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Structural optimization of Au–Pd bimetallic nanoparticles with improved particle swarm optimization method 下载免费PDF全文
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. 相似文献
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针对粒子群优化算法应用在目标跟踪时,其惯性权重调节机制的局限性,提出了改进的粒子群优化目标跟踪方法。首先,对目标及粒子群算法中相应参数进行初始化;接着,引入粒子进化率的概念,对惯性权重调节机制进行改进,根据每代每个粒子的不同状态及时调整惯性权重;然后,在更新粒子的速度和位置的同时,更新个体最优解和全局最优解,进行下一次迭代;最后,比较粒子的适应度,选择相似性函数值最大的区域为目标。实验结果表明,该方法与使用自适应惯性权重调节机制的粒子群优化目标跟踪方法相比,减少了获取相同适应度所需的迭代次数,运算效率提高了42.9%。实现了目标在相似性函数出现"多峰"情况下的准确定位,对目标出现部分遮挡的情况具有很好的适应性。 相似文献
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为提升随机共振理论在微弱信号检测领域中的实用性,以随机共振系统参数为研究对象,提出了基于量子粒子群算法的自适应随机共振方法.首先将自适应随机共振问题转化为多参数并行寻优问题,然后分别在Langevin系统和Duffing振子系统下进行仿真实验.在Langevin系统中,将量子粒子群算法和描点法进行了寻优结果对比;在Duffing振子系统中,Duffing振子系统的寻优结果则直接与Langevin系统的寻优结果进行了对比.实验结果表明:在寻优结果和寻优效率上,基于量子粒子群算法的自适应随机共振方法要明显高于描点法;在相同条件下,Duffing振子系统的寻优结果要优于Langevin系统的寻优结果;在两种系统下,输入信号信噪比越低就越能体现出量子粒子群算法的优越性.最后还对随机共振系统参数的寻优结果进行了规律性总结. 相似文献
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提出了一种采用圆弧型结构的宽频Wilkinson功分器的优化设计方法。在研究奇模-偶模分析理论的基础上,首先,根据奇-偶模分析理论得出设计电路的参数方程,接着采用粒子群算法对方程进行优化,获得具体的设计参数,有效提高功分器的设计效率与准确性。为了验证设计方案的正确性,设计了8~12 GHz的宽带功分器。测试结果显示,在工作频段范围内,各端口回波损耗小于-20 dB,传输损耗小于3.4 dB,隔离度小于-20 dB,实物测试结果与仿真结果吻合良好,验证了设计方法的可行性。 相似文献
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Design of high-dispersion mirrors (HDMs) using a proposed multi-swarm optimization method is reported. We design HDMs for Yb:YAG disk oscillator at 1030 nm and ultrashort pulse Cr:YAG laser at 1550 nm. The results show that the optimum group delay dispersion and reflectance can be obtained with optimal number of layers. The proposed optimization method has a fast convergence rate and powerful global search ability and can be utilized effectively for the design of a variety of optical thin film filters. 相似文献
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Design of broadband hybrid fiber amplifier based on particle swarm optimization algorithm北大核心CSCD 下载免费PDF全文
基于铒/镱共掺光纤放大器(erbium-ytterbium doped fiber amplifier, EYDFA)的理论模型和受激拉曼散射效应的分析理论,利用EYDFA和拉曼光纤放大器(Raman fiber amplifier, RFA)的增益谱互补特性,研究并设计了EYDFA与二阶多泵浦RFA相结合的混合放大器结构。为了得到高增益和低平坦度的混合放大器,引入了粒子群算法优化泵浦光波长和功率。仿真结果表明:在不使用增益均衡器的条件下,所设计的混合光纤放大器在输出端得到了近似相等的输出光功率,在90 nm的带宽范围内平均增益为38.78 dB,增益平坦度为1.1 dB,为混合放大器的设计和优化提供了参考。 相似文献
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针对2维电子光学多参量优化问题,采用微动粒子群优化算法,在给出目标电子轨迹和优化范围的前提下,可以得到趋近于该电子轨迹的真空边界和聚束磁结构。该算法分为前后两阶段:第一阶段采用前后试探法(微动),同时参照最优粒子的信息;第二阶段采用标准粒子群优化算法。针对涉及多个相关参量的电子光学设计问题,标准粒子群优化算法仅能保证以较高概率收敛到局部最佳解,而微动粒子群优化算法能以较高概率收敛到全局最佳解,并且展现了多核计算机在电子光学设计上的潜力。初步的软件试验显示:消耗人类工程师几周时间的电子光学设计问题,用微动粒子群算法在普通个人计算机上几十小时就能完成。 相似文献
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提出改进的粒子群优化算法,获得波束方向图主瓣宽度和旁瓣级折中的优化立体阵形,避免基本实数粒子群算法仅采用旁瓣级或主瓣宽度一个性能指标优化而导致另一个性能指标恶化的问题,利用阵列视角限制进一步优化立体阵形并设计了声成像测量系统。改进的粒子群算法与基本粒子群算法仿真优化阵形比较表明改进粒子群算法设计的优化阵形在保持较窄的主瓣宽度的条件下具有较低的旁瓣级。阵列声成像测量系统的性能测量分析结果表明该系统的空间分辨率和旁瓣抑制能力与理论结果接近,验证了所提算法的有效性。 相似文献
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为降低相控阵超声检测全聚焦算法的成像数据量及阵列稀疏优化的计算时间,研究了一种用于稀疏阵列全聚焦成像的阵列优化算法,并通过实验对其成像效果进行了验证。针对目前超声相控阵检测的全矩阵采集数据量大、全聚焦算法成像时间长的难点,该文通过构建稀疏阵列,在保证成像质量的同时显著降低成像数据量,提高了全聚焦算法的成像效率。通过以主瓣宽度、旁瓣峰值以及主瓣峰值作为约束条件构建适应度函数,采用粒子群算法得到稀疏阵元位置分布并进行阵元权重修正,并将其用于稀疏全聚焦成像。相比全阵元成像,使用粒子群算法所得的稀疏阵列的阵元个数降低了56.25%、65.62%,数据使用量降低了80.86%、88.18%。在阵列优化方面,相比遗传算法减少了84.86%的计算时间。 相似文献
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For the adjustable parameters stochastic resonance system, the selection of the structural parameters plays a decisive role in the performance of the detection method. The vibration signal of rotating machinery is non-linear and unstable, and its weak fault characteristics are easily concealed by noise. Under strong background noise interference, the detection of fault features is particularly challenging. Therefore, a type of weak fault feature extraction method, named knowledge-based particle swarm optimization algorithm for asymptotic delayed feedback stochastic resonance (abbreviated as