群搜索优化中基于分布熵的多样性控制

通过分布熵和方差的对比分析,建立群搜索算法中多样性的定量描述,针对优化计算中的多模态情况提出个体空间中的模式分类问题,并提出一种分类方法.在聚类分析的基础上得到搜索空间中个体的类分布,进而得到由分布熵描述的多样性指标,并据此控制个体间的聚散来实现对多样性的控制.给出一种控制多样性的一阶聚散控制算法,对其参数设置进行分析.仿真实验表明该算法优于标准遗传算法、标准粒子群算法以及无分类过程的集聚性搜索算法.     

一种基于均匀分布策略的NSGAII算法

针对局部搜索类改进型非劣分类遗传算法（Nondominated sorting genetic algorithm Ⅱ,NSGAⅡ）计算过程中种群分布不均的问题,提出一种基于均匀分布的NSGAⅡ（NSGAⅡ based on uniform distribution,NSGAⅡ-UID）多目标优化算法.首先,该算法将种群映射到目标函数对应的超平面,并在该平面上进行聚类以增加解的多样性.其次,为了提高解的分布性,将映射平面进行均匀分区.当分段区间不满足分布性条件时,需要激活分布性加强模块.与此同时在计算过程中分段区间可能会出现种群数量不足或无解的状况,为了保证每个区间所选个体数目相同.最后,采用将最优个体进行极限优化变异的方法来获得缺失个体.实验结果显示该算法可以保证种群跳出局部最优且提高收敛速度,并且在解的分布性和收敛性方面均优于文中其他多目标优化算法.     

一种复杂度约束下基于宏块优先顺序的运动估计优化算法

在实际应用中,视频编码算法不仅需要提供最好的编码效率,而且还需要自动地适应各种平台不同的计算能力约束.这是一个在复杂度约束下的率失真优化问题.针对视频编码消耗计算资源最多的运动估计过程,提出一种复杂度约束下的优化算法.该算法对运动估计的失真度和复杂度建模,并通过该模型决定每个宏块的预测失真度一复杂度斜率(distortion-complexity slope,DC-slope),以此决定各个宏块运动估计的优先顺序,然后通过一个常微分方程建立控制参数与计算复杂度之间的关系,准确地控制运动估计的计算复杂度.通过实验比较,本算法不仅可以自适应地调整运动估计的计算复杂度,而且能在不同的复杂度约束下提供优化的编码性能.     

利用种群扩张与稀疏化策略改进NSGA-II-DE算法

NSGA-II-DE算法是在NSGA-II算法的基础上利用DE算法的收敛速度快、鲁棒性高的特性得到的改进算法,该算法提高了原算法的收敛速度,同时也降低了原算法对参数的依赖性.然而,原算法的解群分布性却没有得到提高.鉴于此,提出一种基于种群扩张与稀疏化策略的改进型NSGA-II-DE算法.该算法利用种群扩张增加候选解的数量,再利用稀疏化策略从候选解中选出使得整体分布尽可能均匀的最优解.种群扩张通过在进化最后的若干代保留每代中的第一非支配面上的个体来实现.在迭代结束后,对种群进行非支配排序,去除第一非支配面以外的个体,以提高解群质量.进行稀疏化处理,即对扩张后的全部个体按目标向量的某一维度排序,再筛选出相邻间距最接近期望距离的个体,以达到改善解群分布性的目的.仿真实验表明,所提出的算法在改善原算法的解群分布性上表现优异,但算法的时间和空间复杂度较原算法有所增加.     

流行病在空间分布人群中的传播模型

研究流行病传播规律,考虑了流行病在空间分布人群中的随机传播过程。目前,人们通常应用复杂网络来模拟人群中的流行病传播过程,但是,复杂网络模型中没有空间、距离等概念,在现实中,人群通常是空间分布,即空间关系是流行病传播的重要影响因素。针对上述问题,提出一种流行病传播的新模型,使人群分布在一个有界区域内,并创新性地引入了距离的概念,改善了复杂网络模型忽视空间因素的缺陷。利用模型建构,通过编写Matlab程序对整个传播过程进行仿真,分析了个体针对病毒所产生的暂时性免疫力对流行病传播过程的影响。表明仿真结果与实际现象吻合。结果证明将空间因素纳入模型更为合理。     

基于柯西分布和父种轮换机制的种子优化算法

针对目前种子优化算法存在的空间探索能力不足、后代个体分布多样性较弱的问题,文中提出基于柯西分布和父种轮换机制的种子优化算法.首先,构建基于柯西分布的种群分布模型,用于前期探索阶段,提升算法的全局搜索能力.然后,建立基于赌轮法的父种轮换机制,提高后代种群的多样性.最后,构建个体距离阈值、分布方差和后代比例的自适应调整机制...     

