A Simple Application and Design of Genetic Algorithm in Card Problem

According to traditional card problem solving which is based on the idea of genetic algorithm(GA),a set of algorithms is designed to find final solution.For each process in genetic algorithm,including choices of fitness function,parameters determination and coding scheme selection,classic algorithm is used to realize the various steps,and ultimately to find solution of problems.

基于拟合椭圆的等震线长短轴测量方法

提出了一种改进的拟合椭圆算法用于测量等震线长短轴,即将等震线测量的模式和直接测量算法的概念以约束的形式加入拟合椭圆算法,并使用最小二乘法求解椭圆系数,在与传统等震线测量方法保持一致的基础上,减少了直接测量方法的主观不确定性。在此基础上讨论了拟合椭圆算法的适用性和鲁棒性,将等震线长短轴的测量结果与前人的结果进行了对比。结果表明:拟合椭圆算法的适用性较好,可用于等震线的拟合;拟合椭圆算法的鲁棒性较好,计算结果较为稳定;对于未闭合且形状复杂的等震线,计算结果相对离散,要单独验证结果是否合理;利用拟合椭圆算法得到的等震线长短轴结果与前人的结果较为一致,可用于建立烈度衰减关系。

面向激光测振应用的改进相位生成载波解调算法

为了解决相位生成载波解调方案应用于激光测振技术时,系统中存在的非线性失真问题,提出一种改进相位生成载波解调算法。该算法采用低频、大幅值的相位调制和迭代重加权椭圆特殊拟合对两路含有非线性误差的正交信号进行校正以抑制非线性失真。其中,低频相位调制由三角波信号驱动压电换能器生成,确保小信号情况下椭圆拟合结果的准确性。迭代重加权椭圆特殊拟合可以减小离群数据的影响并避免拟合结果退化为双曲线,具有精度高、鲁棒性好和计算效率高的优点。实验结果表明改进相位生成载波解调算法可以有效抑制激光测振实验系统的非线性失真,在不同相位调制深度(0.8~3.4 rad)下解调信号的信纳比和总谐波失真稳定,对应的标准差分别为0.55 dB和0.03%。系统的响应线性度优于99.99%,动态范围可达103.9 dB@500 Hz,总谐波失真为1%且工作频宽为20~8000 Hz。与传统相位生成载波解调方案相比,该算法不仅显著抑制了非线性失真,还克服了椭圆拟合算法在小信号下无法工作的缺点。

基于主从关联优化的产品族参数规划方法研究

针对产品族优化设计中存在的共性与个性的相互依存、制约关系,研究面向产品族的主从关联的参数优化规划技术。建立基于灵敏度分析的产品族参数识别划分方法,根据产品族设计参数的主从关联特点,建立优化问题的双层规划模型。提出一种采用多项式响应面拟合和遗传算法相结合的混合算法实现双层规划,下层采用多项式响应面法将双层优化目标拟合成为单层优化目标,在上层实现产品族公共参数的优化,再通过上层可适应参数的松弛约束关系传递,在下层利用遗传算法实现变型产品的参数优化。以起重机卷筒组件产品族规划为例,基于所提出的主从关联优化方法,得到个性变型产品参数最优值,为起重机卷筒组件产品及类似产品的产品族优化设计提供一种方法借鉴。

基于Vector Fitting的光伏并网逆变器控制器参数频域辨识方法

光伏并网逆变器通常含有内外环、锁相环等不同带宽控制环节,且控制器参数往往并不可知,即存在“灰箱”问题。为准确辨识不同带宽控制器参数,提出一种基于端口导纳特性的光伏并网逆变器控制器参数频域辨识方法。首先,建立典型控制下光伏并网逆变器交流端口的dq理论导纳模型,得到其理论导纳标准式;然后,通过扫频手段获得光伏并网逆变器交流端口的测量导纳数据,并采用Vector Fitting算法对测量的端口导纳数据进行矢量拟合,得到拟合导纳标准式;最后,运用最小二乘原理使理论导纳标准式与拟合导纳标准式对应项系数差值的平方和最小,从而辨识得到光伏并网逆变器控制器参数的估计值。参数辨识实例表明,所提方法能够同时准确辨识出不同带宽控制器参数。

