信道分析研究及RSA算法的应用示例

基于机器学习的密码算法侧信道分析是一个较新的研究领域,自首个分析结果发表以来,大量的研究结果表明机器学习算法相比传统方法在侧信道分析中具有很大的性能优势。因此,基于机器学习的侧信道分析应在相关的安全检测技术领域得到充分的应用。本文针对目前侧信道攻击中常用的机器学习算法进行介绍,并针对密码算法RSA进行分析,设计了基于机器学习的侧信道攻击实验并对比实验结果。     

基于C-AdaBoost模型的乳腺癌预测研究

机器学习和深度学习技术可用于解决医学分类预测中的许多问题,其中一些分类算法的预测精度较高,而另一些算法的精度有限。提出了基于C-AdaBoost模型的集成学习算法,对乳腺癌疾病进行预测,发现了判断乳腺癌是否复发、乳腺癌肿瘤是否为良性的最优特征组合。通过逐步回归方法对现有特征进行二次选取,并结合C-AdaBoost模型使得预测效果更优。大量实验表明,基于C-AdaBoost模型的算法的预测准确率比SVM、Naive Bayes、RandomForest以及传统的集成学习模型等机器学习分类器的准确率最多可提高19.5%,从而可以更好地帮助医生进行临床决策。     

基于机器学习建模的航天器健康管理平台研究

近年来,随着深度学习等技术的快速发展和航天器系统数据量的不断增加,新型的机器学习平台凭借其友好的流程化分析框架、丰富的即插即用机器学习工具、分布式的服务等诸多优点,为航天器等领域复杂问题分析处理提出了新思路。在分析了航天器故障预测与健康管理方面存在的难点以及机器学习优势基础上,提出了面向机器学习建模的航天器健康管理平台设计方案与方法,分析了多语言融合的健康管理算法模型构建、基于分布式的健康管理计算服务引擎等关键技术,并以某卫星电源系统太阳电池阵功率预测等案例详细说明平台实际应用情况,验证结果表明研究成果能够为基于机器学习建模的航天器健康管理技术研究与应用提供技术参考,最终提高卫星、空间站等航天器的安全性。     

基于高效通道注意力机制和特征融合网络的冠心病诊断算法研究

针对冠心病重要特征不确定、诊断模型预测性能低等因素而导致冠心病早期诊断精度低的问题,提出一种基于高效通道注意力机制和特征融合的网络。通过XGBoost(eXtreme Gradient Boosting)来确定冠心病重要特征,设计数据生成图片的特征组合算法以适用该模型;为提高诊断模型预测性能,采用可以提升模型学习能力和特征利用率的高效通道注意力机制模块和特征融合模块。实验结果表明,在UCI克利夫兰心脏病数据集上,与其他诊断算法相比,该算法优于传统机器学习方法,预测精度可达100%且稳定性好。     

基于不相似性的软件缺陷预测算法

软件缺陷预测是典型的类不均衡学习问题,其中有缺陷的样本数量远少于无缺陷的样本数量,但有缺陷的样本通常是预测的重点。现有的软件预测模型大多建立在基于静态度量元的软件缺陷数据集上,重点关注如何平衡类分布,而忽略了数据集中属性特征对软件缺陷的判别能力。当软件缺陷数据集中的属性特征对类目标概念缺乏判别能力时,传统机器学习算法难以构建有效的软件缺陷预测模型,从而无法获得有效的预测性能。为此,提出了一种基于不相似性的软件缺陷预测算法,通过改善软件缺陷数据集中属性的判别能力,进而提升软件缺陷预测性能。实验证明：基于不相似性的软件缺陷预测算法能够有效地改善传统机器学习算法在软件缺陷数据集上的预测性能。     

基于QPSO-SVM算法的SELDI-TOF质谱数据分析

生物信息学领域的微阵列分析、质谱数据分析等大规模机器学习问题的不断涌现,对已有的特征选择算法提出了严峻的挑战,迫切需要研究适应于高维小样本特征的、准确性和运行效率等综合性能较好的、新的特征选择算法。将基于量子粒子群算法(QPSO)与SVM结合,并将建立的诊断模型用于生物标记物的选择。实验结果表明,新的基于量子粒子群算法建立的模型不仅具有良好的预测精度,而且在速度上有大幅的提高。     

基于优化组合模型的PM2.5浓度预测

为精确预测出具有非线性、非平稳的PM2.5时序数据，提出基于PSO-VMD-LSTM的组合模型。融合机器学习优化算法和深度学习技术，其中利用以包络熵为适应度函数的PSO机器学习算法对VMD分解过程中的惩罚因子和模态个数进行迭代寻优，基于分解处理后的数据进行LSTM深度学习模型预测。构建两种经典分解组合模型作为对照，结果表明，在相同迭代次数情况下，时序分解处理后的LSTM预测比未分解时的预测精度和效果都有明显改善；与经典分解组合模型相比，该模型在准确度和评估指标上均取得最佳预测效果，在PM2.5浓度预测上具有一定普适性。     

