改进巴氏距离算法下混合级联直流输电纵联阻抗保护优化

为提高纵联保护在LCC-MMC混合级联高压直流输电系统中的鲁棒性,提出一种基于纵联阻抗和改进巴氏距离算法的高压直流输电纵联保护方案。该方案将巴氏距离算法与纵联阻抗保护相结合,对被保护线路首末两端电气量的差异进行量化,并通过量化后的数据,进行区内外故障的判定,然后基于能量函数构建了故障选极判据,保证了保护的可靠性;在此基础上,通过分形维数构建了改进的自适应滑窗,提高了保护的速动性。最后,基于Matlab与PSCAD/EMTDC平台建立了“白江工程”±800 kV LCC-MMC混合级联高压直流输电系统模型,并对所提改进后的保护方案进行验证。仿真结果表明所提保护方案能够快速可靠地判别区内外故障并正确完成故障选极,且有着较好的耐受过渡电阻能力。

基于图像检索技术的受载煤样裂隙演化规律

在煤岩试样破坏过程中进行计算机断层(computed tomography,CT)扫描测试,可实现煤岩试样内部裂隙结构可视化表征,但是在加载过程中,因试样位移变形会引起CT扫描层定位误差,进而影响试验结果准确性。为了解决这一问题,利用图像相似性检索技术,检索出受载试样在不同应力水平下的最相似的CT图像,从而更加准确地描述受载煤样裂隙演化规律。研究结果表明:在三轴压缩破坏过程中,试样应力应变曲线分为5个明显的阶段,即初始压密阶段、线弹性变形阶段、塑性屈服阶段、峰值破坏阶段以及残余变形阶段。基于感知哈希算法的图像检索技术能够准确识别并定位不同应力阶段相似度最高的CT图像,且CT图像相似度随着轴向荷载不断增大而逐渐降低。在整个三轴加载过程中,CT图像的相似度绝对差均值表现出两个明显的变化阶段:缓慢增加阶段和快速增加阶段。分形维数可以定量描述裂隙演化,受载样品破坏过程中分形维数主要经历了缓慢减小、缓慢增大和快速增大3个阶段。

基于改进SFS算法的锚杆钻臂参数整定研究

针对锚杆钻臂井下自动控制过程中存在的环境恶劣、地质复杂等特殊工况,需着重考虑PID的参数选取,为此采用随机分形搜索算法(SFS)对PID参数进行整定。由于随机分形搜索算法存在局部搜索能力不足、易陷入局部最优等问题,在面对机械臂待整定参数多及参数间耦合严重时,其整定效果不佳。因此,引入混沌初始化、正余弦策略、自适应K值选取策略以提高算法的局部搜索能力以及全局搜索速度;采用柯西、差分定向变异策略使算法跳出局部最优。通过标准测试函数测试表明改进后的随机分形搜索算法收敛速度及精度均有一定提高。最后通过锚杆钻臂参数整定仿真实验表明:改进后随机分形搜索算法整定的PID参数总体适应度值提高21%;各关节的量化指标表示改进后随机分形搜索算法跳出了局部最优,提高了整体寻优精度与速度。

并行分布式Fractal图像生成算法的设计

本文以Ｍａｎｄｅｌｂｒｏｔ集图像生成为例提出一种并行Ｆｒａｃｔａｌ图像生成算法，在分布式环境下所实现的算法具有高可靠性、自然负载平衡等特性，实验数据表明所设计的算法具有较高的加速比。

门源M_(S)6.9地震前前兆吸引子的特征提取

以非线性动力系统为理论依据类比地震孕育过程,以非线性动力系统的吸引子理论类比研究地震前兆吸引子,将高台台钻孔倾斜定点形变观测作为孕震系统的状态变量,借助G-P算法从宏观观测数据入手推演前兆动力学特征。在验证了以钻孔倾斜作为状态变量时非线性动力系统前兆吸引子存在的基础上,通过研究以NS、EW分量作为状态变量时吸引子维数的变化特征,归纳总结出门源M_(S)6.9地震前出现异常的NS分量对应的前兆吸引子存在降维特性,即在震前随着时间推移和三维重构相空间数据分布变得集中而有序,相应的地震前兆吸引子的分形维数也更低;而在震前未出现异常的EW分量对应的前兆吸引子的分形维数则保持不变,且其三维重构相空间中点的分布也无明显差异。

