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粒子群优化算法（PSO）是模仿鸟群寻找食物的社会行为的一种全局最优化算法,在多维空间函数寻优、动态目标寻优等方面有着收敛速度快、解质量高且需要设置的参数较少等优点.本文在研究常规粒子群优化算法的基础上,对常规的粒子群算法进行了改进,提出了一种新的惯性权重ω参数振荡递减策略,加快了PSO算法的收敛速度,构造的新算法称为阻尼粒子群优化算法.在MATLAB 6.5 编程环境中对阻尼PSO算法进行了数值实验,并对大地电磁测深的理论模型和实测数据进行了反演试算,结果表明,阻尼PSO算法不依赖于初始模型、能够搜索到全局极值,不易陷入局部极值,是一种快速有效的地球物理反演方法. 相似文献
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变异函数是地统计学中区域化变量空间结构分析和空间局部插值的主要分析工具.理论变异函数模型的获取是地质统计学中的基础性工作,它是了解区域化变量的变异特征、进一步对地质统计学计算的必要环节.针对现有的理论变异函数的拟合方法,如人工拟合法、线性规划拟合法、加权多项式拟合法、目标规划拟合法等的不足之处,充分利用粒子群优化算法在求解非线性优化问题时具有的全局寻优的特点,提出基于粒子群优化的理论变异函数拟合方法.在实例应用中,分别利用粒子群优化算法和加权多项式拟合方法进行理论变异函数拟合,交叉验证结果表明粒子群优化算法预测精度较高,具有较强的稳健性. 相似文献
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从背景噪声中提取瑞雷波频散曲线并通过反演获得地下横波速度结构已被广泛应用于大尺度的地下结构探测和小尺度的工程勘探中.基于频散函数的反演目标函数可以有效解决多阶模频散曲线联合反演的模式误判问题,然而其广泛分布的局部极值导致更为严重的多解性,在大范围的参数搜索空间下很难获得最优解,需要搭配全局搜索性能强的优化算法.本文提出局部优化粒子群算法(PSOG),通过粒子迭代过程中引入局部优化方法提高种群多样性,避免陷入局部极值并加快收敛速度.为验证新算法的有效性,结合基于久期函数的目标函数对理论合成数据进行反演,结果表明,局部优化粒子群算法比传统算法的稳定性与准确性都有显著提高.处理了上海苏州河地区的背景噪声数据,成功地对古河道切割造成的软弱层进行成像.PSOG算法与新型反演目标函数的结合在背景噪声勘探的工程应用上具有巨大潜力. 相似文献
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磁法反演属于非线性最优化问题,具有多变量、目标函数多极值、反演多解性等特点,因此,需要稳定的和高效的优化反演算法.粒子群优化已开始被用于地球物理反演计算,但是对于高维数、多峰值函数,粒子群的收敛精度不高,容易陷入局部极值.如果将混沌局部搜索和粒子群优化的优势相结合,通过将种群搜索过程对应为混沌轨道的遍历过程,可使标准粒子群优化的搜索过程具有避免陷入局部极小的能力.本文利用混沌-粒子群优化用于磁法反演计算.数据试验结果表明,该方法可以用于磁法数据的地球物理非线性反演,并且在一定程度上优于标准粒子群优化方法. 相似文献
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《应用地球物理》2017,(4)
目前,各种主、被动源瑞雷波勘探方法在近地表探测中扮演着日益重要的角色,利用瑞雷波频散曲线反演可以得到近地表横波速度信息,但是瑞雷波频散曲线反演问题是高度非线性的全局优化问题。为了缓解陷入局部最优解的风险,本文将一种新的全局优化方法一洗牌蛙跳算法引入到瑞雷波频散曲线反演中。洗牌蛙跳算法是一种群智能优化算法,通过模拟青蛙种群的觅食行为来实现最优化问题的求解,具有计算速度快,需要调整的参数少,全局寻优能力强的优点。为了检验洗牌蛙跳算法的可靠性和计算能力,首先对不含噪声和含噪声的四层理论模型进行了反演试算。然后,利用不含噪声数据对洗牌蛙跳算法与粒子群优化算法进行比较分析。最后,对实际数据进行反演,以检验洗牌蛙跳算法的实用性。理论地层模型和实际数据的测试结果表明:洗牌蛙跳算法可以有效地定量解释瑞雷波频散曲线,收敛速度、反演精确总体优于经典粒子群优化算法与改进粒子群优化算法,具有很大的发展潜力。 相似文献
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《地震工程与工程振动》2017,(2)
针对标准粒子群优化算法易陷入局部最优及多粒子群协同优化算法(MPSCO)仍存在的不足,提出了一种改进的多粒子群协同优化算法,并将其与Newmark常平均加速度法、假设检验相结合,研发出一种适用于框架结构的损伤检测策略。首先,针对结构损伤前的实测加速度响应,运用改进MPSCO算法识别出结构损伤前的层间刚度值;第二,针对结构损伤后的实测加速度响应并运用同样的方法识别出结构损伤后的层间刚度值;第三,比较所识别出的结构损伤前后的层间刚度值并结合假设检验从而完成损伤检测。最后通过一7层钢框架的数值模型和实验室试验验证了本文所提损伤检测策略的可靠性。研究结果表明,本文所提的损伤检测策略能够精确地识别结构损伤同时具有较好的抗噪性能和鲁棒性。 相似文献
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《地震工程与工程振动》2021,41(2)
粒子群优化算法是模拟群体智能所建立起来的一种全局优化算法,在解决多参数非线性函数的优化问题上具有良好的性能,为了有更好的收敛精度和更快的收敛速度,本文构建了带有压缩因子的粒子群算法,可用于设计反应谱的标定。利用这一方法可给出第一拐点周期、特征周期、平台值和衰减指数等刻画设计反应谱特征的参数值。本文以埃尔森特罗台(El Centro)加速度时程的反应谱标定为例,采用本文提出的改进粒子群算法、Newmark三参数法、双参数法和差分进化算法对其进行标定。对比分析了4种标定方法给出的特征参数及计算精度,实例证明,改进粒子群算法具有较高的精度,给出的设计反应谱较好地反映了地震反应谱的特征。 相似文献
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根据不同流体性质在角度道集上所反映特征的差异,构建了多属性角度叠加数据体组合流体识别因子.并将量子粒子群与模糊神经网络相结合,利用量子粒子群方法来优化模糊神经网络中的连接权值和隶属函数参数,并进行一系列的改进措施,显著提高了算法的全局寻优能力.将近远角度叠加数据体组合流体识别因子作为改进模糊神经网络的输入,流体性质作为输出,同时引入“相控流体识别”的思想,利用碳酸盐岩储集相进行控制,建立了碳酸盐岩流体识别模型.通过塔中实际井区进行验证,证明该方法能够提高流体的识别精度,具有很好的实际应用价值. 相似文献