基于多重分形主曲线模型多目标演化算法研究

为了克服目前模型多目标演化算法多采用PCA,local PCA等线性建模方法,存在模型拟合效果不理想、对建模参数敏感等问题,提出一种基于多重分形的主曲线模型多目标演化算法( multifractal based principal curve multi-objective evolutionary algorithm,MFPC-MOEA).算法采用主曲线方法对解集分布进行非线性建模,通过建立种群个体分布概率模型,生成目标空间均匀分布的个体,保证优化结果的多样性.另外算法通过多重分形方法分析个体在解集空间中的分布,设计了基于多重分形谱的模型演化多目标算法建模开始评测标准,同时采用多重分形方法评估算法收敛程度,设计相关的演化多目标优化算法停止策略.新算法采用国际公认的ZDT,DTLZ测试函数进行实验验证,并与NSGA-II,MOEA/D,PAES,SPEA2,RM-MEDA经典演化多目标优化算法进行了实验比较.实验结果表明,该算法在HV,SPREAD,IGD,EPSIION性能指标上均有较好的表现.说明通过引入多重分形策略和主曲线建模方法,在一定程度上提高了解的质量,为求解多目标优化问题提供新的思路.     

基于参考点选择策略的改进型NSGA-III算法

针对多目标进化算法忽视种群在决策空间的分布信息,未考虑待优化问题Pareto前沿形状的问题,文中提出基于参考点选择策略的改进型NSGA-III算法.首先,根据种群在决策空间的分布特征,借助信息论中的熵思想,计算相邻两代种群的熵差,判定种群的进化阶段.然后,根据种群在目标空间的分布特征,借助参考点关联个体数目的统计信息,评估参考点的重要性.最后,在种群进化的中后期,依据参考点的重要性特征剔除冗余的无效参考点,使保留的参考点适应种群规模与Pareto前沿面,利用筛选后的参考点引导种群进化方向,加快算法收敛及优化效率.在测试函数集上的对比实验表明,文中算法在收敛性和分布性上均较优.     

MMDR算法的优化以及在证券仿真中的应用

设计了一种降低了时间复杂度和空间复杂度的横向拟正则规则双层的MMDR算法,介绍了利用这个优化的算法在股市数据中得到的正则规则进行股票价格预测的方法,以及如何将此算法的运行过程中产生的大量规则应用于证券交易仿真复杂适应系统的“个体”建模中,以解决证券交易仿真系统需要大量互不相同的个体建模的问题。     

基于代理模型的差分进化约束优化

针对耗时计算目标函数的约束优化问题,提出用代理模型来代替耗时计算目标函数的方法,并结合目标函数的信息对约束个体进行选择,从而提出基于代理模型的差分进化约束优化算法。首先,采用拉丁超立方采样方法建立初始种群,用耗时计算目标函数对初始种群进行评估,并以此为样本数据建立目标函数的神经网络代理模型。然后,用差分进化方法为种群中的每一个亲本产生后代,并对后代使用代理模型进行评估,采用可行性规则来比较后代与其亲本并更新种群,根据替换机制将种群中较劣的个体替换为备用存档中较优的个体。最后,当达到最大适应度评估次数时算法停止,给出最优解。该算法与对比算法在10个测试函数上运行的结果表明,该算法得出的结果更精确。将该算法应用于工字梁优化问题的结果表明,相较于优化前的算法,该算法的适应度评估次数减少了80%;相对于FROFI（Feasibility Rule with the incorporation of Objective Function Information）算法,该算法的适应度评估次数减少了36%。运用所提算法进行优化可以有效减少调用耗时计算目标函数的次数,提升优化效率,节约计算成本。     

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。     

How do children do mathematics with LOGO?

Abstract  This paper considers some results of a study designed to investigate the kinds of mathematical activity undertaken by children (aged between 8 and 11) as they learned to program in LOGO. A model of learning modes is proposed, which attempts to describe the ways in which children used and acquired understanding of the programming/mathematical concepts involved. The remainder of the paper is concerned with discussing the validity and limitations of the model, and its implications for further research and curriculum development.