基于退火遗传算法的少数投影CT图像重建

不完全投影重建算法研究是当今图像重建算法中的一个难点问题，近年来，遗传算法在其中有一定的应用，但还存在一些问题。针对遗传算法在优化中的不足(如早熟收敛及易陷入局部最小等)，将模拟退火机制引入到遗传算子中，提出一种新的算法；并通过选择测试函数，建立将该算法应用于不完全投影图像重建的优化模型，进行计算机模拟。通过对从投影角间距为15°的12个不同投影视角方向获取的投影数据进行分析，结果表明，该算法的重建图像具有较高的精度。     

基于遗传模拟退火算法的室内照明节能控制方法研究北大核心CSCD

目前的节能照明控制算法仍有陷入局部最优的问题。为了寻求全局最优解,提高室内照明的节能效果,设计一种遗传模拟退火算法对照明系统的控制参数进行优化求解。该算法通过在遗传操作后对优秀个体进行模拟退火处理,增强了算法的局部搜索能力。根据迭代的次数和种群的适应度对遗传概率进行自适应调节,使得算法在前期丰富种群多样性,避免算法“早熟”。提出基于人工神经网络的照度模型来计算室内照度分布,对照明舒适度进行评估,为构造优化算法的适应函数提供了依据。通过仿真实验,在本文介绍的照明场景应用遗传模拟退火算法,并与传统粒子群算法和遗传算法进行比较,其照明节能性能分别高出5.30%和13.61%。     

模拟退火算法与遗传算法在光谱椭偏数据处理中的应用比较

分别利用模拟退火算法和遗传算法在MATLAB 6.5中编写了一个数据处理程序,用来处理VASE椭偏仪在光谱范围为500nm～900nm所测得的椭偏数据。根据VASE椭偏仪的光度法原理,对评价函数方程进行了改进,并选择合适的退火参数和遗传参数进行计算,得到的数据处理结果与仪器处理结果基本一致。最后对两种算法在解决该类问题上的优劣进行了比较。     

Memoryless cooperative graph search based on the simulated annealing algorithm

We have studied the problem of reaching a globally optimal segment for a graph-like environment with a single or a group of autonomous mobile agents. Firstly, two efficient simulated-annealing-like algorithms are given for a single agent to solve the problem in a partially known environment and an unknown environment, respectively. It shows that under both proposed control strategies, the agent will eventually converge to a globally optimal segment with probability 1. Secondly, we use multi-agent searching to simultaneously reduce the computation complexity and accelerate convergence based on the algorithms we have given for a single agent. By exploiting graph partition, a gossip-consensus method based scheme is presented to update the key parameter--radius of the graph, ensuring that the agents spend much less time finding a globally optimal segment.     

Discrete channel modelling based on genetic algorithm and simulated annealing for training hidden Markov model

Hidden Markov models (HMMs) have been used to model burst error sources of wireless channels. This paper proposes a hybrid method of using genetic algorithm (GA) and simulated annealing (SA) to train HMM for discrete channel modelling. The proposed method is compared with pure GA, and experimental results show that the HMMs trained by the hybrid method can better describe the error sequences due to SA's ability of facilitating hill-climbing at the later stage of the search. The burst error statistics of the HMMs trained by the proposed method and the corresponding error sequences are also presented to validate the proposed method.     

模拟退火算法在波束图设计中的应用

摘要本文提出了基于模拟退火算法的波束设计方法。模拟退火算法模拟了固体缓慢退火从而获得最低内能的物理过程，是一种简单而有效的随机性全局优化算法。为证明该设计方法的可行性和有效性，给出了15元平面阵的设计实例以及仿真结果。结果表明，使用该方法设计的波束与常规方法相比，获得了更低的旁瓣级。     

用于衍射光学元件优化设计的遗传算法及其与模拟退火算法的比较

本文成功地将遗传算法运用于高维衍射位相光学元件的优化设计.并与模拟退火算法进行了比较.结果表明,该算法不仅对于二元,而且对于多元位相光学元件的优化疫计均是十分有效的.而且,它特别适用于利用光电混合处理系统进行优化计算.     