基于粒子群算法求解致密砂岩储层孔隙结构分形维数——以鄂尔多斯盆地大宁-吉县地区山西组为例

针对只有孔隙度、渗透率等基础测试数据的井难以求取其分形维数的问题,提出一种基于粒子群算法的致密砂岩储层分形维数求解方法。首先对于拥有高压压汞、核磁资料的井,利用汞饱和度法、核磁共振法计算其分形维数值,并将其设置为训练样本;其次对于只有孔渗数据的井,基于粒子群算法(PSO)思想将目标函数定义为孔、渗数据和训练样本数据的偏差平方和,使用8个岩心样品的孔渗数据进行分形维数计算;最后将计算结果与汞饱和度法和核磁共振法计算结果进行对比分析。结果表明,使用粒子群算法求得的分形维数具有较高精度,该计算过程具有高自动化性、低主观性,该方法可在分形维数参数求解计算中推广应用。

基于数学形态学理论的旋转机械故障诊断方法研究

在数学形态学理论的基础上运用局部特征长度域(LCD)算法和区间估计分形维数对传统诊断方法进行改进,利用LCD算法对信号进行处理,同时利用区间估计对形态谱进行故障分析。实验结果表明,基于LCD算法的故障诊断研究方法可以准确判断不同故障类型,区间估计分形维数方法的故障判断精度为95%,而且不同故障类型的形态谱特征与实际相符合。

The b-value and fractal dimension of local seismicity around Koyna Dam(India)

Earthquakes began to occur in Koyna region （India） soon after the filling of Koyna Dam in 1962. In the present study, three datasets 1964-1993, 1993-1995, and 1996-1997 are analyzed to study the b-value and fractal dimension. The b-value is calculated using the Gutenberg- Richter relationship and fractal dimension Dcorr. using correlation integral method. The estimated b-value and Dcorr. of this region before 1993 are found to be in good agreement with previously reported studies. In the sub- sequent years after 1995, the b-value shows an increase. The estimated b-values of this region are found within the limits of global average. Also, the pattern of spatial clustering of earthquakes show increase in clustering and migration along the three zones called North-East Zone, South-East Zone （SEZ）, and Warna Seismic Zone. The earthquake events having depth ≤5 km are largely confined to SEZ. After 1993, the Dcorr. shows decrease, implying that earth- quake activity gets clustered. This seismic clustering could be helpful for earthquake forecasting.

Random heterogeneous microstructure construction of composites via fractal geometry

The microstructures of a composite determine its macroscopic properties. In this study, microstructures with particles of arbitrary shapes and sizes are constructed by using several developed fractal geometry algorithms implemented in MATLAB. A two-dimensional (2D) quadrilateral fractal geometry algorithm is developed based on the modified Sierpinski carpet algorithm. Square-, rectangle-, circle-, and ellipse-based microstructure constructions are special cases of the 2D quadrilateral fractal geometry algorithm. Moreover, a three-dimensional (3D) random hexahedron geometry algorithm is developed according to the Menger sponge algorithm. Cube-and sphere-based mi-crostructure constructions are special cases of the 3D hexahedron fractal geometry algo-rithm. The polydispersities of fractal shapes and random fractal sub-units demonstrate significant enhancements compared to those obtained by the original algorithms. In ad-dition, the 2D and 3D algorithms mentioned in this article can be combined according to the actual microstructures. The verification results also demonstrate the practicability of these algorithms. The developed algorithms open up new avenues for the constructions of microstructures, which can be embedded into commercial finite element method soft-wares.

An improved fast fractal image compression using spatial texture correlation

This paper utilizes a spatial texture correlation and the intelligent classification algorithm （ICA） search strategy to speed up the encoding process and improve the bit rate for fractal image compression. Texture features is one of the most important properties for the representation of an image. Entropy and maximum entry from co-occurrence matrices are used for representing texture features in an image. For a range block, concerned domain blocks of neighbouring range blocks with similar texture features can be searched. In addition, domain blocks with similar texture features are searched in the ICA search process. Experiments show that in comparison with some typical methods, the proposed algorithm significantly speeds up the encoding process and achieves a higher compression ratio, with a slight diminution in the quality of the reconstructed image; in comparison with a spatial correlation scheme, the proposed scheme spends much less encoding time while the compression ratio and the quality of the reconstructed image are almost the same.

