A hybrid Particle Chemical Reaction Optimization for biological image matching based on lateral inhibition

In this paper, a hybrid Particle Chemical Reaction Optimization (PCRO) algorithm and lateral inhibition is proposed to solve the image matching problem. Lateral inhibition has the ability to enhance the characters of image, which can help to improve the accuracy of image matching. In order to overcome the shortcomings of basic Chemical Reaction Optimization (CRO) algorithm, we improve CRO by proposing PCRO which inspired from the thought of Particle Swarm Optimization (PSO). Comparative experimental results in image matching show that our proposed hybrid method performs much better than other bio-inspired algorithms.     

Initial guess by improved population-based intelligent algorithms for large inter-frame deformation measurement using digital image correlation

Digital image correlation (DIC) has received a widespread research and application in experimental mechanics. In DIC, the performance of subpixel registration algorithm (e.g., Newton-Raphson method, quasi-Newton method) relies heavily on the initial guess of deformation. In the case of small inter-frame deformation, the initial guess could be found by simple search scheme, the coarse-fine search for instance. While for large inter-frame deformation, it is difficult for simple search scheme to robustly estimate displacement parameters and deformation parameters simultaneously with low computational cost. In this paper, we proposed three improving strategies, i.e. Q-stage evolutionary strategy (T), parameter control strategy (C) and space expanding strategy (E), and then combined them into three population-based intelligent algorithms (PIAs), i.e. genetic algorithm (GA), differential evolution (DE) and particle swarm optimization (PSO), and finally derived eighteen different algorithms to calculate the initial guess for qN. The eighteen algorithms were compared in three sets of experiments including large rigid body translation, finite uniaxial strain and large rigid body rotation, and the results showed the effectiveness of proposed improving strategies. Among all compared algorithms, DE-TCE is the best which is robust, convenient and efficient for large inter-frame deformation measurement.     

基于智能算法的CR39径迹刻蚀过程模拟

CR39可以用于激光等离子物理实验中的离子探测,并给出离子数目、种类和能量信息。通过采用唯象模型,利用离子在CR39中径迹形成的阻止本领动力学方程以及粒子群智能算法对径迹形成的过程进行了数值化模拟,研究了CR39中离子径迹在刻蚀过程中的演化过程,获得了入射离子能量和径迹直径、深度的对应关系,并且发现当离子射程与刻蚀深度相等时,径迹深度最大,给出了利用总刻蚀时间计算最大径迹深度对应的临界能量的公式。     

糖厂澄清工段生产指标建模及操作参数优化

针对亚法糖厂澄清工段清汁色值和清汁残硫量难以在线测量的问题,提出了一种基于人工蜂群优化的在线极限学习机软测量方法。先用核主元分析法确定影响清汁质量的关键参数,建立基于在线极限学习机的软测量模型。同时利用人工蜂群算法对在线极限学习机的隐层参数进行寻优,优化所建模型。最后,使用带约束的粒子群对软测量模型进行优化求解,得到典型工况下的最优操作设定值,为后续工况操作提供参考依据。仿真结果表明,基于人工蜂群优化的在线极限学习机模型能够准确地预测清汁色值和残硫量,同时基于此模型优化的操作参数设定值能够达到期望的指标。     

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针对强磁场实验装置(SHMFF)的链式高压有源电力滤波方案规划,基于有源滤波系统的非线性特性, 采用分数阶值。PI 控制器替代普通PI 控制器,在此基础上引入粒子群算法优化指令电流PI 控制器参数,并通过 实验对比分析了人工整定的PI 控制器与PSO 整定的PI 控制器的运行效果。经样机实验表明,采用的PSO 算法 整定的电流内环控制器是正确的,且具有一定的参考价值。     

Online Tracking of Maneuvering Target Trajectory Based on Chaotic Time Series Prediction

Online prediction of maneuvering target trajectory is one of the most popular research directions at present. Specifically, the primary factors balancing, between prediction accuracy and response time, will give the research substance. This paper presents an online trajectory prediction algorithm based on small sample chaotic time series (OTP-SSCT). First, we optimize in terms of data breadth. The dynamic split window is built according to the motion characteristics of the maneuvering target, thus realizing trajectory segmentation and constructing a small sample chaotic time series prediction set. Second, since fully considering the motion patterns of maneuvering targets, we introduce the spatiotemporal features into the particle swarm optimization (PSO) model identification algorithm, which improves the identification sensitivity of key trajectory data points. Furthermore, we propose a feedback optimization strategy of residual compensation to correct the trajectory prediction values to improve the prediction accuracy. For the initial value sensitivity problem of the PSO model identification algorithm, we propose a new initial population strategy, which improves the effectiveness of initial parameters on model identification. Through simulation experiment analysis, it is verified that the proposed OTP-SSCT algorithm achieves better prediction accuracy and faster response time.     

B离子掺杂TiO2催化剂(TiO2－xBx)光催化活性的研究

采用溶胶-凝胶法制备出纳米TiO₂和TiO_2－xB_x催化剂. 光催化实验证明, TiO_2－xB_x催化剂的紫外、可见光催化活性均高于TiO₂. XRD, XPS和Raman结果表明, B离子是以取代式掺杂占据了TiO₂的O^2－的晶格位置. UV-Vis和PL谱的结果表明, B离子的2p轨道与O的2p轨道形成混合价带, 产生可见光响应, B离子的掺入有效地阻止了光生载流子的复合, 促进了其分离, 是TiO_2－xB_x催化剂紫外、可见光催化活性提高的主要原因.     

Co—Mo／MgO—Al2O3水煤气耐硫变换催化剂失活的研究

利用Ｘ－射线衍射，扫描电镜，拉曼光谱，等离子发射光谱和比表面测定等方法研究了不同状态下失活及新鲜催化剂的结构，杂种类及含量。结果表明，超温使催化剂晶化明显，制备方法对催化剂结构有直接影响，再生使其强度降低，条形催化剂比较容易粉化，无机杂质是次要的失活原因。     

Liquid membranes for gas/vapor separations

A review on developments of liquid membranes (LMs) in the field of gas and vapor separation of the last 16 years is presented. Liquid membrane configurations employing supports, i.e. immobilized, supported and contained liquid membranes are focussed and detailed information on the respective materials, i.e. supports (supplier, type, thickness, pore width, porosity, tortuosity), liquids and carriers, are presented together with their specific separation tasks. Performance of different LMs in terms of permeability and selectivity as well as stability (duration of testing, applied differential pressures) are compared and discussed. Finally, different preparation methods of LMs are illustrated.     

基于时间的随机需求二级分销网络物流系统集成优化研究

分销网络设计包括设施选址、库存控制、运输等方面的设计与优化,但以往只是从战略层、战术层、运作层来分别进行各自的研究。实际上,这三个层次的决策要素之间存在着复杂的互动关系,并存在着广泛的效益悖反关系,这些在变化的环境下显得尤为突出。本文充分考虑时间因素的重要性,从物流系统的集成优化高度出发,研究建立需求随机的多分销中心多顾客的设施选址———运输路线安排———库存控制问题(ILRIP)的模型,对此设计了一个两层粒子群优化(PSO)算法,并给出了计算实例。研究结果有助于供应链分销网络的集成优化,缩短商品流转周期,提高顾客服务水平,提升竞争力。