改进的粒子群算法

针对基本粒子群算法容易陷入局部最优点,进化后期速度慢等缺点,设计了一种新的粒子群算法,将基本粒子群算法粒子行为基于个体极值点转化为个体自身极值与其他某一个个体极值的加权平均值,而全局极值点转化为群体中优秀个体极值的加权平均值。数值仿真实验表明,新算法比PSO具有更好的收敛性,能更快地找到问题的最优解。     

话题发现与追踪技术研究

话题发现与追踪以新闻流为处理对象,采用基于事件的信息组织方式进行研究,一直是自然语言处理领域里的热点。该研究借鉴大量相关研究尤其是信息检索中的经典模型和方法,取得了很大成功。首先介绍了话题发现与追踪的主要研究内容、评价方法以及发展历史;然后对其多个研究内容提出一个统一研究框架,并对该框架中的关键技术进行了详细分析;最后指出该领域中的关键问题及难点,并对未来研究做出展望。     

Cryo-EM image alignment based on nonuniform fast Fourier transform

In single particle analysis, two-dimensional (2-D) alignment is a fundamental step intended to put into register various particle projections of biological macromolecules collected at the electron microscope. The efficiency and quality of three-dimensional (3-D) structure reconstruction largely depends on the computational speed and alignment accuracy of this crucial step. In order to improve the performance of alignment, we introduce a new method that takes advantage of the highly accurate interpolation scheme based on the gridding method, a version of the nonuniform fast Fourier transform, and utilizes a multi-dimensional optimization algorithm for the refinement of the orientation parameters. Using simulated data, we demonstrate that by using less than half of the sample points and taking twice the runtime, our new 2-D alignment method achieves dramatically better alignment accuracy than that based on quadratic interpolation. We also apply our method to image to volume registration, the key step in the single particle EM structure refinement protocol. We find that in this case the accuracy of the method not only surpasses the accuracy of the commonly used real-space implementation, but results are achieved in much shorter time, making gridding-based alignment a perfect candidate for efficient structure determination in single particle analysis.     

考虑电-氢-热多能互补的微网多目标优化配置研究

氢储能具有储能容量大、储存时间长、清洁无污染、实现多种能源网络互联互补和协同优化等诸多优点,有望成为推动分布式能源发展和提升终端能源利用效率的重要支撑技术。为了提高独立型微网供电可靠性及可再生能源利用率,本文建立了考虑电-氢-热多能互补的独立微网多目标优化配置模型,并基于模拟退火的粒子群算法对目标问题进行求解。最后,通过东北某地独立微网优化配置算例,基于MATLAB平台验证了所提多能互补配置方案较传统电储能配置方案负荷失电率降低了3.18%,可再生能源利用率提高了8.37%,所提配置方案可有效促进可再生能源消纳,保证独立微网的供电可靠性。     

Finite-time optimal tracking control for a class of nonlinear systems with prescribed performance

In this paper, a finite-time optimal tracking control scheme based on integral reinforcement learning is developed for partially unknown nonlinear systems. In order to realize the prescribed performance, the original system is transformed into an equivalent unconstrained system so as to a composite system is constructed. Subsequently, a modified nonlinear quadratic performance function containing the auxiliary tracking error is designed. Furthermore, the technique of experience replay is used to update the critic neural network, which eliminates the persistent of excitation condition in traditional optimal methods. By combining the prescribed performance control with the finite-time optimization control technique, the tracking error is driven to a desired performance in finite time. Consequently, it has been shown that all signals in the partially unknown nonlinear system are semiglobally practical finite-time stable by stability analysis. Finally, the provided comparative simulation results verify the effectiveness of the developed control scheme.     

Reconstructing design parameters of a rectangular resonator via peak signal-to-noise ratio and global optimization algorithms

This article proposes an approach for reconstructing physical parameters of a sample in a rectangular resonator during microwave radiation, knowing a priori, its electric field distribution. The inverse problem was solved using two global optimization algorithms and the peak signal-to-noise ratio (PSNR) criterion. First, the Self-regulated Fretwidth Harmony Search algorithm (SFHS) identified suitable resonant frequencies for a given configuration. Next, the unified Particle Swarm Optimization (UPSO) optimized said configuration. Together, they became a maximization strategy of the PSNR through a dual optimization process. Results showed the ability of the approach for estimating the height of each sample block and the resonating frequency of the cavity. This process takes longer to finish as a higher PSNR is demanded (mainly due to the aforementioned dual optimization). Even so, it allows for more similar electric field distributions between both, the direct and inverse problems.     

