共查询到20条相似文献,搜索用时 156 毫秒
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遗传算法作为一种随机化优化搜索方法,已经在很多领域得到了成功应用,但其存在控制参数多且配置困难的问题.本文采用一类最新试验设计方法-计算机试验设计,对遗传算法的参数配置进行优化.结果表明,基于正交拉丁超立方设计的参数配置,其算法的计算精度和速度表现最佳.模拟结果进一步讨论了不同试验设计方案在遗传算法中的差别. 相似文献
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鉴于图像增强技术在生活应用中的重要性,模糊技术在图像应用中的实用性和广泛性,提出了一种基于三角隶属函数和模糊熵的新的图像增强算法(T-FE增强算法),使用三角函数作为隶属函数,重构参数型对比增强算子,运用模糊熵最大原则选取阈值,计算快速,简单.并且将T-FE算法运用于图像分割,边缘检测.通过实验仿真表明,T-FE算法在进行图像处理时有较好效果. 相似文献
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神经网络和遗传算法是软计算领域中最重要的方法.采用MATLAB的神经网络工具箱和遗传算法工具,研究二者的结合使用,对两个工具箱的基本应用以及将二者结合的相关技术都作了介绍,并应用实例进行了分析研究,提出了使用遗传算法优化神经网络参数的不同结论,对于如何有效使用遗传算法优化神经网络具有一定的借鉴作用. 相似文献
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针对单纯使用遗传算法处理大规模数据需要时间长和对计算机的内存等硬件要求较高的问题,将神经网络嵌入到遗传算法中构造出混合智能遗传算法用于SVM核函数的参数优化,数值试验结果表明该算法对SVM核参数优化是可行的、有效的,并能得到较好的SVM核参数组合和具有较高的分类准确率及较好的泛化能力. 相似文献
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遗传算法是解决多机调度组合优化问题最有效的方法之一,但由于其自身存在着一定的缺陷应用受到一定的限制.针对遗传算法的“早熟”和非均匀地在优化空间中搜索等缺陷,提出了一种自适应选择交叉概率、变异概率以及交叉位置非等概率选取的改进的遗传算法,并将其用于某钢管钢绳企业的多机调度问题,进行了仿真分析. 相似文献
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针对简单遗传算法易陷入局部最优及收敛速度慢的不足,提出一种改进遗传算法-基于启发式策略的搜寻者遗传算法.首先将搜寻者优化算法中的模糊思想和近邻策略相结合改进变异算子,增强种群多样性,避免陷入局部最优;然后针对路径优化问题基于启发式策略设计反转算子,使得路径中不存在交叉边,加快收敛速度;最后将改进遗传算法用于求解旅行商问题.结果表明,改进遗传算法的求解精度和求解效率明显优于基本遗传算法. 相似文献
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《数学的实践与认识》2013,(18)
遗传算法是一种基于生物选择与遗传机理的随机搜索与优化的方法,近年来解决了许多不同领域不同类型的优化难题.采用此方法就生物质发电过程中集料处理作业系统优化问题进行了研究.文中以获取最小生物质发电集料处理系统成本为目标,利用遗传算法对集料处理系统工序进行了优化设计,通过输入实际案例数据,得到的输出结果与试验结果一致,证明了设计的有效性.同时,通过测试不同参数取值对输出结果的影响,得到了最佳参数值.研究对于企业优化生产工艺、降低生产成本,对于政府审核生物质发电项目具有重大意义. 相似文献
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二维恒定各向同性介质渗透系数反演的遗传算法 总被引:1,自引:0,他引:1
给出了利用遗传算法求解二维恒定各项同性介质渗透系数反演的一种新方法,该方法把参数反演问题转化为优化问题通过遗传算法求解.数值模拟结果表明:该方法具有精度高、收敛速度快、编程简单、易于计算机实现等优点,值得在实际工作采用. 相似文献
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Multi-resolution and region-growing strategies have been successfully used in several fields of image processing. In this paper we investigate how these two strategies can be applied for binary tomography. We included these strategies into a reconstruction method using simulated annealing and tested these new methods on different images. 相似文献
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基于内容的检索是多媒体信息处理中的一个重要问题,图像、视频作为多媒体中最直观、最形象的内容,对它们的检索和查询是多媒体内容处理的一个重要方面。以往对图像检索往往借助于图像理解等领域发展起来的模式识别技术,但检索在很多方面又不同于模式识别,它通常并不需要精确匹配,而且由于检索中人一机交互性起着很重要的作用,使得在检索中有必要利用模糊的方法来提出查询要求,计算机也可以通过模糊相似性匹配来给出结果。本文提出了以信任度、可能性测度、权重有隶属函数概念作为模糊相似性匹配的基础来检索图像的方法。 相似文献
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Annamária R. Várkonyi-Kóczy 《Memetic Computing》2010,2(4):283-304
Enhancement of noisy image data is a very challenging issue in many research and application areas. In the last few years, non-linear filters, feature extraction, high dynamic range imaging methods based on soft computing models have been shown to be very effective in removing noise without destroying the useful information contained in the image data. In this paper new image processing techniques are introduced in the above mentioned fields, thus contributing to the variety of advantageous possibilities to be applied. The main intentions of the presented algorithms are (1) to improve the quality of the image from the point of view of the aim of the processing, (2) to support the performance, and parallel with it (3) to decrease the complexity of further processing using the results of the image processing phase. 相似文献
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A new contrast enhancement algorithm for image is proposed combining genetic algorithm (GA) with wavelet neural network (WNN).