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估计转换波的静校正量是一个复杂的非线性问题,常规的线性静校正方法无法取得好的效果.粒子群算法是一种很好的非线性全局最优化方法,但其缺点是"早熟"现象严重.最大能量法是一种常规求取静校正量的方法,局部寻优能力强且收敛速度快是其优点,但是当地震记录含有大的静校正量时易收敛于局部极值.本文在标准粒子群算法的基础上发展出了一种改进的粒子群算法:团体粒子群算法.并且通过对Rastrigin函数的寻优实验证明了其全局寻优能力优于标准粒子群算法.同时为了解决转换波静校正问题串行融合了团体粒子群算法和最大能量法.最后,建立了含一个水平反射层的模型并合成地震记录,加入随机值作为检波点静校正量.对合成的地震数据分别利用团体粒子群和最大能量的串行融合算法、标准粒子群算法和最大能量法求取静校正量并进行静校正.结果证明串行融合算法得到的静校正量与理论值误差很小,静校正后的叠加剖面连续性较好. 相似文献
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基于零阶和一阶优化算法的建筑结构抗震优化设计 总被引：2，自引：0，他引：2
针对第三水准“大震不倒”的抗震设防目标,提出一种建筑结构的抗震优化设计方法,依据“用相同的投资获最好的设计”的设计理念,建立了在强烈地震波的作用下,以建筑结构最大的层间相对位移最小化作为优化目标,同时满足体积约束的优化数学模型,并采用动力有限元分析模型和高效的显式动力分析方法进行结构分析获得最大的层间相对位移,采用零阶和一阶优化算法分别求解优化数学模型,在显式动力分析软件ANSYS／LS—DYNA的基础上进行二次开发,实现了一个三维框架结构的抗震优化设计。数值结果表明该方法能获得较高质量的解,经优化设计后建筑结构的抗震性能得到了很大的改善。 相似文献
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The optimal seismic design of structures requires that time history analyses （THA） be carried out repeatedly. This makes the optimal design process inefficient, in particular, if an evolutionary algorithm is used. To reduce the overall time required for structural optimization, two artificial intelligence strategies are employed. In the first strategy, radial basis function （RBF） neural networks are used to predict the time history responses of structures in the optimization flow. In the second strategy, a binary particle swarm optimization （BPSO） is used to find the optimum design. Combining the RBF and BPSO, a hybrid RBF-BPSO optimization method is proposed in this paper, which achieves fast optimization with high computational performance. Two examples are presented and compared to determine the optimal weight of structures under earthquake loadings using both exact and approximate analyses. The numerical results demonstrate the computational advantages and effectiveness of the proposed hybrid RBF-BPSO optimization method for the seismic design of structures. 相似文献
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由地震等自然灾害引发的等级多变强随机振动会对大跨度钢管混凝土柱结构产生较大的破坏,造成相关建筑全结构寿命周期性衰减。提出一种随机振动下大跨度钢管混凝土柱结构的抗震性测试方法,在等级多变强随机振动的情况下,设计测试模型,利用信号的协方差矩阵将振动信号与噪声进行分离,通过计算振动信号的强度、后验密度及权值系数等对振动信号进行预处理,获取单一寿命衰减参数;在此基础上引入粒子群算法,求解大跨度钢管混凝土柱结构寿命衰减抑制周期,判断其抗震性。实验结果表明,按照大跨度钢管混凝土柱结构寿命衰减抑制周期的判断方法,可实现对相关建筑结构在等级多变强随机振动下的抗震性测试。 相似文献
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本文探讨了粒子群优化(PSO)算法在叠前地震角道集子波反演中的应用.在基本最优PSO算法的基础上,提出了对粒子更新速度进行平滑滤波的改进最优粒子群算法.由于代表子波的粒子的维数较大,如果粒子的各维元素相互独立,将导致粒子速度更新紊乱,影响搜索速度.通过对粒子速度进行三点均值滤波,加强了单个粒子各维元素的相互联系,并防止了粒子速度逃逸,使粒子更快地向有利于最优解的位置收敛.该方法应用于叠前角道集子波的反演中,取得了较好的子波反演效果,证明了本文方法的有效性. 相似文献
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《地震工程与工程振动(英文版)》2015,(1)