基于遗传-模拟退火算法修正高斯烟羽模型参数

高斯烟羽模型由于受到地形地貌与气象条件等因素的影响,难以准确反映大气的实际扩散过程。为解决上述问题,首先在经验参数作为先验值的基础上,通过遗传算法对实际观测数据进行参数反演修正,根据观测结果调整模型参数,提高模型的准确性;然后,为进一步优化参数修正结果,引入模拟退火算法,通过随机搜索和逐步降温的策略来跳出遗传算法可能陷入的局部最优解,进一步改善模型的性能。为了评估修正效果,建立一个基于权重的模型值与观测值之间差异的适应度函数,通过比较修正前后的误差率来判断参数修正对高斯烟羽模型的影响程度。仿真实验的结果表明,所提出的遗传-模拟退火算法模型能够有效地修正高斯烟羽模型中的扩散参数,修正后的模型在预测污染物浓度方面的误差率下降了89.40%。所提模型可为环境保护和污染防治提供重要的理论支撑和决策依据,具有较大的应用潜力。

基于代理模型进化的高效神经网络架构搜索

针对传统人工神经网络设计的时间复杂性与调试困难等问题,研究基于神经网络架构搜索的高效神经网络架构自动搜索方法,解决网络设计方案,提出了一种代理模型进化方法的高效神经网络搜索方法。上述方法将代理模型集成到遗传算法中,通过训练代理模型将预测卷积神经网络(Convolutional Neural Networks,CNN)性能问题转化为二值分类问题,加速网络评估过程。另外,在最新一代模型中,子模型通过继承父模型参数,在训练数据集上训练较少次数,加速最优网络的生成。所提方法在CIfar-10数据集上分类精度为95.6%,模型参数为3.4M;在Cifar-100数据集上分类精度为77.46%,模型参数为4.3M。由于使用代理模型和参数共享,新方法在cirar-10数据集上经过2.5天搜索获得性能优异的模型,避免了43.8%的候选CNN训练。

基于脉冲耦合神经网络的红外图像分割算法研究

红外图像噪声多、结构复杂,传统的分割方法难以对红外图像实现完整的分割。脉冲耦合神经网络(PCNN)参数众多,而人工调整网络参数耗时耗力。为了避免人工调整网络参数、实现对红外图像较完整的分割,将粒子群优化(PSO)算法和改进的PCNN相结合,提出了一种新的红外图像分割算法。首先,对红外图像进行预处理。其次,为了减少网络参数,对PCNN进行了化简。然后,将预处理图像输入网络进行循环迭代,利用PSO算法计算每次迭代的分割结果的适应函数值,从而确定群体和个体最佳参数。最后,通过种群最佳参数得到分割结果。为了验证算法的分割性能,试验使用了不同的自然风景图像和红外图像。试验结果表明,所提算法可以对红外和自然风景图像实现较完整的分割;无论是分割效果还是定性分析,所提算法都要优于传统算法。

基于遗传算法的隧道光面爆破参数优化模型研究

隧道光面爆破是一种控制爆破技术,能够保持新壁面平整而不受明显破坏。提出了一种基于遗传算法的隧道光面爆破参数优化模型,该模型以隧道光面爆破效果的综合评价函数为目标函数,以隧道开挖断面尺寸、岩性等级、地质条件等为约束条件,以周边孔间距、光爆层厚度、装药量等为决策变量,通过选择、交叉、变异等操作,不断产生新的个体,并根据适应度函数评价个体的优劣,最终得到最优或近似最优的隧道光面爆破参数。通过算例分析,验证了该模型的有效性和可行性,为隧道工程提供了合理且优化的光面爆破参数,提高了隧道质量和安全性。

遗传算法在相似材料配比试验设计中的应用研究

为探究相似材料配比优化问题,选取水膏比(水与石膏质量之比)为变量因素,基于Matlab环境进行遗传算法的相似材料配比优化研究。设计以1/15拉压比为主要参照目标,通过力学性质试验获取不同水膏比的相似材料单轴抗压强度、抗拉强度、弹性模量、泊松比、内摩擦角和内聚力6项力学特性参数,对其进行回归拟合,并构建遗传算法的相似材料配比优化模型。经对输出结果的二次试验检验可得到较好的配比优化效果,研究结果可为相似材料配比优化方法提供一定的理论依据。

Implementation of Dynamic System Control Circuit Board Test System of Pure Electric Vehicles

The dynamic system control circuit board(DSCCB)is one of the most important components for dynamic system of pure electric vehicles. The current detection of the DSCCB is done manually, which is not only inefficient in the detection but also difficult to guarantee the data accuracy. In order to improve the detection efficiency and accuracy, a new testing system is designed by Labview. The total test time can be further reduced by about 75% compared with the results of the manual detection. In this paper, the three-parameter sine wave curve-fit algorithm theory is applied to the phase delay detection of the current sensor sampling circuit on the DSCCB. This method solves the problem of big error in the phase delay detection.

