A modified particle swarm optimization with multiple subpopulations for multimodal function optimization problems

In this paper, a modified particle swarm optimization (PSO) algorithm is developed for solving multimodal function optimization problems. The difference between the proposed method and the general PSO is to split up the original single population into several subpopulations according to the order of particles. The best particle within each subpopulation is recorded and then applied into the velocity updating formula to replace the original global best particle in the whole population. To update all particles in each subpopulation, the modified velocity formula is utilized. Based on the idea of multiple subpopulations, for the multimodal function optimization the several optima including the global and local solutions may probably be found by these best particles separately. To show the efficiency of the proposed method, two kinds of function optimizations are provided, including a single modal function optimization and a complex multimodal function optimization. Simulation results will demonstrate the convergence behavior of particles by the number of iterations, and the global and local system solutions are solved by these best particles of subpopulations.     

Multiobjective PSO based adaption of neural network topology for pixel classification in satellite imagery

The proposed work involves the multiobjective PSO based adaption of optimal neural network topology for the classification of multispectral satellite images. It is per pixel supervised classification using spectral bands (original feature space). This paper also presents a thorough experimental analysis to investigate the behavior of neural network classifier for given problem. Based on 1050 number of experiments, we conclude that following two critical issues needs to be addressed: (1) selection of most discriminative spectral bands and (2) determination of optimal number of nodes in hidden layer. We propose new methodology based on multiobjective particle swarm optimization (MOPSO) technique to determine discriminative spectral bands and the number of hidden layer node simultaneously. The accuracy with neural network structure thus obtained is compared with that of traditional classifiers like MLC and Euclidean classifier. The performance of proposed classifier is evaluated quantitatively using Xie-Beni and β indexes. The result shows the superiority of the proposed method to the conventional one.     

Cost-minimization analysis of a working vacation queue with N-policy and server breakdowns

This paper investigates the N-policy M/M/1 queueing system with working vacation and server breakdowns. As soon as the system becomes empty, the server begins a working vacation. The server works at a lower service rate rather than completely stopping service during a vacation period. The server may break down with different breakdown rates during the idle, working vacation, and normal busy periods. It is assumed that service times, vacation times, and repair times are all exponentially distributed. We analyze this queueing model as a quasi-birth–death process. Furthermore, the equilibrium condition of the system is derived for the steady state. Using the matrix-geometric method, we find the matrix-form expressions for the stationary probability distribution of the number of customers in the system and system performance measures. The expected cost function per unit time is constructed to determine the optimal values of the system decision variables, including the threshold N and mean service rates. We employ the particle swarm optimization algorithm to solve the optimization problem. Finally, numerical results are provided, and an application example is given to demonstrate the applicability of the queueing model.     

嵌人式与独立存储器设计上的差异分析和研究

进入21世纪,随着集成电路的发展,SoC(System on Chip)片上系统应运而生。而作为SoC重要组成部分的嵌入式存储器,在SoC中所占的比重正逐步增加,并起着越来越重要的作用,那么嵌入式存储器与独立的存储器芯片在设计上存在着哪些差异?对此本文将以NOR型闪存为例在制造工艺的选取、衍生产品的设计、功耗与噪声、后端功能仿真、测试与修复等方面进行分析和研究。     

构建媒体网络信息安全体系

通过对广州市电视台综合信息平台网络系统的应用现状及安全风险进行分析,提出基于网络层、系统层、用户层和安全策略管理全方位的网络信息安全体系.     

提高托盘利用效率的重要手段——电子信息化管理

托盘能否有效运用对物流的畅通与否关系重大,这已经引起了国内外专家和学者们的重视,并就此制定了托盘电子信息化管理系统,旨在更合理地使用托盘,推进托盘一体化和共用系统的建立。而RFID技术在托盘的电子信息化管理的应用更将大大提高物流的效率与准确性,托盘电子信息化管理将成为今后托盘管理的趋势。     

数字电视用户管理系统

课题实现了数字电视用户管理系统的设计与开发,以Oracle数据库作为后台数据库,以C Builder 6作为前台开发工具,包括表的设计与界面的设计.实现了数字电视用户管理系统基本功能,基本上满足了实际商业运营的需要.     

阴,阳离子聚合物地层内凝胶化改善水驱效果的研究

研究了一杆阴离子聚合物（Ａｃ５３０）和一种阳离子聚合物（Ｍｂ５８１）在水溶液中形成凝胶的条件和过程、凝胶化学结构、形态、稳定性和力学性能。在模拟地层的二维微观模型内观测了两种聚合物驱替渗流、相逼、形成凝胶、凝胶封堵大孔道的机理。在亲水填砂模型内测定了阴、阳离子聚合物凝胶体系降低渗透率的能力。     

Test Case Generation as an AI Planning Problem

While Artificial Intelligence techniques have been applied to a variety of software engineering applications, the area of automated software testing remains largely unexplored. Yet, test cases for certain types of systems (e.g., those with command language interfaces and transaction based systems) are similar to plans. We have exploited this similarity by constructing an automated test case generator with an AI planning system at its core. We compared the functionality and output of two systems, one based on Software Engineering techniques and the other on planning, for a real application: the StorageTek robot tape library command language. From this, we showed that AI planning is a viable technique for test case generation and that the two approaches are complementary in their capabilities.