A reliable seismic-resistant design of structures is achieved in accordance with the seismic design codes by designing structures under seven or more pairs of earthquake records. Based on the recommendations of seismic design codes, the average time-history responses(ATHR) of structure is required. This paper focuses on the optimal seismic design of reinforced concrete(RC) structures against ten earthquake records using a hybrid of particle swarm optimization algorithm and an intelligent regression model(IRM). In order to reduce the computational time of optimization procedure due to the computational efforts of time-history analyses, IRM is proposed to accurately predict ATHR of structures. The proposed IRM consists of the combination of the subtractive algorithm(SA), K-means clustering approach and wavelet weighted least squares support vector machine(WWLS-SVM). To predict ATHR of structures, first, the input-output samples of structures are classified by SA and K-means clustering approach. Then, WWLS-SVM is trained with few samples and high accuracy for each cluster. 9- and 18-storey RC frames are designed optimally to illustrate the effectiveness and practicality of the proposed IRM. The numerical results demonstrate the efficiency and computational advantages of IRM for optimal design of structures subjected to time-history earthquake loads. 相似文献
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The equivalent linearization method approximates the maximum displacement response of nonlinear structures through the corresponding equivalent linear system.By using the particle swarm optimization technique,a new statistical approach is developed to determine the key parameters of such an equivalent linear system over a 2D space of period and damping ratio.The new optimization criterion realizes the consideration of the structural safety margin in the equivalent linearization method when applied to the performance-based seismic design/evaluation of engineering structures.As an application,equations for equivalent system parameters of both bilinear hysteretic and stiffness degrading single-degree-offreedom systems are deduced with the assumption of a constant ductility ratio.Error analyses are also performed to validate the proposed approach. 相似文献
19.
Optimized earthquake response of multi‐storey buildings with seismic isolation at various elevations
The response of multi‐storey structures can be controlled under earthquake actions by installing seismic isolators at various storey levels. By vertically distributing isolation devices at various elevations, the designer is provided with numerous options to appropriately adjust the seismic performance of a building. However, introducing seismic isolators at various storey levels is not a straightforward task, as it may lead to favourable or unfavourable structural behaviour