An Enhanced Particle Swarm Optimization Algorithm

Particle Swarm Optimization (PSO) algorithm is often used for finding optimal solution, but it easily entraps into the local extremum in later evolution period. Based on improved chaos searching strategy, an enhanced particle swarm optimization algorithm is proposed in this study. When particles get into the local extremum, they are activated by chaos search strategy, where the chaos search area is controlled in the neighborhood of current optimal solution by reducing search area of variables. The new algorithm not only gets rid of the local extremum effectively but also enhances the precision of convergence significantly. Experiment results show that the proposed algorithm is better than standard PSO algorithm in both precision and stability.

一种改进的自适应逃逸微粒群算法及实验分析

分析了变异操作对微粒群算法（panicle swarm optimization，简称PSO）的影响，针对收敛速度慢、容易陷入局部极小等缺点，结合生物界中物种发现生存密度过大时会自动分家迁移的习性，给出了一种自适应逃逸微粒群算法，并证明了它依概率收敛到全局最优解．算法中的逃逸行为是一种简化的确定变异操作．当微粒飞行速度过小时，通过逃逸运动使微粒能够有效地进行全局和局部搜索，减弱了随机变异操作带来的不稳定性、典型复杂函数优化的仿真结果表明，该算法不仅具有更快的收敛速度，而且能更有效地进行全局搜索．

基于PSO的球磨机粉磨系统自适应模糊控制

提出了一种基于粒子群算法优化(PSO)的模糊控制器,对模糊控制器参数进行全局优化,以弥补模糊控制器参数在线调节方面的不足,并应用于球磨机粉磨系统的控制中。控制系统采用粒子群优化模糊控制器作为双闭环控制中的成品流量控制器,并在Matlab/Simulink进行的仿真分析中实现模糊控制器参数的在线调节。仿真结果表明,系统较好地实现了给定参考轨迹自适应跟踪,具有鲁棒性强、控制精度高等优点。

RFID系统优化模型与智能算法研究

射频识别技术（Radio Frequency Identification, RFID）作为采集与处理信息的高新技术和信息化标准的基础，被列为本世纪十大重要技术之一。但是，RFID技术的大规模实际应用仍处于探索阶段，RFID系统的应用基础技术还存在着大量尚未解决的关键问题，其中RFID系统优化是RFID技术研究和应用的重要课题。由于RFID系统本身的动态性和不确定性， RFID系统优化面对的一般是非线性、多目标、大规模的复杂优化问题，传统的数学优化算法在处理这些问题时，存在困难。为此，研究新的优化算法成为RFID技术实际应用和理论研究中必须解决的课题。 智能计算方法是求解复杂RFID系统优化问题的一种可供选择的算法。智能计算作为一个新兴领域，其发展已引起了多个学科领域研究人员的关注，目前已经成为人工智能、经济、社会、生物等交叉学科的研究热点和前沿领域。智能计算的各类算法已在传统NP问题求解及诸多实际应用领域中展现出其优异的性能和巨大的发展潜力。 本文旨在对RFID系统的各种优化问题进行深入研究和探讨，面向RFID技术的实际应用需求构建其优化模型，并基于智能计算思想设计能够有效求解这些复杂模型的新型智能优化算法。具体研究内容包括： 首先，进行了RFID读写器网络的调度问题研究。在深入分析RFID网络中读写器冲突类型和成因的基础上，考虑RFID网络中的读写器冲突约束，以最小化系统中的频道数量、时隙分配以及总处理时间建立了RFID读写器网络调度的数学优化模型。从生物学的角度出发提出基于生态捕食模型的改进PSO算法（Particle Swarm Optimizer based on Predator-prey Coevolution, PSOPC），在一定程度上解决了PSO算法在迭代后期随着多样性丧失而陷入局部最优的缺点。应用PSOPC设计了求解RFID读写器网络调度模型的智能求解算法，分别给出算法的求解框架、关键步骤的实现机制。通过在不同规模的RFID读写器网络上进行实例仿真，验证了算法的有效性和模型的正确性。 其次，进行了基于菌群自适应觅食算法RFID网络规划问题的研究。考虑RFID系统在不同应用环境下的系统需求，建立了RFID网络规化的数学模型，其目标函数分别为：RFID网络标签覆盖率的最大化目标函数、RFID读写器冲突的最小化目标函数、RFID网络运行的经济效益最大化目标函数、RFID网络运行的负载平衡目标函数以及同时考虑全局目标的混合目标函数。将自然界生物觅食所采用的自适应搜索策略与细菌的趋化行为和群体感应机制相集成，提出了适合求解复杂RFID网络规划问题的菌群自适应觅食算法（Adaptive Bacterial Foraging Optimization, ABFO）。通过仿真实验基于ABFO算法分别对RFID网络规划模型中的五个目标函数进行了实例求解和分析，测试结果与标准PSO算法和遗传算法进行了比较分析。 再次，进行了基于系统智能方法的RFID网络规划分布式决策模型研究。采用分布式决策的思想建立了RFID网络规划的层次模型，在一定程度上缓解、分散了RFID网络规划问题的复杂性，以解决具有混合变量（包括离散变量和连续变量）的多目标RFID网络规划问题。针对层次模型求解的复杂性，以复杂适应系统理论为指导思想设计了一种新型系统智能优化算法对RFID网络规划的层次模型进行求解。系统智能算法将群体智能中的单层群体系统概念扩展为多层涌现系统，仿真实验表明新提出的算法显著提高了智能计算方法的寻优能力，以及算法的适应性、鲁棒性和平衡性等性能。 最后，进行了RFID网络目标跟踪系统中的数据融合研究。以基于RFID技术的目标定位与跟踪系统为应用背景，提出了基于模糊聚类方法的多RFID读写器数据融合模型框架。通过深入分析蜜蜂采蜜的基本生物学规律，对蜜蜂的个体行为及群体行为进行模拟，提出了一类新型群体智能优化算法-蜂群优化算法（Bee Swarm Optimization, BSO），并将BSO算法嵌入RFID目标定位跟踪系统，作为其模糊聚类的基本算法。仿真研究表明，提出的融合模型能够有效的过滤读写器对跟踪目标的错误监测数据，显著提高目标定位与跟踪的精度。