Measurement of the banana pseudo-stem phenotypic parameters based on ellipse model

The measurement of banana pseudo-stem phenotypic parameters is a critical way to evaluate the growth status of bananas,and it can provide essential data support for mechanized cultivation operations such as fertilization and pesticide application.Existing studies mainly measure the diameter of banana pseudo-stem as its phenotypic parameter.The banana pseudo-stem cross section was closer to an ellipse other than a standard circle,so the diameter parameter cannot adequately represent the phenotypic characteristics of the banana plant.In this study,an automatic measuring device for banana pseudo-stem phenotypic parameters was developed.The device,which integrates three different types of sensors:a laser ranging sensor,a rotary encoder,and a digital camera,were used to obtain the point cloud and image data of banana pseudo-stem.A K-means point clouds clustering algorithm based on Euclidean distance was proposed.The point cloud of banana pseudo-stem was identified and extracted.A three-dimensional reconstruction algorithm based on the ellipse model was also proposed.The three-dimensional contour of the pseudo-stem was calculated to obtain three types of phenotypic parameters:the long axis length,the short axis length,and the perimeter.Further,a synchronous trigger image acquisition mechanism was used to take pictures of pseudo-stems during measurement.It can be utilized for manual assessment of the growth status of the banana.Field experimental results showed that the three banana phenotypic parameters had a high correlation with the manual measurement results,and R^(2)is always more significant than 0.95,the total average measurement error and relative error were only 6.16 mm and 4.38%,respectively,both are within the acceptable agronomy range.In general,this method has good universality for plant stem detection,and the stem phenotypic parameters can be obtained by means of non-contact test,which is of great significance to the mechanized cultivation of the forest and fruit industry.

A Statistical Model for Phase Difference Spectrum of Ground-Motion and Its Application in Generating Non-Stationary Seismic Waves

The intensity non-stationarity is one of the most important features of earthquake records.Modeling of this feature is significant to the generation of artificial earthquake waves.Based on the theory of phase difference spectrum,an intensity non-stationary envelope function with log-normal form is proposed.Through a tremendous amount of earthquake records downloaded on Kik-net,a parameter fitting procedure using the genetic algorithm is conducted to obtain the value of model parameters under different magnitudes,epicenter distances and site conditions.A numerical example is presented to describe the procedure of generating fully non-stationary ground motions via spectral representation,and the mean EPSD(evolutionary power spectral density)of simulated waves is proved to agree well with the target EPSD.The results show that the proposed model is capable of describing the intensity non-stationary features of ground motions,and it can be used in structural anti-seismic analysis and ground motion simulation.

Singularity of Some Software Reliability Models and Parameter Estimation Method

According to the principle, “The failure data is the basis of software reliability analysis”, we built a software reliability expert system (SRES) by adopting the artificial intelligence technology. By reasoning out the conclusion from the fitting results of failure data of a software project, the SRES can recommend users “the most suitable model” as a software reliability measurement model. We believe that the SRES can overcome the inconsistency in applications of software reliability models well. We report investigation results of singularity and parameter estimation methods of experimental models in SRES.

基于高频信号注入的同步电机无传感器控制

针对现有低速同步电机无传感器控制精度低、运算复杂的问题,提出了一种适用于静止和低速应用场合的高频电压信号注入的同步电机无传感器驱动控制方法(椭圆拟合技术)。首先,建立了永磁同步电动机(PMSM)的数学模型,分析了椭圆拟合技术判断永磁同步电机转子位置的原理;其次,通过对比线性最小二乘法问题的3种求解方法,显示了QR分解法的优势,并提出了椭圆拟合技术中QR分解原理;最后,在两种不同的控制平台下进行了实验验证。结果表明所提出的椭圆拟合技术不受信号处理延迟效应的影响,响应速度快;只需调整遗忘因子一个参数,设置简单,适用于工业领域的广泛应用。

