求解舰船电力系统网络重构的贪婪DPSO算法

针对舰船电力系统的网络重构,建立了故障恢复的离散模型.提出基于简单贪婪法、概率贪婪法两种离散微粒群优化算法,分析了参数对离散化过程的影响.舰船电力系统网络故障恢复算例显示:该方法能获得更好的故障恢复方案;参数选取合适的概率贪婪法能有效地克服微粒群算法易于陷入局部极值的缺点,具有优良的收敛性能.     

依概率收敛的改进粒子群优化算法

粒子群优化算法是一种随机优化算法,但它不依概率1收敛到全局最优解。因此提出一种新的依概率收敛的粒子群优化算法。在该算法中,首先引入了具有探索和开发能力的两个变异算子,并依一定概率对粒子当前最好位置应用这两个算子,然后证明了该算法是依概率1收敛到ε-最优解。最后,把该算法应用到13个典型的测试函数中,并与其他粒子群优化算法比较,数值结果表明所给出的算法能够提高求解精度和收敛速度。     

基于克隆选择粒子群算法的多用户检测

对离散粒子群优化算法(DPSO)进行了改进,提出一种克隆选择粒子群算法(CSDPSO).该算法提高了离散粒子群优化算法的局部搜索能力,保持了很强的全局搜索能力.本文将该算法应用到多用户检测中,用以解决Verdu提出的最优多用户检测所存在的计算量过大无法工程实现的问题.仿真证明,该算法比标准的离散粒子群算法具有更好的搜索能力.基于该算法的多用户检测器比基于DPSO的多用户检测器,无论在误码率性能还是收敛速度方面都有明显改善.     

带蜂群策略的粒子群算法训练人工神经网络研究

提出一种带蜂群策略的粒子群优化算法,并将算法应用于神经网络训练。将蜂群优化算法中引领蜂和观察蜂的收益评价与贪婪选择策略以及侦察蜂的探索新解策略引入到粒子群优化算法中。粒子在飞行时,按维度对粒子速度和位置进行更新,根据对收益的评价,只接收能够提高解适应值的位置,从而加快了收敛速度;如果粒子多次迭代均无法改进解,则在解空间中随机搜索新的位置,增强算法跳出局部极值的能力。在求解异或问题、奇偶校验和编码解码问题的神经网络上进行了仿真,结果表明,该算法优于BP算法、粒子群优化算法和蜂群优化算法。     

基于Inver-Over算子的改进离散粒子群优化算法

离散粒子群算法能充分利用粒子的局部极值和全局极值信息,但收敛速度慢、精度低;Inver-Over算子收敛速度快、精度高,但学习具有盲目性。结合二者优点,文中提出一种基于Inver-Over算子的改进离散粒子群优化算法。为防止早熟收敛,引入局部最优子群的概念,使粒子向局部最优子群中粒子学习而不是向个体局部最优学习。引入3个参数:学习选择概率用以确定粒子的学习对象,代数阈值确定何时向全局最优粒子学习,局部最优子群比决定最优子群的规模。讨论这些参数的选择原则,并给出相应参考选择范围。研究表明,文中算法与普通离散粒子群优化算法和郭涛算法相比,收敛速度和求解精度都有较大提高。     

求解TSP问题的伪贪婪离散粒子群优化算法

以旅行商问题为例,提出一种基于元胞结构的伪贪婪离散粒子群优化算法.为了体现粒子对环境的感知能力,设计了伪贪婪的粒子位置修改操作算子,为了反映粒子间不同学习能力,体现粒子的个体差异性,设计了3种学习算子来提高算法的局部求精能力,为了更好地保持粒子群的多样性,采用了元胞结构作为粒子群的种群拓扑和邻城结构,这些策略使算法在空...     

含维变异算子的量子粒子群算法

针对粒子群优化(PSO)算法搜索空间有限,容易陷入局部最优点的缺陷,提出一种新的量子粒子群优化算法--含维变异算子的量子粒子群算法(QPSODMO).计算每一维的收敛度,以一定的概率对收敛度最小的维进行变异,让所有粒子在该维上的位置重新均匀分布在可行区域上.对测试函数所做的对比实验表明,所提出的QPSODMO增强了全局搜索能力,克服了PSO算法易于收敛到局部最优的缺点,也优于原始的量子粒子群算法.     

一种求解离散优化问题的粒子群算法

粒子群算法在求解连续变量问题有了比较成功的应用,但是对离散变量问题方面的应用研究却相对滞后.针对离散优化问题,提出了一种遗传粒子群算法.算法使用了交叉、变异等遗传算子替代传统粒子群算法的速度-位移公式,克服了传统粒子群算法对组合优化问题编码时出现的信息冗余的问题,提高了搜索效率.应用该算法求解了车辆路径问题,实验结果表明,该算法具有较好的全局收敛能力和较快的收敛速度.在同等条件下,求解效果要明显好于遗传算法和基于速度位移公式的粒子群算法     

具有自适应邻域探测机制的改进型PSO算法

针对基本PSO算法在全局优化中易陷入局部极值和收敛精度低的不足,分析了基本PSO算法早熟收敛的原因,提出具有自适应邻域探测机制的改进型粒子群优化(ANE-PSO)算法.该算法在进化过程中以概率总体递减的方式,选择部分粒子对最佳位置按半径总体递减的规则进行邻域探测,并引入速度变异算子,提高种群的多样性,增强了算法的全局搜索能力.并证明它依概率1收敛到全局最优解.通过与其它三个改进算法比较.结果表明ANE-PSO具有较好的全局搜索能力,收敛速度较快,稳定性较好,且没有增加时间复杂度,较有效的避免了早熟收敛问题.     

粒子群算法的交互性与随机性分析

在现有分析结论的基础上, 分别采用优化的凸性理论和概率收敛理论, 分析了粒子群 (Particle swarm optimization, PSO) 算法的交互性和随机性对算法的影响. 分析得出, 在不考虑随机性的条件下, 当 PSO 算法优化单峰函数时, 交互性使粒子最终收敛于全局最优粒子位置; 当 PSO 算法优化多峰函数时, 交互性未必使粒子最终收敛于全局最优位置. 但如果考虑随机性, 算法优化的目标函数无论是单峰函数还是多峰函数, 粒子都会依概率收敛于最优位置. 通过基准函数的实验验证了分析的结论.     

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.