基于机器学习算法的寿命预测与故障诊断技术应用与发展综述

寿命预测与故障诊断作为复杂装备系统可靠性分析中的两类重要问题,基于数据驱动的机器学习分析方法具有良好的工程效果。本文系统地从故障预测与寿命估算及后续健康管理的实际工程需求出发,深入分析该类型系统因性能衰退出现的早期故障诊断与维护时间确定的共性难点问题并深度挖掘其所对应的关键科学问题,对机器学习算法在其中的应用与研究进行综述,重点阐述了人工神经网络、支持向量机等机器学习算法,对于完善可靠性分析方法,进一步推动机器学习算法在可靠性工程领域的运用具有一定的指导意义。     

基于利用BP神经网络进行Stacking模型融合算法的电力非节假日负荷预测研究

短期负荷预测尤其是非节假日负荷预测对提升电力系统整体调度、支撑电网运营工作起着十分关键的作用。目前针对非节假日负荷预测的理论、方法和应用层出不穷,但是预测精度和使用范围都受到一定限制,并且经济发展对短期负荷预测的精度提出越来越高的要求,传统的机器学习算法已经难以满足人们的需求。为了提高负荷预测的精度,本文提出了利用BP神经网络进行Stacking模型融合算法,它是基于集成学习的思想,首先挑选五种预测精度较高的单模型,然后利用Stacking模型融合方法将其集成为预测精度更高的综合模型。本文采用此算法预测某省2018年非节假日负荷,结果表明该算法可以有效提高预测精度。     

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。     

煤矿井下安全监控分站的设计及其仿真实现

为了设计一种具有低成本、低功耗、易操作、功能强且可靠性高的煤矿井下安全分站,针对煤矿安全生产实际,文章提出了采用MCS-51系列单片机为核心、具有CAN总线通信接口的煤矿井下安全监控分站的设计方案;首先给出煤矿井下安全监控分站的整体构架设计,然后着重阐述模拟量输入信号处理系统的设计过程,最后说明单片机最小系统及其键盘、显示、报警、通信等各个组成部分的设计;为验证设计方案的可行性与有效性,使用Proteus软件对设计内容进行仿真验证,设计的煤矿井下安全监控分站具有瓦斯、温度等模拟量参数超标报警功能和电机开停、风门开闭等开关量指示功能;仿真结果表明:设计的煤矿井下安全监控分站具有一定的实际应用价值.     

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.     

View-based model-driven architecture for enhancing maintainability of data access services

In modern service-oriented architectures, database access is done by a special type of services, the so-called data access services (DAS). Though, particularly in data-intensive applications, using and developing DAS are very common today, the link between the DAS and their implementation, e.g. a layer of data access objects (DAOs) encapsulating the database queries, still is not sufficiently elaborated, yet. As a result, as the number of DAS grows, finding the desired DAS for reuse and/or associated documentation can become an impossible task. In this paper we focus on bridging this gap between the DAS and their implementation by presenting a view-based, model-driven data access architecture (VMDA) managing models of the DAS, DAOs and database queries in a queryable manner. Our models support tailored views of different stakeholders and are scalable with all types of DAS implementations. In this paper we show that our view-based and model driven architecture approach can enhance software development productivity and maintainability by improving DAS documentation. Moreover, our VMDA opens a wide range of applications such as evaluating DAS usage for DAS performance optimization. Furthermore, we provide tool support and illustrate the applicability of our VMDA in a large-scale case study. Finally, we quantitatively prove that our approach performs with acceptable response times.     

A pragmatic multi-method investigation of discrepant technological events: Coping,attributions, and ‘accidental’ learning

Discrepant technological events or situations that entail a problem, a misunderstanding or a difficulty with the Information Technology (IT) being employed, are common in the workplace, and can lead to frustration and avoidance behaviors. Little is known, however, about how individuals cope with these events. This paper examines these events by using a multi-method pragmatic approach informed by coping theory. The results of two studies – a critical incident study and an experiment – serve to build and test, respectively, a theoretical model that posits that individuals use a variety of strategies when dealing with these events: they experience negative emotions, make external attributions, and adopt engagement coping strategies directed at solving the event, eventually switching to a disengagement coping strategy when they feel they have no control over the situation. Furthermore, users’ efforts may result in ‘accidental’ learning as they try to overcome the discrepant IT events through engagement coping. The paper ends with a discussion of the results in light of existing literature, future opportunities for research, and implications for practice.