A Modeling Method for Transformer Windings Under VFTO Based on S-parameters

To study the Very Fast Transient Over-voltage (VFTO) distribution in transformer windings in gas insulated substation (GIS), a systematic methodology based on S-parameters is presented for establishing high-frequency model of transformer windings. Firstly, voltage transfer functions are derived from S-parameters which are calculated or measured from transformer windings. Secondly, voltage transfer functions are fitted with rational functions by the vector fitting method and then the rational transfer functions are order-reduced by optimal Pade-approximation algorithm. Lastly, the resultant voltage transfer functions are synthesized by network technology. Computational results are consistent with simulation results of Electromagnetic Transient Program (EMTP) and confirm the feasibility and validity of proposed methodology.

基于GA-BP的圆形靶标圆心定位误差预测建模与补偿研究

利用圆形靶标进行相机标定时,靶标成像效果会随着不同的相机拍摄位姿呈现为椭圆,因此利用常规圆心定位方法得到的图像圆心坐标并非真实圆心在图像中的成像位置,直接利用该圆心图像坐标进行相机标定的标定精度不高。针对此问题,提出了一种先对圆形靶标图像圆心定位误差进行预测建模,然后进行误差补偿来提高圆心定位精度的方法。首先,建立圆形靶标成像图的仿真图像集;其次,对图像预处理并利用椭圆拟合法定位图像中的圆心坐标;再次,构建并训练GA-BP神经网络,建立圆心定位误差与相机镜头位姿之间的关系模型;最后,通过误差补偿策略对定位的圆心坐标进行误差补偿。实验结果表明,所构建的GA-BP神经网络模型对圆心定位的横、纵坐标的误差预测精度明显优于BP或者E-R模型,其MAPE,RMSE,R 2分别为5.51%,0.0048,0.9996和6.14%,0.0964,0.9998。误差补偿后的圆心定位精度更高,验证了采用误差预测建模和误差补偿的方法提高圆心定位精度的可行性,为高精度相机标定任务提供了方法支撑。

基于机器视觉的光纤端面几何参数测量研究

研究了一种基于机器视觉的光纤几何参数测量方法。该方法运用数字图像处理算法,首先,读取光纤端面图片,采用Deriche边缘检测算法进行图像分割;然后,利用去伪边缘算法完成对有效边缘的提取及合并;最后,进行曲线拟合,完成对光纤端面几何参数的测量。实验结果表明:该方法操作简便,算法复杂度低,光纤端面边缘拟合精确度较高,数据检测速度快,可以精确高效地检测出光纤端面几何参数的数据,对涂覆层直径的重复测量精度可达0.021μm,涂覆层圆度重复测量精度可达0.043%。

New separation algorithm for touching grain kernels based on contour segments and ellipse fitting

A new separation algorithm based on contour segments and ellipse fitting is proposed to separate the ellipse-like touching grain kernels in digital images.The image is filtered and converted into a binary image first.Then the contour of touching grain kernels is extracted and divided into contour segments (CS) with the concave points on it.The next step is to merge the contour segments,which is the main contribution of this work.The distance measurement (DM) and deviation error measurement (DEM) are proposed to test whether the contour segments pertain to the same kernel or not.If they pass the measurement and judgment,they are merged as a new segment.Finally with these newly merged contour segments,the ellipses are fitted as the representative ellipses for touching kernels.To verify the proposed algorithm,six different kinds of Korean grains were tested.Experimental results showed that the proposed method is efficient and accurate for the separation of the touching grain kernels.

SSA优化深度双向门控循环单元网络的轴承性能退化趋势预测

为在非经验指导下获取双向门控循环单元网络中最优隐藏层单元数,实现滚动轴承性能退化趋势预测,提出基于麻雀搜索算法优化深度双向门控循环单元的轴承性能退化趋势预测方法。首先,在正向门控循环单元网络基础上,增加反向门控循环单元网络,以构建深度双向门控循环单元预测网络;然后,将预测值与真实值的均方误差作为适应度值,根据麻雀发现者和捕食者进行参数更新,经优化后获得最优隐藏层单元参数下的深度双向门控循环单元网络预测模型;最后,通过全连接层实现性能退化趋势预测。在公共数据集与实测数据集上进行试验验证,验证了所提方法的有效性与可行性。