基于GEP-BP网络集成的蛋白质二级结构预测方法研究*

为提高蛋白质二级结构预测的精度,提出了一种基于GEP-BP网络集成的两层结构预测模型。首先利用基因表达式编程（GEP）的全局搜索能力同时进化设计BP网络的结构和连接权,并将进化最后一代的个体用BP算法进一步训练学习,然后采用组合方法将部分个体集成构成模型的第一层;根据神经网络输出之间具有相关性,用第二层网络对第一层的预测结果进行精炼。用PDBSelect25中的36条蛋白质共6 122个残基进行测试,结果表明提出的模型能有效预测蛋白质二级结构,将预测精度提高到73.02%。     

改进的新BRNN网络集成及其二级结构预测的研究

为提高二级结构预测精度,试用神经网络集成法预测.针对BRNN网络结构复杂、收敛时间长、参数多的缺点,本文提出一种改进的新BRNN网络,删除BRNN左、右子网络的隐层,直接将输入连接到状态层,并采用BP改进算法中的弹性算法训练.以90条蛋白质序列共15 377个氨基酸交叉验证,仿真结果表明新网络可以有效地缩短收敛时间,新BRNN集成预测二级结构效果较好.     

蛋白质二级结构的协同训练预测方法*

针对蛋白质二级结构机器学习预测方法,忽略氨基酸疏水性特征以及氨基酸之间的长程作用和准确率不高的现状,进行了比较实验分析。采用氨基酸对应的疏水能值替换蛋白质中相应的氨基酸,得到疏水能值的序列实验结果表明,用长的疏水能值序列,训练BP网络,对长程作用起主导的E结构的预测效果好。由于Profile编码特征和疏水能值特征是独立的冗余视图,基于协同训练思想,提出Cotraining算法。该算法的主要步骤是在Profile特征空间训练SVM分类器,在疏水性特征空间训练BP神经网络分类器,协同对氨基酸二级结构进行预测     

基于集成BP网络的人脸识别研究

在对人脸图像使用小波变换进行数据压缩的基础上,使用PCA进行特征提取,再将特征输入集成BP神经网络实现对人脸图像的识别。集成BP网络将多分类问题转换为多个相互独立的二分类问题,在提高网络泛化能力的同时缩短了网络的训练时间。另外,集成网络通过增添子网络或者重新训练子网络的方法解决了网络"失忆"问题,使其具有增量式学习的能力。通过在ORL人脸库上仿真的实验,证明了集成网络的人脸识别以及增量学习都具有良好的性能。     

集成型神经网络手写体数字识别

采用Kirsch边缘检测算子对手写体数字进行特征提取，分别得到数字的水平、垂直、左右对角线方向特征以及全局特征，然后利用5个改进的BP神经网络分类器分别对5种特征进行训练和分类，最后利用一个BP神经网络对5个子网络识别结果进行集成识别，取得了较好的实验效果。     

QPSO算法优化BP网络的网络流量预测

网络流量预测对于大规模网络的规划设计和网络资源管理等方面都具有积极的意义,是网络流量工程重要组成部分。结合QPSO算法和BP神经网络的优势,采用QPSO算法对BP神经网络的权值和阈值进行优化,并利用历史记录训练BP网络。仿真实验表明,与PSO训练的BP网络以及直接用BP网络进行预测的模型相比,基于QPSO训练的BP网络流量预测模型具有更好的预测能力。     

基于级联神经网络的蛋白质二级结构预测

为提高蛋白质二级结构预测的精度,提出一种由两层网络构成的级联神经网络模型。第1层网络采用具有差异度的5个子网构成的网络模型,对第2层网络的输入编码进行改进。对PDBSelect25中的36条蛋白质共6 122个残基进行测试,结果表明,该模型能有效预测蛋白质二级结构,其预测精度分别比SNN, DSC, PREDSATOR方法提高5.31%, 1.21%和0.92%,平均预测精度提高到69.61%。     

基于Bagging集成学习的水华预测方法研究

随着经济社会的高速发展和工业化建设程度不断提高,水环境问题已经严重影响甚至威胁了人类的健康。近年来,国家大力推行水环境的预测预警,许多专家学者利用人工神经网络等智能方法在富营养化评价及水华预测中得到了较为广泛的运用,也取得了一定成效。然而,人工神经网络的性能受到样本训练算法等方面的影响,在选取合适的神经网络模型、算法以及设置参数麻烦、耗时。随着问题复杂程度的增加,单个网络的隐层节点数将增加很多,训练时间将大大增加,从而造成训练困难。且由于训练过度或不够,往往导致泛化能力较差。为解决此问题,本文在对湖库水华形成机理深入分析的基础上,建立了BP网络的水华预测模型,并利用Bootstrap采样技术获取不同的数据集,分别训练多个BP网络,最终将多个网络进行集成用于建立太湖流域水华预测模型。通过基于Bagging算法的集成学习,可以对样本包含的信息进行充分挖掘,更全面的刻画因素之间的相互联系和变化规律。实验表明基于Bagging算法的BP网络集成模型预测结果与单个BP网络模型预测结果对比,具有较高的预测能力,从而获得了相对理想的预测效果。     

基于集成BP神经网络的短期负荷预测

利用混沌相空间重构理论对负荷时间序列研究,用改进的C_C方法求得时间延迟τ和嵌入维数m,得到系统最大李雅普诺夫指数,证明其具有混沌特性.对样本数据相空间重构,构建多个BP神经网络的预测子模型,所有子模型同步预测的加权平均作为集成负荷预测值.在线采集负荷数据,利用增量式训练获取新的预测子模型,按“先入先出”顺序进行BP神经网络集成更新.将预测结果同普通BP神经网络预测结果进行对比,结果证明这种方法提高了预测精度.     

基于小波降噪和改进免疫优化的BP模型网络流量预测

为了实现大规模复杂网络的流量预测,并改善传统BP网络预测模型存在的收敛速度慢和容易陷入局部最优的缺陷,提出了一种基于小波降噪和改进人工免疫优化BP神经网络的网络流量模型;首先,描述了网络流量预测的基本原理;然后,采用小波包降噪法对网络流量原始采样序列进行降噪处理,在此基础上定义了采用BP网络进行网络流量预测的算法,在确定了神经网络的结构后,采用训练数据和改进的人工免疫优化算法对BP网络中的参数即权值和阀值进行优化,从而得到最终的BP网络流量预测模型;最后,采用1 800组样本中的1 200组训练数据对网络进行训练后得到最终的BP网络模型,再采用剩余的600组测试数据进行流量预测;实验结果证明结合人工免疫算法和BP网络的网络流量预测模型能实现大规模复杂网络的流量预测,且较传统方法相比,具有收敛速度快、训练时间短和预测精度高的优点。     

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。