基于熵的双群体遗传算法研究

提出了一种基于熵的双群体遗传算法.首先采用熵最大的方法产生两个初始化群体,使得初始化的个体尽可能均匀分布在遗传搜索空间.在一个群体中设计了基于熵最大的直接替代选择运算并采用高变异率提高遗传算法的全局探索能力.在另一个群体中采用逐渐减小的动态变异率提高遗传算法的快速局部搜索能力.两个群体之间的相互移民策略均衡了遗传算法的全局探索能力和快速局部搜索能力.实验显示,基于熵的双群体遗传算法对复杂多模函数寻优在全局收敛率和收敛速度上都具有一定的优势.     

基于多种编码的多群体遗传算法

为了有效地克服标准遗传算法（SGA）中的早熟收敛现象,提出了一种基于多种编码的多群体遗传算法,该方法是采用3个群体同时进行进化的策略,其中,第1个 本是采用浮点数编码方法,以使该群体具有较强的局部搜索能力,第2个群体是采用二进制编码方法,以使该群体具有较强的全局搜索能力。第3个群体为“精华种群”,用于保存算法在进化过程中产生的优秀个体,在进化过程中,还通过引入“移民”策略来交换3个群体中的优秀个体,以有效地增加群体的多样性,该算法不仅不易陷入局部收敛,还具有较强的跳出局部收敛的能力,且收敛速度较快,通过对一系列典型复杂多模函数进行的优化计算试验,结果证实了该方法的有效性和优越性。     

经纬度坐标下矿山微震震源深度的测定方法

针对经纬度坐标下矿山微震震源深度难以确定或误差较大的问题,提出了一种震源深度的测定方法。该方法在只利用微震P波走时的情况下,通过改进微震线性定位法计算微震震源的平面位置和发震时刻,然后通过震源到台站的震中距和微震走时,先进行TD模式拟合,在剔除错误数据后进行DT模式拟合,最后依据拟合直线的截距确定震源深度。实际应用结果表明,该方法能有效降低错误实测数据的干扰,提高震源深度的测定精度。     

文化遗传算法的研究及其在函数优化中的应用

为了提高遗传算法的性能,将遗传算法纳入到文化算法框架中组成群体空间和信念空间,提出一种新的优化算法。在群体空间的遗传进化过程中引入随机种群来增加算法的勘探能力,并组织较差个体依概率与信念空间中更新后的优秀个体进行交叉操作;在信念空间充分利用对优秀个体所包含信息的开采能力并采用耗散结构来提高整个空间的自组织能力,更新优秀个体,在很大程度上提高了算法的速度和效率。实验结果表明,新算法能有效地应用于函数优化。     

单纯形搜索在遗传算法中的融合研究

构造了单纯形混合遗传算法SM-HGA⁺。分析单纯形搜索算法,提出了单纯形交叉算子和K步随机单纯形搜索算子,并将单纯形搜索算法和这两个算子分别融入到最优微群体μP_B（t）、最差微群体μP_W（t）和普通群体P_C（t）,形成SM-HGA⁺。最优微群体中的单纯搜索算法提高算法的精度;最差微群体中的单纯形交叉算子加速最差个体向优秀个体进化;普通群体中K步随机单纯性搜索提高全局搜索速度,同时在普通群体采用大交叉概率的标准遗传算法,提高全局搜索能力。遗传算法测试函数验证算法SM-HGA⁺的正确性、效率。     

基于蜂群遗传算法的0-1背包问题

针对0-1背包问题,本文提出了基于蜂群遗传算法的优化求解方案。该算法包括两个种群,一个主要用于全局搜索,另一个主要用于局部搜索;每个个体采用二进制编码;采用最优个体交叉策略;对当前解的处理措施是将还未装入背包且性价比最好的物品装进背包,直至不能装为止;不符合约束条件的解采用诱变因子指导变异处理;遗传算子包括单点交叉算子、简单变异算子、主动进化算子和抑制算子。本算法充分发挥了遗传算法的群体搜索和全局收敛的特性,快速地并行搜索,有效地克服了经典遗传算法容易陷入局部最优问题。数值实验表明,该算法在求解0-1背包问题中取得了较好的效果,同样可以应用于其它的组合优化问题。     

