Description: 提出了一个新的超声缺陷自动识别系统。该系统采用小波包分解提取超声信号的特征,采用混沌遗传算法来消除冗余和不相关的特征,并采用支持向量机(SVM) 来对缺陷进行识别。-Proposed a new ultrasonic flaw Automatic Identification System. The system uses wavelet packet decomposition extract the characteristics of ultrasonic signals using chaos genetic algorithm to eliminate redundant and irrelevant features, and using support vector machine (SVM) to identify defects. Platform: |
Size: 195584 |
Author:zhaoxiufen |
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Description: 人工神经网络算法研究及应用 田景文.包括神经网络、遗传算法、小波网络、模拟退火算法和支持向量机,清晰易懂,非常值得一看。-Artificial Neural Network Algorithm Research and Application田景文. Including neural networks, genetic algorithms, wavelet networks, simulated annealing algorithm and support vector machine, clear and easy to understand, is a must see. Platform: |
Size: 8607744 |
Author:yt |
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Description: 两本神经网络方面的经典电子书
人工神经网络导论.pdf
人工神经网络实用教程.pdf
神经网络是智能控制技术的主要分支之一。本书的主要内容有:神经网络的概念,神经网络的分类与学习方法,前向神经网络模型及其算法,改进的BP网络及其控制、辨识建模,基于遗传算法的神经网络,基于模糊理论的神经网络,RBF网络及其在混沌背景下对微弱信号的测量与控制,反馈网络,Hopfield网络及其在字符识别中的应用,支持向量机及其故障诊断,小波神经网络及其在控制与辨识中的应用。-Two neural networks classic book Introduction to Artificial Neural Networks. Pdf Practical Guide artificial neural network. Pdf neural network is the intelligent control technology, one of the main branch. The main contents of this book are: the concept of neural networks, neural network classification and learning methods, the former to the neural network model and its algorithm, the improved BP network and its control, recognition modeling, based on genetic algorithm neural network, based on fuzzy the theory of neural network, RBF network and its application in the context of chaotic signals of weak measurement and control, feedback network, Hopfield Network and Its Application in character recognition, support vector machine and its fault diagnosis, wavelet neural network and its application in control and identification applications. Platform: |
Size: 7793664 |
Author:梁健 |
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Description: 线性预测算法基于遗传算法-支持向量机的水库叶绿素a浓度短期预测非线性时序模型,利学水 报 2009 年 1 月 SHUILI XUEBAO 第第 40 卷 1 期文章编号 :055929350 2009 0120046206 基于遗传算法 -matlab Linear prediction algorithm is based on genetic algorithm- support vector machine reservoir chlorophyll-a concentration of short-term prediction of nonlinear time series model, Lee study of water reported in January 2009 SHUILI XUEBAO No. 40 Volume 1 Article ID: 055929350 20090120046206 based on genetic algorithm Platform: |
Size: 3072 |
Author:微软 |
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Description: 模型利用协商历史中隐含的信息自动对数据进行标注以形成训练样本,用最小二乘支持向量回
归机学习此样本得到对手效用函数的估计,然后结合自己和对手的效用函数构成一个约束优化问题,用遗传算法求
解此优化问题,得到的最优解就是己方的反建议.实验结果表明,在信息保密和没有先验知识的条件下,此模型仍然
表现出较高的效率和效用-The proposed model labels the negotiation history data automatically by making full use of the implicit
information in negotiation history.Then,the labeled data become the training samples of least-squares support
vector machine that outputs the estimation of opponent’s utility function.After that,the self s utility function and
the estimation of opponent’s utility function constitute a constraint optimization problem that will be further figured
out by genetic algorithm.The optimal solution is the counter-ofer of onesel~ Experimental results show that the
proposed model is efective and efi cient in environments where information is private and the prior knowledge is
not available. Platform: |
Size: 514048 |
Author:11 |
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Description: 提出一种基于支持向量机( SVM)和遗传算法(GA)的离散余弦变换(DCT)域盲数字图像水印方法. 该方法能自适应于图像的局部特征. 依据图像块的局部特性,利用SVM对图像块分类,自适应地确定水印嵌入强度, GA用来优化水印嵌入位置. 实验结果表明该方法有较好的不可见性和较强对抗攻击的鲁棒性.-Based on support vector machine (SVM) and genetic algorithm (GA), discrete cosine transform (DCT) domain blind digital image watermarking method. The method adaptive to local image features. Based on the local characteristics of image block using the SVM the image block classification, adaptive to determine the embedding strength, GA to optimize the watermark embedding location. The experimental results show that the method has good invisibility and robustness of the strong against the attacks. Platform: |