用模拟退火法进行纯永磁波荡器磁块组合优化

纯永磁波荡器由多个磁块组成,磁块的剩磁离散性会引起波荡器磁场误差,从而影响储存环工作状态和自发辐射谱质量。在波荡器磁块安装之前,使用模拟退火法对磁块进行组合排序优化,可以使峰值场强误差降低到10-4量级以下,磁场一次积分降低到10-6 T·m量级,二次积分降低到10-6 T·m2量级,优化结果不依赖于初始状态的选择。给出优化的详细过程,提出了根据磁块剩磁快速计算波荡器峰值场强误差和积分场的方法。     

基于多波长激光吸收光谱技术的气体浓度与温度二维分布遗传模拟退火重建研究

利用可调谐半导体激光吸收光谱技术实现气体浓度温度二维分布重建.设计了气体浓度温度二维分布重建测量系统,采用四路波分复用技术以减少投影光路布置数量和增加气体吸收测量信息.针对于图像重建过程中建立的非线性投影方程组,将遗传算法与模拟退火算法相结合进行求解,在实现全局最优搜索基础上提高算法搜索效率.建立燃烧环境下H2O浓度温度二维分布模型,借助于近红外波段1.3—1.5μm范围内4条H2O气体吸收谱线,利用数值模拟计算方法进行了气体分布重建,重建结果与模型符合得很好.通过在投影数据中添加不同比例的随机误差,考察其对气体分布重建结果的影响.研究表明,气体浓度分布重建结果对于投影误差不敏感,而增加投影误差幅值将导致温度分布重建均方误差增大。     

Noise barrier optimization using a simulated annealing algorithm

This paper presents a novel method to design a desired noise barrier using the global optimization of a simulated annealing (SA) algorithm. This method focuses on minimizing the barrier dimensions, which are related to material and construction costs, as well as satisfying the target sound pressure levels at receiver points on the condition of traffic noise. Various examples are presented to evaluate the optimized barrier dimensions according to given traffic noise sources, ground topography, surface conditions, and the influence of different receiver positions. As a result, a robust method is found that can determine optimized barrier configurations and dimensions that yield cost reductions.     

自适应模拟退火遗传算法在薄膜厚度及光学常数反演中的应用

准确的测量薄膜的厚度和光学常数,在薄膜的制备、研究和应用中都是十分重要的。借助Cauchy色散模型,通过薄膜透过率测量曲线,用改进的自适应模拟退火遗传算法对透过率曲线进行全光谱拟合,从而反演得到薄膜的厚度和光学常数。对由电子束蒸发制备的TiO2单层膜和SiO2/TiO2双层膜的厚度和光学常数进行了测量计算。实验结果表明,计算得到的光学参数与实测结果相一致,厚度误差小于2nm,在560nm波长处折射率误差小于0.03。     

Fiber Bragg grating distributed strain sensing: an adaptive simulated annealing algorithm approach

We demonstrate the use of adaptive simulated annealing (ASA) algorithm for determining the strain profile along a fiber Bragg grating (FBG) from its amplitude reflection spectrum. By combining the ASA algorithm and the matrix method for calculating the reflection spectrum of a FBG, the FBG sensor can be used for the distributed strain sensing. Experiments showed that the strain detection accuracy could be in the order of a few microstrains.     

Phase unwrapping with regularized phase-tracking technique based on simulated annealing algorithm

We propose an improved regularized phase-tracking (RPT) technique for unwrapping two-dimensional principal phase maps. The size of the neighborhood selected for plane approximation at each pixel is adjustable according to local noise severity. In the area of low noise, the size is small to improve processing speed. On the contrary, a neighborhood with large size is selected to enhance the noise-reduced ability in the high-noisy area. Further, simulated annealing (SA) algorithm is applied to RPT technique for finding the global optimum solutions. Numerical simulation proves that this SA-based RPT phase unwrapping technique is highly robust to noise and experimental results also show its feasibility in practical applications.     

基于遗传算法的Au-Cu-Pt三元合金纳米粒子的稳定结构研究

合金纳米粒子展示出单金属粒子所不具有的多功能性能, 而其稳定结构的研究对于进一步了解其催化性能具有重要的意义. 本文采用改进的遗传算法和量子修正Sutton-Chen型多体势对二十四面体Au-Cu-Pt三元合金纳米粒子的稳态结构进行了系统的研究. 针对不同尺寸、不同组成比例的合金纳米粒子, 探讨了遗传算法的收敛性及初始构型对稳态结构的影响. 计算的结果表明: 初始结构的选取并不影响最终的稳定结构, 并且改进的遗传算法具有较好的稳定性; Au和Cu形成表面偏聚, 而Pt则倾向于分布在内层; 当Au或Cu比例较小时, Au和Cu表现出表面最大偏聚; 当Au与Cu原子数之和大于表面原子数时, 二者表现出竞争偏聚, 且Cu的偏聚效应较强; 随着Au, Cu原子数继续增长至大于表面和次表面原子数之和时, Au的偏聚性能增强. 此外, Cu在占据表面后, 会越过次外层, 与Pt在内层形成混合相结构.     