KPSO-ADFSR) is proposed. Through deduction under adiabatic approximation, we observe that both the asymmetric parameters, the length of delay and the feedback strength, impact the potential function. After adjusting the asymmetric parameters of the system, the output signal-to-noise ratio (SNR) is used as the fitness function, and the setting of the relationship between the noise intensity and barrier height is used as the prior knowledge of the particle swarm algorithm. Through this algorithm, the delay length and the feedback strength are optimized. This method achieves global optimization of system parameters in a short time; it overcomes the shortcomings of the traditional stochastic resonance method, which has a long convergence time and tends to easily fall into local optimization. It can effectively improve the detection of weak fault features. In the bearing rolling body pitting corrosion failure experiment and steel field engineering experiment, the proposed method could extract the characteristics of a weak fault more effectively than the traditional stochastic resonance method based on the standard particle swarm algorithm. 相似文献
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For modeling of jute as acoustic material, knowledge of its non-acoustical parameters like porosity, tortuosity, air flow resistivity, thermal and viscous characteristic lengths is a prime requisite. Measurement of these non-acoustical parameters is not straightforward and involves a dedicated measurement setup. So in order to overcome this issue, the inverse acoustical characterization can be used. In this paper, the particle swarm optimization method (PSO) is used as an optimization method. This method estimates the non-acoustical parameters of jute material in felt form by minimizing the error between experimental and theoretical sound absorption data. In this work, the impedance prediction models for fibrous materials like Johnson–Champoux–Allard model with rigid and limp frame and Garai–Pompoli model is used for sound absorption coefficient calculation by the transfer matrix method along with the PSO. The inverse estimated non-acoustical parameters for jute material are then compared with estimated and experimentally measured parameters for jute felts. Using these inversely predicted parameters, sound absorption of multilayer sound absorbers is also studied. 相似文献
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为了避免粒子群算法退化和运算量大问题,提出利用修补粒子群算法对红外目标进行跟踪。该算法先用设置粒子的惯性因子对搜索到的红外目标位置进行修正,使粒子的位置达到局部最优点和全局最优点;然后通过粒子群收缩因子限制在边界搜索,消除目标位置的模糊性。利用该方法对空中红外战斗机图像跟踪仿真,结果显示在500次粒子迭代,100次跟踪中误差为2.83%,在最大惯性权值为1.2和最小惯性权值为0.3时跟踪效果最接近真实目标,且边缘最清晰。 相似文献
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The multi-phase particle swarm optimization (MPPSO) technique is applied to retrieve the particle size distribution (PSD) under dependent model.Based on the Mie theory and the Lambert-Beer theory, three PSDs, i.e., the Rosin-Rammer (R-R) distribution, the normal distribution, and the logarithmic normal distribution, are estimated by MPPSO algorithm.The results confirm the potential of the proposed approach and show its effectiveness.It may provide a new technique to improve the accuracy and reliability of the PSD inverse calculation. 相似文献
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We extensively explore the high-pressure structures of InBi by using a newly developed particle swarm optimization algorithm. An orthorhombic Imma structure is discovered to be stable from 43.7 GPa to 107.9 GPa, ruling out the previously speculated cubic structure. Further increasing the pressure, we find a tetragonal P4/nmm structure which is energetically more favourable from 107.9 GPa to 200 GPa. Especially, the tetragonal P4/nmm structure is known to occur at high pressure in the structures of ZnO and MgTe. We also predict this structure to be a high-pressure structure of ZnTe. Thus the tetragonal P4/nmm structure may be a universal high-pressure structure of the Ⅱ-Ⅵ and the Ⅲ-Ⅴ compounds. 相似文献