网络结构增长的极端学习机算法

针对极端学习机(extreme learning machine,ELM)结构设计问题,基于隐含层激活函数及其导函数提出一种前向神经网络结构增长算法.首先以Sigmoid函数为例给出了一类基函数的派生特性:导函数可以由其原函数表示.其次,利用这种派生特性提出了ELM结构设计方法,该方法自动生成双隐含层前向神经网络,其第1隐含层的结点随机逐一生成.第2隐含层的输出由第1隐含层新添结点的激活函数及其导函数确定,输出层权值由最小二乘法分析获得.最后给出了所提算法收敛性及稳定性的理论证明.对非线性系统辨识及双螺旋分类问题的仿真结果证明了所提算法的有效性.     

ELM算法中随机映射作用的实验研究

通过实验研究ELM算法中随机映射的作用及神经网络中隐含层结点个数对网络泛化能力的影响.在35个数据集上进行实验,针对不同的数据集,找到网络的最优精度所对应的隐含层结点个数.实验结果表明,当随机映射使数据升维到一定维数时,网络性能得到提高.     

基于互信息的贝叶斯网络结构学习算法

贝叶斯网络结构学习是贝叶斯网络构建的核心,有效的结构学习算法是构建最优网络结构的基础。基于此,提出一种基于互信息的贝叶斯网络结构学习算法,该算法可以挖掘出数据集各属性中存在的隐含依赖关系,适时地对数据集进行降维操作,从而提高算法的效率,并可保证结果的准确性。实验结果表明,与常用的依赖分析算法SGS相比,在结果相似的情况下,该算法执行效率更高。     

集成重复训练极限学习机的数据分类

极限学习机是一种随机化算法,它随机生成单隐含层神经网络输入层连接权和隐含层偏置,用分析的方法确定输出层连接权。给定网络结构,用极限学习机重复训练网络,会得到不同的学习模型。本文提出了一种集成模型对数据进行分类的方法。首先用极限学习机算法重复训练若干个单隐含层前馈神经网络,然后用多数投票法集成训练好的神经网络,最后用集成模型对数据进行分类,并在10个数据集上和极限学习机及集成极限学习机进行了实验比较。实验结果表明,本文提出的方法优于极限学习机和集成极限学习机。     

小数据集的贝叶斯网络结构学习

针对直接基于小数据集贝叶斯网络结构学习不可靠, 以及目前对小数据集的处理只强调扩展而忽略对扩展数据的修正等, 提出了将扩展与修正相结合的小数据集处理机制, 以及在此基础上的基于结点排序和局部打分--搜索的贝叶斯网络结构学习方法. 可不需要完全结点顺序的先验知识, 但能够结合专家的部分结点顺序信息. 实验结果显示了这种方法的有效性和可靠性.     

基于模型输出敏感度分析法的动态RBF神经网络设计

针对一般RBF神经网络在学习过程中网络结构不能改变的问题,提出一种动态RBF神经网络结构设计方法．算法的实质是利用敏感度分析法（SA）对神经网络模型的输出进行分析,通过判断隐含层神经元的输出对整个网络输出的影响,删除RBF隐含层中冗余的神经元,实现对神经网络的动态修剪．非线性函数逼近结果及动态系统建模结果表明,该动态RBF神经网络具有较好的性能;与最小RBF（MRBF）神经网络相比,采用所提算法能得到更小的检测误差和更短的训练时间,最终网络结构紧凑．     

基于灵敏度分析法的ELM剪枝算法

针对极端学习机(ELM)网络结构设计问题,提出基于灵敏度分析法的ELM剪枝算法.利用隐含层节点输出和相对应的输出层权值向量,定义学习残差对于隐含层节点的灵敏度和网络规模适应度,根据灵敏度大小判断隐含层节点的重要性,利用网络规模适应度确定隐含层节点个数,删除重要性较低的节点.仿真结果表明,所提出的算法能够较为准确地确定与学习样本相匹配的网络规模,解决了ELM网络结构设计问题.     

一种基于互信息变量选择的极端学习机算法

针对回归问题中存在的变量选择和网络结构设计问题, 提出一种基于互信息的极端学习机(ELM) 训练算法, 同时实现输入变量的选择和隐含层的结构优化. 该算法将互信息输入变量选择嵌入到ELM网络的学习过程之中, 以网络的学习性能作为衡量输入变量与输出变量相关与否的指标, 并以增量式的方法确定隐含层节点的规模.在Lorenz、Gas Furnace 和10 组标杆数据上的仿真结果表明了所提出算法的有效性. 该算法不仅可以简化网络结构, 还可以提高网络的泛化性能.

     

基于敏感度方差重要性的RBF 神经网络结构优化算法

针对RBF 神经网络的结构设计问题, 提出一种基于输出敏感度方差重要性的结构优化算法. 首先, 检验网络隐层节点的输出敏感度在样本集上的方差是否与零有显著差异, 以此作为依据增加或删除相应的隐层节点; 然后,对调整后的网络参数进行修正, 使网络具有更好的拟合精度和收敛性; 最后, 对所提出的优化算法进行仿真实验, 结果表明, 所提出的算法可根据研究对象自适应地调整RBF 的网络结构, 具有良好的逼近能力和泛化能力.

     

随机权分布对极限学习机性能影响的实验研究

极限学习机是一种训练单隐含层前馈神经网络的算法,它随机初始化输入层的权值和隐含层结点的偏置,用分析的方法确定输出层的权值。极限学习机具有学习速度快、泛化能力强的特点。很多研究都用服从[－1,1]区间均匀分布的随机数初始化输入层权值和隐含层结点的偏置,但没有对这种随机初始化合理性的研究。用实验的方法对这一问题进行了研究,分别研究了随机权服从均匀分布、高斯分布和指数分布对极限学习机性能的影响。研究发现随机权的分布对极限学习机的性能的确有影响,对于不同的问题或不同的数据集,服从[－1,1]区间均匀分布的随机权不一定是最优的选择。研究结论对从事极限学习机研究的人员具有一定的借鉴作用。     

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.