In-complete Beta transform (IBT) is used to obtain non-linear gray transform curve so as to enhance global contrast for an
image. GA determines optimal gray transform parameters. In order to avoid the expensive time for traditional contrast enhancement
algorithms, which search optimal gray transform parameters in the whole parameters space, based on gray distribution of an
image, a classification criterion is proposed. Contrast type for original image is determined by the new criterion. Parameters
space is, respectively, determined according to different contrast types, which greatly shrink parameters space. Thus searching
direction of GA is guided by the new parameter space. Considering the drawback of traditional histogram equalization that
it reduces the information and enlarges noise and background blur in the processed image, a synthetic objective function is
used as fitness function of GA combining peak signal-noise-ratio (PSNR) and information entropy. In order to calculate IBT
in the whole image, WNN is used to approximate the IBT. In order to enhance the local contrast for image, discrete stationary
wavelet transform (DSWT) is used to enhance detail in an image. Having implemented DSWT to an image, detail is enhanced by
a non-linear operator in three high frequency sub-bands. The coefficients in the low frequency sub-bands are set as zero.
Final enhanced image is obtained by adding the global enhanced image with the local enhanced image. Experimental results show
that the new algorithm is able to well enhance the global and local contrast for image while keeping the noise and background
blur from being greatly enlarged. 相似文献
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Wavelet analysis is a universal and promising tool with very rich mathematical content and great potential for applications in various scientific fields, in particular, in signal (image) processing and the theory of differential equations. On the other hand distributions are widely used in these fields. And to apply wavelet analysis in these areas it is important to define and investigate wavelet transforms of distributions. In this paper we introduce continuous wavelet transforms of distributions and study convergence properties of these transforms. 相似文献
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采样数据的增加究竟有多少相应的有效Fisher信息增益,这是测量数据处理、图像数据融合等应用领域中关心的问题.以(共轭)正态分布为基础,利用统计推断理论,导出一定相关性下样本数据的增加与统计信息(Fisher信息)增益之间的关系,并经一维航天测量数据和二维图像超分辨仿真算例验证. 相似文献
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Prediction of significant wave height (SWH) field is carried out in the Bay of Bengal (BOB) using a combination of empirical orthogonal function (EOF) analysis and genetic algorithm (GA). EOF analysis is performed on 4 years (2005–2008) of numerical wave model generated SWH field, and analyzed fields of zonal (U) and meridional (V) winds. This is to decompose the space-time distributed data into spatial modes ranked by their temporal variances. Two different variants of GA are tested. In the first one, univariate GA is applied to the time series of the first principal component (PC) of SWH in the training dataset after a filtering with singular spectrum analysis (SSA) for effecting noise reduction. The generated equations are used to carry out forecast of SWH field with various lead times. In the second method, multivariate GA is applied to the SSA filtered time series of the first PC of SWH, and time- lagged first PCs of U and V and again forecast equations are generated. Once again the forecast of SWH is carried out with same lead times. The quality of forecast is evaluated in terms of root mean square error of forecast. The results are also compared with buoy data at a location. It is concluded that the method can serve as a cost-effective alternate prediction technique in the BOB. 相似文献