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.     

Preparation and properties of nano-sized SnO2 powder

1　INTRODUCTIONSnO2isoneofthemainmaterialsusedingassensor.Becauseofthehumidityandgassensingfunction,itattractsmoreandmoreattentions.Butthepresentproblemishowtoimprovethestabilityandsensibilityofgassensor.Researchershavetakenmanymeasurestoresolvethisproble…     

具有细小组织的高强度和高延性钢管的开发

介绍了日本川崎制铁公司技术研究所开发出的电焊钢管采用热张力减径工艺的特性 ,及这种钢管的高强度、高延性等基本特性。用这种钢管制造的汽车零部件 ,经弯曲、冲击和疲劳特性等实验 ,证明具有良好的机械加工性能 ,是制造汽车用零部件的优良材料。     

Reliability and scale effect in toughness of concrete structures

In the present work, the distribution of the random toughness characteristics (i.e. critical energy release rate, G_1c) has been evaluated on the basis of experimental observations. Fracture test results from three groups of geometrically similar concrete specimens of size (width×total depth×thickness), 420×420×50–1680×1680×200 mm³, made with different maximum aggregate size of 9.5, 19, 38, and 76 mm were analyzed using a recently proposed distribution of extremes. In applications of probability, it is important to use an appropriate distribution type and adequate techniques for estimating the parameters of distribution. In this study, a new type distribution of minima is employed for probability computations. It was noticed that the entropy of distribution increases with the crack length, i.e. the uncertainty of toughness, G_1c, value increases with crack length. A non-linear reduction of the maximum allowable splitting force with the defect size, a, was noticed. For large specimens, the maximum allowable splitting load is more sensitive to the required reliability level than that for small specimens. Reliability increases with aggregate size when all other conditions were constant.     

ARAM·ARIES SPM-Lite便携式遥测地震数据采集系统简介

ARAM·ARIES SPM-Lite便携式遥测地震数据采集系统是加拿大GEO-X公司在2002年下半年推出的全新小型便携式地震数据采集系统。该仪器运用了当今最先进的计算机制造技术、网络化技术和微电子技术,除继承了ARAM-ARIES地震数据采集系统所有功能和技术外,它还简化了硬件结构,使体积更小,重量更轻,功能性更强。更加适应地矿、煤田、丛林和山区进行地震勘探。     

浅议铵梯炸药质量检验中的三个问题

文章探讨了GB 12437-2000标准规定的产品检验项目中,中包浸水试验的科学性问题和对批产品进行抽样时的样本代表性问题以及使用多段爆速仪测试爆速时应注意的样本量问题.     

纳米颗粒的测量与表征

介绍了用于纳米颗粒测量的电镜观察法、X射线衍射线宽法、激光粒度分析法、比表面积法、颗粒沉降法、扫描探针显微术以及小角X射线散射等,并对其测量原理、测量过程、适用范围及测量方法的优缺点进行了讨论。