Self-adjusting the intensity of assortative mating in genetic algorithms

Mate selection plays a crucial role in both natural and artificial systems. While traditional Evolutionary Algorithms (EA) usually engage in random mating strategies, that is, mating chance is independent of genotypic or phenotypic distance between individuals, in natural systems non-random mating is common, which means that somehow this mechanism has been favored during the evolutionary process. In non-random mating, the individuals mate according to their parenthood or likeness. Previous studies indicate that negative assortative mating (AM)—also known as dissortative mating—, which is a specific type of non-random mating, may improve EAs performance by maintaining the genetic diversity of the population at a higher level during the search process. In this paper we present the Variable Dissortative Mating Genetic Algorithm (VDMGA). The algorithm holds a mechanism that varies the GA’s mating restrictions during the run by means of simple rule based on the number of chromosomes created in each generation and indirectly influenced by the genetic diversity of the population. We compare VDMGA not only with traditional Genetic Algorithms (GA) but also with two preceding non-random mating EAs: the CHC algorithm and the negative Assortative Mating Genetic Algorithm (nAMGA). We intend to study the effects of the different methods in the performance of GAs and verify the reliability of the proposed algorithm when facing an heterogeneous set of landscapes. In addition, we include the positive Assortative Mating Genetic Algorithm (pAMGA) in the experiments in order test both negative and positive AM mechanisms, and try to understand if and when negative AM (or DM) speeds up the search process or enables the GAs to escape local optima traps. For these purposes, an extensive set of optimization test problems was chosen to cover a variety of search landscapes with different characteristics. Our results confirm that negative AM is effective in leading EAs out of local optima traps, and show that the proposed VDMGA is at least as efficient as nAMGA when applied to the range of our problems, being more efficient in very hard functions were traditional GAs usually fail to escape local optima. Also, scalability tests have been made that show VDMGA ability to decrease optimal population size, thus reducing the amount of evaluations needed to attain global optima. We like to stress that only two parameters need to be hand-tuned in VDMGA, thus reducing the tuning effort present in traditional GAs and nAMGA.     

关于沥青针入度指数

介绍了沥青针入度指数(PI)的由来和计算、使用意义、局限性和分析。     

CDMA发射分集系统的多用户检测常模算法分析

空时分集技术的最大优点在于在不增加带宽的情况下可以提高系统的可靠性,是目前移动通信的研究热点.常模算法是一种性能优良的码分多址(CDMA)盲多用户检测技术,能确保判决信号与实际传送信号之间的差错较小,误码率性能良好.文中提出将标准线性受限常模算法(LCCMA)与空时分组码(STBC)相结合,设计出一种收敛快、能够改善系统性能的基于2-空时分组码的多用户接收机.     

基于随机相位误差Tikhonov分布的MC-DS-CDMA系统性能分析

本文针对工作于慢变频率选择性Rayleigh衰落信道中的部分相干的MC-DS-CDMA系统，基于随机相位误差的Tikhonov密度分布提出了误码率上边界的一种分析方法。仿真结果表明，随着环路信噪比的增加，相位误差损耗所产生的系统误码率性能损失变得越来越小，当环路信噪比高于系统信噪比(Eb/N0)20dB时，系统误码率性能损失小于0．2dB。在MC-DS-CDMA系统中，由于能用频率分集取代路径分集，因而接收机结构更易实现。     

漏斗贮料压力计算公式

本文从平衡条件和常系数假定出发，建立贮料压力微分方程，导出了正倒锥漏斗、倒锥漏斗贮料压力计算公式。文中说明，圆柱仓筒贮料压力微分方程为上述方程的特殊情形。本文成果可供筒仓工程设计使用，还可供确定斗口给料机贮料荷载参考。     

Inference and retrieval of facial images

Attempts have been made to extend SQL to work with multimedia databases. We are reserved on the representation ability of extended SQL to cope with the richness in content of multimedia data. In this paper we present an example of a multimedia database system, Computer Aided Facial Image Inference and Retrieval system (CAFIIR). The system stores and manages facial images and criminal records, providing necessary functions for crime identification. We would like to demonstrate some core techniques for multimedia database with CAFIIR system. Firstly, CAFIIR is a integrated system. Besides database management, there are image analysis, image composition, image aging, and report generation subsystems, providing means for problem solving. Secondly, the richness of multimedia data urges feature-based database for their management. CAFIIR is feature-based. A indexing mechanism,iconic index, has been proposed for indexing facial images using hierarchical self-organization neural network. The indexing method operates on complex feature measures and provides means for visual navigation. Thirdly, special retrieval methods for facial images have been developed, including visual browsing, similarity retrieval, free text retrieval and fuzzy retrieval.     

强度调制／直接检测（IM／DD）光纤通信系统色散限制的研究

通过引入归一化脉宽Ｐ和相对脉冲展宽因子ｑ，提出了一个适用于ＩＭ／ＤＤ系统中各种眼图恶化量ｘ和归一化脉宽Ｐ的色散限制改进公式。通过与其它理论的比较、计算机仿真和对实验数据的分析，验证了该公式的正确性，并给出了其它结果的限制条件。研究表明：当眼图恶化量ｘ为１ｄＢ左右时，对２．５Ｇｂ／；外调制信号（α＝０）而言，非色散位移光纤ＩＭ／ＤＤ系统的色散因子γ约等于０．７９，所对应的系统再生中继距离约为９００余公里。     

A bidding decision index for construction contractors

Results from applying the model on a sample of contractors, the majority of whom were international and operating in Egypt, reinforces the credibility of the developed methodology, claim the authors.