Size: 449536 |
Author:郭事业 |
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Description: 遗传算法+支持向量机,非常的实用,希望对大家有用。-Genetic algorithms+ support vector machine, very useful, we want to be useful. Platform: |
Size: 1673216 |
Author:慧莹 |
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Description: SVM方法的基本思想是:定义最优线性超平面,并把寻找最优线性超平面的算法归结为求解一个凸规划问题。进而基于Mercer核展开定理,通过非线性映射φ,把样本空间映射到一个高维乃至于无穷维的特征空间(Hilbert空间),使在特征空间中可以应用线性学习机的方法解决样本空间中的高度非线性分类和回归等问题。svm 程序,即支持向量机的代码。-The basic idea of SVM method are: the definition of the optimal linear hyperplane, and the search algorithm for optimal linear hyperplane by solving a convex programming problem. Then based on Mercer nuclear expansion theorem, through a nonlinear mapping φ, the sample space is mapped to a high-dimensional and even infinite dimensional feature space (Hilbert space), so that in the feature space can be applied to solve the linear learning machine method, the sample space The highly nonlinear classification and regression problems. svm procedures that support vector machine code. Platform: |
Size: 117760 |
Author:秀 |
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Description: 遗传算法和支持向量机的故障诊断方法Based on genetic algorithm and support vector machine method of fault diagnosis-Based on genetic algorithm and support vector machine method of fault diagnosis Platform: |
Size: 315392 |
Author:zine2008 |
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Description: 用遗传算法( Genetic Algorithm,GA) 搜寻可识别被不同农药污染脐橙的可见/近红外光谱的最佳特征光
谱区间及波长,并建立了支持向量机( Support Vector Machines,SVM) 定性分析模型。实验供试农药为灭多威、
氰戊菊酯和氧乐果3 种。通过GA 来搜寻整个波段范围( 460 ~ 1 800 nm) ,将得到的9 个最佳特征光谱区间所
包含的波长( 共318 个) 作为SVM 建模的输入变量,对识别被3 种农药污染脐橙的准确率为100 。并继续应
用GA 优化,得到71 个特征波长,此时建立的SVM 模型的识别准确率为99. 57 。虽然识别的准确率有所下降,但是模型的复杂程度得到了很大的优化,其输入变量减少到71 个。实验结果表明利用可见/近红外光谱技
术结合SVM 方法可以有效识别被不同农药污染的脐橙。-Genetic algorithm ( GA) was used to search for the best characteristic spectral ranges andwavelengths of visible /near - infrared spectra ( Vis /NIRs) ,a qualitative analysis model of support vector machine
( SVM) was set up to recognize navel oranges contaminated with different pesticides. The pesticides in
the experiment were Methomyl,fenvalerate and omethoate. Using GA to search the entire band range ( 460 ~1 800 nm) ,the 9 best characteristic spectral ranges ( 318 wavelengths) were used as the input variables of SVM model and the accuracy of the prediction set classification was 100 . Then GA method was used continually
and 71 wavelengths were extracted,the corresponding SVM model was built with 99. 57 accuracy. Although
the classification accuracy rate declined,the complexity of the model was greatly optimized by reducing
the input variables to 71. The experiment results showed that the application of Vis /NIRs combined with SVM can effectively detect the navel oranges conta Platform: |
Size: 220160 |
Author:ygliang30 |
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Description: 采用遗传算法优化最小二乘支持向量机参数的方法-Using genetic algorithms to optimize the parameters of least squares support vector machine approach Platform: |
Size: 230400 |
Author:刘梦 |
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Description: 遗传算法用于神经网络BP和支持向量机SVM参数的优化-GA was used to optimize BP and SVM( support vector machine) parameters. Platform: |
Size: 235520 |
Author:qiulijuan |
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Description: 遗传算法优化支持向量机的惩罚系数C与高斯核系数g,能够提高支持向量机的分类精度-Genetic algorithm to optimize the punish coefficient of support vector machine (SVM) with gaussian kernel coefficient C g, can improve the support vector machine (SVM) classification accuracy Platform: |
Size: 2048 |
Author:T和 |
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