遗传算法中初始种群与交叉、变异率对解的影响及其解决方案

本文的研究表明，在相同的遗传算子下，初始种群性状和数量以及交叉、变异率的确定对算法收敛速度和结果的影响不能忽略。初始种群或交叉、变异率选择不当，将增加迭代次数，甚至直接导致算法陷入局部最优解。为此，本文提出一种基于空间分割的遗传算法及初始种群产生和种群数量确定方法，并根据有关文献，提出一种自适应交叉、变异率方法。实际计算表明，该算法在很大程度上避免了算法收敛于局部最优点，取得较好的效果。     

基于遗传算法的实验室排课系统设计与实现

由于排课问题是一个NP完全优化问题,采用遗传算法来搜索近似最优解。遗传算法是一种借鉴生物界自然选择和进化论发展起来的随机搜索算法,能够非常有效地解决NP完全的组合优化问题,并且解决了遗传算法在排课过程中的冲突问题。系统采用的是B/S网络结构,实践证明,系统运行良好。     

Governing software: networks,databases and algorithmic power in the digital governance of public education

This article examines the emergence of ‘digital governance’ in public education in England. Drawing on and combining concepts from software studies, policy and political studies, it identifies some specific approaches to digital governance facilitated by network-based communications and database-driven information processing software that are being discursively promoted in education by cross-sectoral intermediary organizations. Such intermediaries, including National Endowment for Science, Technology and the Arts, Demos, the Innovation Unit, the Education Foundation and the Nominet Trust, are increasingly seeking to participate in new digitally mediated forms of educational governance. Through their promotion of network-based pedagogies and database-driven analytics software, these organizations are seeking to delegate educational decision-making to socio-algorithmic forms of power that have the capacity to predict, govern and activate learners' capacities and subjectivities.     

基于遗传算法的柔性作业车间等量分批调度问题研究

针对柔性作业车间等量分批调度问题的复杂性,文中采用遗传算法进行求解.引入等量分批的策略,并提出了染色体的两级编码方法,设计了两种交叉和变异操作方法,以防止操作中非法解的产生,提高求解效率.对比整批调度和等量分批调度的生产周期,仿真结果表明,等量分批调度可缩短生产周期,验证了本文采用算法的可行性和有效性.     

Multi-layer self-organizing polynomial neural networks and their development with the use of genetic algorithms

In this paper, we introduce a new architecture of genetic algorithms (GA)-based self-organizing polynomial neural networks (SOPNN) and discuss a comprehensive design methodology. Let us recall that the design of the “conventional” PNNs uses an extended group method of data handling (GMDH) and exploits polynomials (such as linear, quadratic, and modified quadratic functions) as well as considers a fixed number of input nodes (as being selected in advance by a network designer) at polynomial neurons (or nodes) located in each layer. The proposed GA-based SOPNN gives rise to a structurally optimized structure and comes with a substantial level of flexibility in comparison to the one we encounter in conventional PNNs. The design procedure applied in the construction of each layer of a PNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomial, and a collection of the specific subset of input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the network. To evaluate the performance of the GA-based SOPNN, the model is experimented with using chaotic time series data. A comparative analysis reveals that the proposed GA-based SOPNN exhibits higher accuracy and superb predictive capability in comparison to some previous models available in the literature.     

几种隐私数据挖掘算法研究进展

隐私数据挖掘是数据挖掘的一个重要研究方向,它旨在研究在数据挖掘过程中如何保护私有的和敏感的数据不被泄露。文章阐述几种常用的隐私数据挖掘算法,分析它们的技术特点,文末对几种隐私数据挖掘技术进行总结与展望。     

海量数据的MapReduce相似度检测

针对当前海量数据的相似重复问题,提出了MapReduce下通过SimHash算法检测相似文档的方法:即首先将存储在分布式文件系统的海量文档集进行分类,然后进行特征提取,由SimHash算法生成SimHash指纹和生成Sequence File;最后,计算相似度产生检测结果;通过实验测试可知,提出的检测方法和设计的相似度算法能很好适应海量数据相似检测,并能有效地提高工作效率。     

Tackling the storage problem through genetic algorithms

The capability automated warehouse in of a company to implement an an optimized way might be nowadays a crucial leverage in order to gain competitive advantage to satisfy the demand. The order picking is a warehouse function that needs to deal with the retrieval of articles from their storage locations. Merging several single customer orders into one, a picking order can increase efficiency of warehouse operations. The aim of this paper is to define throughout the use of ad-hoc genetic algorithm （GA） how better a warehouse can be set up. The paper deals with order batching, which has a major effect on efficiency of warehouse operations to avoid wastes of resources in terms of processes and to control possibility of unexpected costs in advance.     

基于信息传播算法的云存储系统架构研究

云存储是一种在线网络存储模式,可以为用户提供能直接访问的大范围资源和应用程序。虽然许多云存储提供商已经采用加密策略来保护客户的数据,但是用户还是怀疑数据的安全性和隐私性。通过信息传播算法分析,证明它能够解决云存储数据的私密性、完整性等问题,在此基础上,提出一种采用信息传播算法的云存储系统架构,实验证明,它可以提高云存储数据的安全性、完整性和可用性。     

船型论证中的随机仿真与优化

随机性是运输系统的主要特性之一。但是,过去由于随机系统的优化手段不够成熟,计算量相当大,因此,在实际优化过程中不得不作了许多简化与假设。这样对最后所得到的优化结果的准确性与可靠性会产生一定的不利影响。本文结合受随机干扰影响的船型论证工作,介绍了一种连续型随机系统优化算法——随机逼近法SAM,它比传统的建立在均值处理基础上的仿真优化算法——直接搜索法DSM,无论在运算速度还是计算准确性等方面均有显著的优越性,也比通常只能逐个分析处理备选方案而不能得出最优解的不确定性分析与风险分析方法更方便,有效和全面。