Erosion coupled dynamic mesh analysis for location of maximum erosion in 90-degree bends for gas-solid flows

The progressive change in the surface geometry of the component due to erosive wear affects the correct estimation of erosive wear performance and service life of the components handling particulate flows. The current study focuses on determining the change in the location of higher erosion on the bend surface during the pneumatic conveying of solids with continuous geometric modification due to erosive wear. Computational fluid dynamics (CFD) based erosion-coupled dynamic mesh methodology is adopted to simulate the time-dependent surface modification of the 90° bend geometry due to erosive wear. Available experimental data are used to validate the numerical results. Further, the erosion distribution and the location of the maximum erosion for different flow velocities, particle sizes, and bend radius ratios with the increase in solid throughput are investigated. It has been found that the modification in the bend geometry due to erosion influences the location of the maximum erosion. The increase in thickness loss due to erosion increases the variation in the location of the maximum erosion. Furthermore, an equation for predicting the location of maximum erosion of bend geometry is obtained based on the bend radius ratio and the thickness loss.     

在线修正的人脸姿态跟踪算法及交互应用

针对人脸在跟踪过程中可能存在大幅度的倾斜、旋转、遮挡以及肤色干扰等问题,提出一种基于在线修正的人脸跟踪算法.该算法当人脸检测失效时,人脸跟踪模块将用于提取目标参数;而在人脸跟踪过程中,为减小由连续跟踪造成的累积误差,利用人脸实时检测机制新检测到的人脸目标参数来修正跟踪模块的参数,包括跟踪窗口的位置和尺度,从而利用了人脸检测和人脸跟踪各自的优点.通过实验,其结果表明,该算法能够精确地跟踪复杂姿态下的人脸目标,并且能够解决肤色干扰和遮挡的问题,具有很好的适应性和鲁棒性.另外,将在线修正的跟踪方法应用于娱乐游戏控制,为人机交互提供了新的方式.     

Discrete particle swarm optimization based on estimation of distribution for terminal assignment problems

Terminal assignment problem (TEAP) is to determine minimum cost links to form a network by connecting a given set of terminals to a given collection of concentrators. This paper presents a novel discrete particle swarm optimization (PSO) based on estimation of distribution (EDA), named DPSO-EDA, for TEAP. EDAs sample new solutions from a probability model which characterizes the distribution of promising solutions in the search space at each generation. The DPSO-EDA incorporates the global statistical information collected from personal best solutions of all particles into the PSO, and therefore each particle has comprehensive learning and search ability. In the DPSO-EDA, a modified constraint handling method based on Hopfield neural network (HNN) is also introduced to fit nicely into the framework of the PSO and thus utilize the merit of the PSO. The DPSO-EDA adopts the asynchronous updating scheme. Further, the DPSO-EDA is applied to a problem directly related to TEAP, the task assignment problem (TAAP), in order to show that the DPSO-EDA can be generalized to other related combinatorial optimization problems. Simulation results on several problem instances show that the DPSO-EDA is better than previous methods.     

Checking determinism of XML Schema content models in optimal time

We consider the determinism checking of XML Schema content models, as required by the W3C Recommendation. We argue that currently applied solutions have flaws and make processors vulnerable to exponential resource needs by pathological schemas, and we help to eliminate this potential vulnerability of XML Schema based systems. XML Schema content models are essentially regular expressions extended with numeric occurrence indicators. A previously published polynomial-time solution to check the determinism of such expressions is improved to run in linear time, and the improved algorithm is implemented and evaluated experimentally. When compared to the corresponding method of a popular production-quality XML Schema processor, the new implementation runs orders of magnitude faster. Enhancing the solution to take further extensions of XML Schema into account without compromising its linear scalability is also discussed.