Numerical and experimental study on coherent beam combining of fibre amplifiers using simulated annealing algorithm

We present the numerical and experimental study on the coherent beam combining of fibre amplifiers by means of simulated annealing (SA) algorithm. The feasibility is validated by the Monte Carlo simulation of correcting static phase distortion using SA algorithm. The performance of SA algorithm under time-varying phase noise is numerically studied by dynamic simulation. It is revealed that the influence of phase noise on the performance of SA algorithm gets stronger with an increase in amplitude or frequency of phase noise; and the laser array that contains more lasers will be more affected from phase noise. The performance of SA algorithm for coherent beam combining is also compared with a widely used stochastic optimization algorithm, i.e., the stochastic parallel gradient descent (SPGD) algorithm. In a proof-of-concept experiment we demonstrate the coherent beam combining of two 1083~nm fibre amplifiers with a total output power of 12~W and 93% combining efficiency. The contrast of the far-field coherently combined beam profiles is calculated to be as high as 95%.     

用模拟退火法进行纯永磁波荡器磁块组合优化

 纯永磁波荡器由多个磁块组成,磁块的剩磁离散性会引起波荡器磁场误差,从而影响储存环工作状态和自发辐射谱质量。在波荡器磁块安装之前,使用模拟退火法对磁块进行组合排序优化,可以使峰值场强误差降低到10 ^-4量级以下,磁场一次积分降低到10^-6 T·m量级,二次积分降低到10 ^-6 T·m ²量级,优化结果不依赖于初始状态的选择。给出优化的详细过程,提出了根据磁块剩磁快速计算波荡器峰值场强误差和积分场的方法。     

Structural optimization of Au–Pd bimetallic nanoparticles with improved particle swarm optimization method

Due to the dependence of the chemical and physical properties of the bimetallic nanoparticles(NPs) on their structures,a fundamental understanding of their structural characteristics is crucial for their syntheses and wide applications. In this article, a systematical atomic-level investigation of Au–Pd bimetallic NPs is conducted by using the improved particle swarm optimization(IPSO) with quantum correction Sutton–Chen potentials(Q-SC) at different Au/Pd ratios and different sizes. In the IPSO, the simulated annealing is introduced into the classical particle swarm optimization(PSO) to improve the effectiveness and reliability. In addition, the influences of initial structure, particle size and composition on structural stability and structural features are also studied. The simulation results reveal that the initial structures have little effects on the stable structures, but influence the converging rate greatly, and the convergence rate of the mixing initial structure is clearly faster than those of the core-shell and phase structures. We find that the Au–Pd NPs prefer the structures with Au-rich in the outer layers while Pd-rich in the inner ones. Especially, when the Au/Pd ratio is 6:4, the structure of the nanoparticle(NP) presents a standardized Pd_(core) Au_(shell) structure.     

A quantitative analysis of the simulated annealing algorithm: A case study for the traveling salesman problem

A quantitative study is presented of the typical behavior of the simulated annealing algorithm based on a cooling schedule presented previously by the authors. The study is based on the analysis of numerical results obtained by systematically applying the algorithm to a 100-city traveling salesman problem. The expectation and the variance of the cost are analyzed as a function of the control parameter of the cooling schedule. A semiempirical average-case performance analysis is presented from which estimates are obtained on the expectation of the average final result obtained by the simulated annealing algorithm as a function of the distance parameter, which determines the decrement of the control parameter.     

Non-minimum phase reconstruction from amplitude data in fiber Bragg gratings using an adaptive simulated annealing algorithm

Adaptive simulated annealing algorithm used for phase reconstruction in fiber Bragg grating (FBG) is presented. Theory and numerical simulations show that the non-minimum phase of the FBG can be reconstructed by using this method.     

Remote sensing of atmospheric duct parameters using simulated annealing

Simulated annealing is one of the robust optimization schemes. Simulated annealing mimics the annealing process of the slow cooling of a heated metal to reach a stable minimum energy state. In this paper, we adopt simulated annealing to study the problem of the remote sensing of atmospheric duct parameters for two different geometries of propagation measurement. One is from a single emitter to an array of radio receivers (vertical measurements), and the other is from the radar clutter returns (horizontal measurements). Basic principles of simulated annealing and its applications to refractivity estimation are introduced. The performance of this method is validated using numerical experiments and field measurements collected at the East China Sea. The retrieved results demonstrate the feasibility of simulated annealing for near real-time atmospheric refractivity estimation. For comparison, the retrievals of the genetic algorithm are also presented. The comparisons indicate that the convergence speed of simulated annealing is faster than that of the genetic algorithm, while the anti-noise ability of the genetic algorithm is better than that of simulated annealing.