depending on a large number of factors. As a consequence, a rather chaotic decision space of seismic isolation configurations arises, within which a favourable solution needs to be located. The search for favourable isolators' configurations is formulated in this work as a single‐objective optimization task. The aim of the optimization process is to minimize the maximum floor acceleration of the building under consideration, while constraints are specified to control the maximum interstorey drift, the maximum base displacement and the total seismic isolation cost. A genetic algorithm is implemented to perform this optimization task, which selectively introduces seismic isolators at various elevations, in order to identify the optimal configuration for the isolators satisfying the pre‐specified constraints. This way, optimized earthquake response of multi‐storey buildings can be obtained. The effectiveness of the proposed optimization procedure in the design of a seismically isolated structure is demonstrated in a numerical study using time‐history analyses of a typical six‐storey building. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
20.
Anxu Wu Xiangdong Lin Changsheng Jiang Yongxian Zhang Xiaodong Zhang Mingxiao Li Ping&# an Li 《地震科学（英文版）》2009,22(5):563-574
In the research of projection pursuit for seismic comprehensive forecast, the algorithm of projection pursuit regression (PPR) is one of most applicable methods. But generally, the algorithm structure of the PPR is very complicated. By partial smooth regressions for many times, it has a large amount of calculation and complicated extrapolation, so it is easily trapped in partial solution. On the basis of the algorithm features of the PPR method, some solutions are given as below to aim at some shortcomings in the PPR calculation: to optimize project direction by using particle swarm optimization instead of Gauss-Newton algorithm, to simplify the optimal process with fitting ridge function by using Hermitian polynomial instead of piecewise linear regression. The overall optimal ridge function can be obtained without grouping the parameter optimization. The modeling capability and calculating accuracy of projection pursuit method are tested by means of numerical emulation technique on the basis of particle swarm optimization and Hermitian polynomial, and then applied to the seismic comprehensive forecasting models of poly-dimensional seismic time series and general disorder seismic samples. The calculation and analysis show that the projection pursuit model in this paper is characterized by simplicity, celerity and effectiveness. And this model is approved to have satisfactory effects in the real seismic comprehensive forecasting, which can be regarded as a comprehensive analysis method in seismic comprehensive forecast. 相似文献