病毒进化遗传算法的车辆调度优化模型

为了提高车辆调度优化效率,提出一种病毒进化遗传算法的车辆调度优化模型。建立车辆调度的数学模型,采用遗传算法对模型进行求解,并采用病毒群体感染主群体,主群体在历代个体间纵向传递信息以利于全局优化,病毒群体通过感染操作在同代个体间横向传递信息利于局部搜索,进行仿真对比实验。结果表明,病毒进化遗传算法较好地解决了标准遗传算法存在的不足,加快了车辆调度优化问题的求解效率,获得了更优的车辆调度方案,具有较高的应用价值。     

基于改进支持向量机的微震初至波到时自动拾取方法

微震初至波到时拾取是实现微震震源高精度定位的重要前提。传统的人工拾取方法效率低,而自动拾取方法在低信噪比条件下难以准确拾取初至波到时。针对上述问题,提出了一种基于改进支持向量机（SVM）的微震初至波到时自动拾取方法。首先,对原始微震数据进行归一化处理、线性校正和适当裁剪,将微震数据的振幅、能量和相邻时刻的能量比作为特征对数据标记不同类别;然后采用粒子群优化（PSO）算法和网格搜索法优化SVM的惩罚参数和核函数参数,即先利用PSO算法对参数进行大范围的快速定位,得到初步最优解,再以该解为初始位置重新构建参数搜索区间,设置小步长的网格搜索法对参数进行精细搜寻,得到最优参数,并将该最优参数代入SVM模型进行训练,得到改进SVM模型;最后根据改进的SVM模型对微震数据进行分类识别,定义微震波第1个采样点对应的时刻为初至波到时。采用某矿井下微震监测数据进行实验,结果表明：该方法对微震初至波到时的拾取准确率达96.5%,平均拾取误差为3.8 ms,在低信噪比情况下仍可对微震初至波到时进行准确拾取,拾取精度高于自动拾取方法中常用的长短时窗能量比（STA/LTA）法。     

一种基于遗传算法与蚁群算法混合算法的无线传感器网络定位算法

无线传感器网络技术应用广泛,而大多数应用依赖于节点定位,本文提出了一种基于遗传算法与蚁群算法混合算法的节点定位算法,遗传算法采用实数编码,利用线性交叉和非均匀变异算子进行搜索,在遗传算法搜索结果的基础上,利用改进的蚁群算法进行进一步搜索,蚁群算法采用MMAS算法,根据遗传算法搜索结果产生初始吸引强度分布,之后应用精英策略比较混合算法产生的新个体与父代种群,保留较优个体为新一代种群。仿真结果表明,混合算法的定位精度优于dv-hop,遗传算法等传统定位算法,算法收敛性也优于遗传算法和蚁群算法,该混合算法汲取了两种算法的优点,时间效率高,定位精度高,收敛速度快,是一种优秀的无线传感器网络定位算法。     

基于头脑风暴优化算法的多机器人气味源定位

针对现有室内湍流环境下多机器人气味源搜索算法存在历史浓度信息利用率不高、缺少调节全局与局部搜索的机制等问题,提出头脑风暴优化（BSO）算法与逆风搜索结合的多机器人协同搜索算法。首先,将机器人已搜索位置初始化为个体,以机器人位置为中心聚类,有效利用了历史信息的指引作用;然后,将逆风搜索作为个体变异操作,动态调节选中一个类中个体或两个类中个体融合生成新个体的数量,有效调节了全局和局部搜索方式;最后,根据浓度和持久性两个指标对气味源进行确认。在有障碍和无障碍两个环境中将所提算法与三种群体智能多机器人气味源定位算法进行定位对比仿真实验,实验结果表明,所提算法的平均搜索时间减少33%以上,且定位准确率达到100%。该算法能够有效调节机器人全局和局部搜索关系,快速准确定位气味源。     

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     

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.     

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。