一种改进的变步长自适应GSO算法

基本萤火虫群优化(GSO)算法在求解全局优化问题时,存在收敛速度慢、求解精度不高等问题。为此,提出一种变步长自适应GSO算法。该算法在一定程度上可以避免GSO算法过早陷入局部最优,且步长随迭代次数的增加而自适应地调整,从而使算法在后期获得精度更高的解。运用6个标准测试函数进行实验,结果表明,与GSO算法相比,该算法的收敛速度及精度均有明显提高。     

基于混合变异的萤火虫群优化算法

基本萤火虫群优化GSO(Glowworm Swarm Optimization)算法在求解函数全局寻优问题时,存在后期收敛速度慢、容易陷入局部极值等问题。为此,提出一种基于混合变异的萤火虫群优化算法。该算法用混沌变异和边界变异来增加种群的多样性,避免算法陷入局部最优,且能使算法获得精度更高的解。运用六个标准测试函数进行测试,结果表明,改进后的萤火虫群优化算法比基本GSO算法具有更高的寻优速度、寻优精度和收敛率。     

带交尾行为的混沌人工萤火虫优化算法

针对基本萤火虫优化(GSO)算法在求解全局优化问题存在易陷入局部极小值、收敛速度慢和求解精度不高等缺陷,首先对基本萤火虫优化算法采用混沌搜索技术进行初始化,使算法获得质量较高且分布较均匀的初始解,在此基础上再引入交尾行为,提出了一种带交尾行为的混沌萤火虫优化算法(MCGSO)。该算法在一定程度上防止了基本GSO算法易陷入局部最优,且能够获得精度更高的解甚至可达到理论最优解。最后,通过对8个标准测试函数进行测试,测试结果表明,带交尾行为的混沌萤火虫优化算法比基本萤火虫优化算法有更高的收敛速度和求解精度。     

一种基于差分策略的群搜索优化算法

针对群搜索优化(Group Search Optimizer,GSO)算法易陷入局部最优、收敛速度较慢、收敛精度较低等问题,提出一种基于差分策略的群搜索优化(Differential Ranking-based Group Search Optimizer,DRGSO)算法。主要进行两方面改进:1)按照适应度值的大小对种群进行排序,适当增加发现者的数目,使种群能够获得更好的启发式信息,加快了算法的收敛速度,有效地避免了算法陷入局部最优;2)在发现者搜索过程中,引入4种不同的差分变异策略,提高了算法的收敛精度,增强了算法的群体多样性在。11组国际标准测试函数上的实验测试结果显示,与GA,GSO,PSO算法相比,DRGSO算法具有较强的全局搜索能力以及局部资源勘探能力,算法整体收敛性能明显提高。     

具有捕食策略的混合随机优化算法及其多极值函数优化

SAGACIA是一种混合随机优化算法,该算法虽已吸收了模拟退火算法、遗传算法和趋化性算法的优点,但搜索过程中仍存在收敛速度慢以及采用固定步长影响搜索精度的缺点,而捕食搜索策略通过限制的调节能较快锁定最优区域,从而提高收敛速度。结合两者的优缺点,提出一种具有捕食搜索策略的自适应调整步长SAGACIA算法,改进后的算法通过捕食搜索策略平衡了算法的局域搜索和全局搜索,提高了收敛速度;邻域搜索采用自适应步长,避免了最优解附近的震荡,提高了搜索精度。实验仿真结果表明,改进后的SAGACIA算法具有较快的收敛速度和较高的寻优精度,证明了算法改进的有效性和可行性。     

自适应步长萤火虫群多模态函数优化算法

针对萤火虫群优化(GSO)算法优化多模态函数存在收敛速度慢和求解精度低等缺陷,提出一种自适应步长萤火虫群多模态函数优化算法((SASGSO)。该算法解决了萤火虫群优化(GSO)算法优化多模态函数所存在的不足;同时SASGSO算法也可找到多模态函数的所有极值点。数值实验仿真表明,该算法具有操作简单、易理解、收敛速度快和求解精度高等优点。     

正余混沌双弦鲸鱼优化算法

针对基本鲸鱼优化（WOA）算法容易陷入局部最优解和收敛速度慢的缺点,提出一种正余混沌双弦鲸鱼优化（CSCWOA）算法。为鲸鱼的觅食加入信息交流强化机制,并在捕食引入正余混沌双弦机制,通过正弦全局搜索减少寻优盲点,余弦局部开发加快收敛速度,以及混沌算子增强跳出局部最优的能力,个体信息在种群中双弦混沌交叉快速传播。通过仿真对比实验,证明了该算法具有较好的收敛速度、求解精度和稳定性。     

应用反向学习和差分进化的群搜索优化算法

针对标准群搜索优化算法在解决一些复杂优化问题时容易陷入局部最优且收敛速度较慢的问题,提出一种应用反向学习和差分进化的群搜索优化算法(Group Search Optimization with Opposition-based Learning and Diffe-rential Evolution,OBDGSO)。该算法利用一般动态反向学习机制产生反向种群,扩大算法的全局勘探范围;对种群中较优解个体实施差分进化的变异操作,实现在较优解附近的局部开采,以改善算法的求解精度和收敛速度。这两种策略在GSO算法中相互协同,以更好地平衡算法的全局搜索能力和局部开采能力。将OBDGSO算法和另外4种群智能算法在12个基准测试函数上进行实验,结果表明OBDGSO算法在求解精度和收敛速度上具有较显著的性能优势。     

变步长自适应萤火虫群多模态函数优化算法

针对萤火虫群优化（GSO）算法优化多模态函数存在收敛速度慢和求解精度不高等缺陷,提出一种变步长自适应萤火虫群优化算法（CSGSO）。该算法主要思想是在GSO算法中引入搜索成功与失败概念,在每次迭代中萤火虫个体据其搜索成功或失败,加大或减小其搜索步长,使算法具有动态自适应性。实验结果表明,该算法可有效地解决GSO算法优化多模态函数存在收敛速度慢和求解精度不高的问题,增强了GSO算法优化多模态函数的性能;与其他算法相比,提出的算法具有操作简单、容易理解、收敛速度快和求解精度高等优点。     

基于适应性动态步长的变异果蝇优化算法

针对基本果蝇优化算法（FOA）容易陷入局部最优值、后期收敛速度变慢和收敛精度较低的缺点,提出了一种基于适应性动态步长的变异果蝇优化算法（MFOAADS）。首先,利用佳点集法选取种群初始位置,降低算法初始点选取的随机性和陷入局部最优值的概率;然后,采用适应性动态步长优化策略,提高收敛速度和求解精度;最后,若算法陷入了早熟,则对种群最优个体按一定概率执行柯西变异扰动,赋予其跳出局部最优的能力。经5个经典函数测试表明,固定迭代次数时MFOAADS的收敛精度与收敛速度明显优于FOA;固定目标精度时,MFOAADS相对于FOA平均迭代次数有着大幅下降且成功率达97%以上。实验结果表明,所提算法求解精度、运行效率以及可靠性相对于基本FOA算法都有着显著提高。     

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。