Detecting P2P Botnet by Analyzing Macroscopic Characteristics with Fractal and Information Fusion

Towards the problems of existing detection methods,a novel real-time detection method(DMFIF) based on fractal and information fusion is proposed.It focuses on the intrinsic macroscopic characteristics of network,which reflect not the "unique" abnormalities of P2P botnets but the "common" abnormalities of them.It regards network traffic as the signal,and synthetically considers the macroscopic characteristics of network under different time scales with the fractal theory,including the self-similarity and the local singularity,which don't vary with the topology structures,the protocols and the attack types of P2P botnet.At first detect traffic abnormalities of the above characteristics with the nonparametric CUSUM algorithm,and achieve the final result by fusing the above detection results with the Dempster-Shafer evidence theory.Moreover,the side effect on detecting P2P botnet which web applications generated is considered.The experiments show that DMFIF can detect P2P botnet with a higher degree of precision.

A New Parallel Algorithm for Simulation of Spin-Glass Systems on Scales of Space-Time Periods of an External Field

We study the statistical properties of an ensemble of disordered 1D spatial spin-chains (SSCs) of certain length in the external field. On nodes of spin-chain lattice the recurrent equations and corresponding inequal-ity conditions are obtained for calculation of local minimum of a classical Hamiltonian. Using these equa-tions for simulation of a model of 1D spin-glass an original high-performance parallel algorithm is developed. Distributions of different parameters of unperturbed spin-glass are calculated. It is analytically proved and shown by numerical calculations that the distribution of the spin-spin interaction constant in the Heisenberg nearest-neighboring Hamiltonian model as opposed to the widely used Gauss-Edwards-Anderson distribu-tion satisfies the Lévy alpha-stable distribution law which does not have variance. We have studied critical properties of spin-glass depending on the external field amplitude and have shown that even at weak external fields in the system strong frustrations arise. It is shown that frustrations have a fractal character, they are self-similar and do not disappear at decreasing of calculations area scale. After averaging over the fractal structures the mean values of polarizations of the spin-glass on the scales of external field's space-time peri-ods are obtained. Similarly, Edwards-Anderson’s ordering parameter depending on the external field ampli-tude is calculated. It is shown that the mean values of polarizations and the ordering parameter depending on the external field demonstrate phase transitions of first-order.

Distinction of self-synchronous scrambled linear blockcodes based on multi-fractal spectrum

This study proposes a novel multi-fractal spectrumbasedapproach to distinguish linear block codes from its selfsynchronousscrambled codes. Given that the linear block codeand self-synchronous scrambled linear block code share the propertyof linear correlation, the existing linear correlation-basedidentification method is invalid for this case. This drawback can becircumvented by introducing a novel multi-fractal spectrum-basedmethod. Simulation results show that the new method has highrobustness and under the same conditions of bit error, the lowerthe code rate, the higher the recognition rate. Thus, the methodhas significant potential for future application in engineering.

Restoration of Noisy 1/f Family Fractal Signal Based on Haar Wavelets and Wiener Filter

In order to restore noisy fractal Brownian motion(FBM),discrete fractional gaussiannoise(DFGN) combined with noise increments is decomposed by Haar wavelets based on Mallatalgorithm.Considering the correlation of detail coefficients,a bank of Wiener filters are used to estimatethe detail coefficients to reconstruct DFGN considering the estimated approximation coefficients in thecoarsest scale in the minimum mean square sense.Then,the reconstructed DFGN is used to restore FBM.In the digital simulation,in light of the restoration mean square error,we show that the suppose that thecorrelation of detail coefficients and the approximation coefficients in the coarsest scale for any Hurstcould be avoided is unrealistic.Moreover,we calculate the estimation root mean square error of the hurstparameter of the restored FBM to show the validity of our algorithm.

改进蝴蝶算法的神经网络天线建模

为提高天线建模效率,改变传统建模方法速度慢、效率低的问题,提出了一种用改进的蝴蝶算法(BOA)优化多层前馈神经网络(back propagation neural network,BPNN)的天线建模方法。首先,以多层前馈神经网络为基础网络,建立蝴蝶算法优化的BP神经网络,解决BP神经网络预测精度低的问题。其次,在蝴蝶算法中融入天牛须算法(BAS),用天牛须算法替代蝴蝶算法的局部寻优过程,减小蝴蝶算法的空间复杂度、解决蝴蝶算法易陷入局部最小值的问题,创建改进的BOA-BP神经网络对天线进行精准建模。设计实例表明,该网络的预测精度达到了99.60%,相比于传统的BPNN和未改进蝴蝶算法优化的BPNN,预测S11的误差分别减少了47%和40.9%。此外,改进的BOA算法的运行时间相对于粒子群算法和遗传算法也分别减小了80.86%和82.79%,大大降低了网络运行的时间成本。综上,改进的BOA优化后的BPNN的建模精度和速度均得到了提高,验证了改进的蝴蝶算法作为一种新型神经网络优化策略的可行性和有效性。