基于粗糙集和多Agent系统的知识挖掘

通过优化知识表达系统中条件属性对决策属性的依赖度,深入研究了粗糙集并与多Agent系统相结合。利用离散粒子群算法,提出一种基于粒子群优化的粗糙集知识约简算法,该算法解决了启发式算法无法全局搜索进行约简的问题。最后通过在矿井中调度信息的应用验证了有效性。

混沌粒子群混合算法对微型永磁电机的优化设计

在电机的设计中,常常需要通过优化设计得到合理的电机结构尺寸和参数.电机的设计问题实质上是一种带约束的复杂的非线性连续函数优化问题.要得到一个满意的优化结果不仅要求算法具有较高的精度,而且要有快的收敛速度.提出一种新的混合算法对永磁电机的尺寸和整体结构进行优化设计.将混沌算法和粒子群算法相结合,以微型永磁电机为例,对槽形等多个变量进行优化,结果证明了算法的有效性和快速性,适合于同类问题求解.

Improved Procedure on the Microscopic Approach to Determine Colloidal Stability

We present an improved procedure on the approach to determine the stability of polystyrene spheres at microscopic particle levels by means of artificially induced particle collisions with the aid of optical tweezers [J.Chem.Phys. 119, 2399(2003)]. The basic consideration on this new development is that the major contribution to the sticking probability for a particle pair caught into the optical trap for a short period is from its single collision; therefore, if the trapping duration for the pair is taken to be short, the accumulated sticking probability will be a good approximation for the single collision. The experimental procedure associated with this approximation does not resort to exactly controlling the short trapping duration or request the trapping duration correction as previously reported and therefore it is more practical and applicable for broader range of the stability ratio. The experimental results under different electrolyte concentrations by the new procedure are consistent with those from the turbidity measurements.

An Improved Ce/Se Scheme For Multi-Material Elastic-Plastic Flows And Its Applications

In this paper, a new definition of SE and CE, which is based on the hexahedron mesh and simpler than Chang's original CE/SE method (the space-time Conservation Element and Solution Element method), is proposed and an improved CE/SE scheme is constructed. Furthermore, the improved CE/SE scheme is extended in order to solve the elastic-plastic flow problems. The hybrid particle level set method is used for tracing the interfaces of materials. Proper boundary conditions are presented in interface tracking. Two high-velocity impact problems are simulated numerically and the computational results are carefully compared with the experimental data, as well as the results from other literature and LS-DYNA software. The comparisons show that the computational scheme developed currently is clear in physical concept, easy to be implemented and high accurate and efficient for the problems considered. (C) 2008 Elsevier Ltd. All rights reserved.

Improved BCS-type pairing for the relativistic mean-field theory

A density-dependent delta interaction (DDDI) is proposed in the formalism of BCS-type pairing correlations for exotic nuclei whose Fermi surfaces are close to the threshold of the unbound state. It provides the possibility to pick up those states whose wave functions are concentrated in the nuclear region by making the pairing matrix elements state dependent. On this basis, the energy level distributions, occupations, and ground-state properties are self-consistently studied in the RMF theory with deformation. Calculations are performed for the Sr isotopic chain. A good description of the total energy per nucleon, deformations, two-neutron separation energies and isotope shift from the proton drip line to the neutron drip line is found. Especially, by comparing the single-particle structure from the DDDI pairing interaction with that from the constant pairing interaction for a very neutron-rich nucleus it is demonstrated that the DDDI pairing method improves the treatment of the pairing in the continuum.

Improved Melting Strength of Polypropylene by Reactive Compounding With Ultrafine Full-Vulcanized Polybutadiene Rubber (UFBR) Particles

Ultrafine full-vulcanized polybutadiene rubber (UFBR) in particle sizes of ca. 50-100 nm has been used for modifying mechanical and processing performances of polypropylene (PP), and PP-g-maleic anhydride (PP-MA) has been used as a compatibilizer for enhancing the interfacial adhesion between the two components. The results show that PP/UFBR possesses rheological behaviors such as highly branched PP when UFBR content in blends reaches 10 wt%, while in contrast, the much low content of UFBR combining small amount of PP-MA endows the material with rheological characteristics of high melt strength materials like highly branched PP.

Improved size control of large palladium nanoparticles by a seeding growth method

A new approach to the preparation of large palladium nanoparticles with diameters between 25 and 100 nm is presented. In this approach PdCl42- ions are reduced on the surface of performed 12-nm-diameter gold "seeds'' by the introduction of ascorbic acid. The resultant particles exhibit improved monodispersity relative to previous work. Interestingly, these nanoparticles possess Au-Pd core-shell structures. The method can be scaled up to produce 50-110 mg of large palladium nanoparticles.