基于Borges差分的RMSprop算法及在卷积神经网络参数训练中的应用

针对RMSprop算法存在梯度消失和局部最优的问题,本文提出了一种基于Borges差分的RMSprop算法并应用到卷积神经网络参数训练方法.根据Borges分形导数的定义,本文给出了Borges差分的定义;将Borges差分与RMSprop算法相结合,提出了基于Borges差分的RMSprop优化算法,提高了图像识别的精度和学习收敛速度;给出了一种基于梯度信息的自适应的调整阶次的方法.本文以Fashion-MNIST数据集为例,分析了阶次对网络参数训练结果的影响,验证了本文提出的算法提高卷积神经网络的识别精度和学习收敛速度的有效性.

无人机蜂群轨迹预测研究

传统防空火控算法中的轨迹预测模型无法对复杂的无人机蜂群进行有效轨迹预测,而现有针对无人机机动轨迹的预测研究通常只考虑单个无人机,模型量级过大。为了准确且快速地预测无人机蜂群轨迹,提出一种面向蜂群的轨迹预测方法。在获得蜂群轨迹后,首先采用具有噪声的基于密度的聚类(DBSCAN)方法对其进行聚类,判断出蜂群中各个无人机的类别;然后基于分形算法,判断无人机轨迹是简单轨迹还是复杂轨迹;最后采用卡尔曼滤波进行简单轨迹预测,基于长短期记忆(LSTM)网络方法进行复杂轨迹的预测。结果表明:本文提出的无人机蜂群轨迹预测方法的预测误差远小于仅采用卡尔曼滤波方法的预测误差,且预测时间小于仅采用LSTM网络方法预测的时间,可以较为准确地预测蜂群中不同集群无人机的轨迹,能够为反无人机蜂群火控解算提供参考。

基于分形理论的产品形态参数化设计研究

研究分形理论及算法在产品形态创新设计中的应用,为产品形态创新设计提供理论指导和更多思路。文章结合分形理论及分形算法,提出分形理论及算法在产品形态上的创新研究,通过构建的分形理论的产品形态参数化设计模型,实现产品形态的族群化,同时结合感性优选方法,创造了理性与感性相结合的产品形态设计方式。得到家居桌的设计实践。运用分形理论、软件实证与优选验证了创新设计方法的可操作性和可实现性。丰富了产品形态创新设计的理论体系。

基于压缩感知和分形图的视觉有意义的图像加密算法

基于压缩感知和分形图,提出一种视觉有意义的图像加密算法,从视觉安全和数据安全两方面为图像提供保护.明文图像哈希值与外部密钥共同生成混沌系统初始值,能有效提高算法抵御已知明文和选择明文攻击的能力.使用分数阶混沌系统与克罗内克积生成压缩感知所需的测量矩阵,增强安全性的同时能大幅缩短所需混沌序列的长度、提高算法的加解密效率.使用离散忆阻混沌系统控制分形图的生成、图像的置乱及按位异或操作,对压缩感知测量结果进行二次加密,在解决测量结果像素值分布不均问题的同时提高算法的安全性.实验结果表明:该文算法具有良好的视觉安全性,能有效抵抗穷举攻击、差分攻击、统计攻击等常见攻击;相对于其他文献算法,该文算法的保真度更高.

利用元胞自动机算法的建筑形态生成设计

随着建筑学的发展和创新,建筑设计不再拘泥于传统的简单欧式几何,不规则、非线性的建筑形态也逐渐进入了大众的视野,用于表达某些建筑意向,增添建筑趣味,并拓展建筑多样性。分形迭代便是生成非线性形态的重要方法,元胞自动机作为一种重要的分形迭代算法,在城市设计中已经有较为广泛的运用,但在建筑设计中应用较少。研究通过构建参数化的迭代模型,引入城市空间、交通等因素作为目标控制和约束条件,按照一定的体块规则进行不断迭代,生成复杂多样的体量形态,改变迭代规则和迭代次数,可以对生形结果进行探究和优化,最终经过建筑化的处理,得到具体的建筑体量。运用元胞自动机进行建筑生形,是一种对非线性建筑形态设计的新的探索。