共查询到20条相似文献，搜索用时 250 毫秒
1.
蒋惠凤 《温州职业技术学院学报》2014,(1):57-60
为提高负荷预测精度,将主成分回归（PCR）、偏最小二来回归（PLSR）与反向传播神经网络（BPNN）相结合,分别建立基于PCR和PLSR及与神经网络耦合的年用电量预测模型.结果表明,以PCR和PLSR方法提取成分作为神经网络的输入,以实际用电量作为输出,建立的PC-BPNN和LV-BPNN非线性预测模型拟合优度优于PCR和PLSR线性预测模型.从检验四个预测模型的预测效果看,线性预测模型的预测值均高于实际值,非线性预测模型的预测值均低于实际值. 相似文献
2.
《武汉工程职业技术学院学报》2019,(4)
为了更好地识别人手动作的肌电信号,采用基于小波包分解与主成分分析结合的特征提取方法,并利用粒子群优化Elman神经网络的模式分类方法。选择"db"系小波对肌电信号进行多尺度分解,并结合主成分分析法,选用累计贡献率大于98.6%的十个主成分作为特征向量,输入优化神经网络进行网络训练,实现对人手抓取动作的模式识别。实验结果表明,与传统神经网络仿真结果对比,采用粒子群算法优化Elman神经网络不仅能提高系统稳定性问题,而且能提高人手动作分类识别率,验证了该方法是一种可行的人手动作分类识别方法。 相似文献
3.
在波长范围380-600nm测定了藏红、荧光桃红、曙红三种色素混合物溶液的吸光度数据,用小波变换对光谱数据进行处理,然后将小波变换系数用偏最小二乘(PLS)法进行回归分析。用Daubechies4小波对原始吸光度数据进行一次分解,以低频系数作校正集并用交叉验证法选择主成分数进行PLS建模,获得了令人满意的预测结果。 相似文献
4.
为了将低分辨率多光谱图像和高分辨率全色图像有效地融合,提出了主成分分析(PCA)变换和提升小波相结合的融合方法。小波提升后选用不同的融合规则对高低频成分进行融合,并与PCA+DWT和HSV+LWT融合法进行了比较,实验结果表明,该方法较好地保留了多光谱图像的光谱特性,提高了空间分辨率。 相似文献
5.
大学生成绩的综合评价及分析 总被引：2，自引：0，他引：2
本文运用主成分分析对大学生四年的学习成绩进行综合评价,并对主成分得分进行单因素方差分析,以期更好地对大学生的学习成绩进行综合评价。 相似文献
6.
基于DiagPCA（对角主成分分析）及平均脸的方法对二维主成分分析（2DPCA）方法进行了改进,既考虑到构造2DPCA训练样本人脸间散布矩阵时使特征最大化,减少了同类人脸之间的特征差异,又利用图像矩阵对角化将图像的行、列关系联系起来,并利用ORL人脸数据库进行实验。结果显示,该方法可提高人脸识别率,且降低了特征提取的时间。 相似文献
7.
刘悦婷 《咸阳师范学院学报》2015,(2):49-52
为提高人脸识别率,提出一种小波树和主元分析的人脸识别算法。该算法先利用小波变换公式,在人脸图像上计算出一个小波近似分量,并对该近似分量进行二次小波分解,相应地计算出各小波近似分量;其后对三层分解的小波近似系数进行重新组合,得到新样本集;最后在此样本集上使用主元分析进行人脸识别。ORL和CAS-PEAL-R1人脸库的MATLAB程序仿真实验结果表明,与基于图像矩阵的二维主元分析(2D-PCA)相比较,新方法的人脸识别率为95%,对光照条件、脸部表情变化有良好的鲁棒性。 相似文献
8.
引入职业生命周期理论,采用问卷调查的方法,运用SPSS统计软件进行主成分分析（PrincipalCorn—ponentAnalysis简称PCA）,对职业生命周期不同阶段的知识员工的激励影响因子进行排序。结果表明,主成分分析方法具有一定的应用价值,能为企业制定激励措施提供一定参考。 相似文献
9.
采用同时蒸馏萃取方法对松乳菇挥发性成分进行提取,并用气相色谱—质谱法对提取物进行化学成分分析.从同时蒸馏萃取提取物中鉴定出了67个成分,并以归一化法测定了各个成分的质量分数.其中超过2%的有9种：1-辛烯-3-醇（2.27%）,丁酸丁酯（13.52%）,（E）-2-辛烯醛（2.88%）,n-癸酸（4.99%）,[1 aR-（1 a..α,4..β,4 a..β,7..β,7 a..β,7b..α）]-十氢-1,1,4,7-四甲基-1H-环丙烯并[e]薁（4.16%）,n-十六烷酸（4.75%）,（Z）-9,17-十八碳二烯醛（5.19%）,（E）-9-十八碳烯酸（3.33%）,十八烷酸（2.13%）. 相似文献
10.
针对传统信用评价方法分类精度较低、数据集属性变量间存在相关性等问题,提出基于主成分分析的稀疏贝叶斯学习（PCA-SBL）算法。首先对数据集特征变量进行主成分分析,使降维后的变量无相关性|其次,对主成分分析后的数据进行稀疏贝叶斯分类|最后将 PCA-SBL 分类方法分类精度与传统分类方法精度进行比较。分析发现,在 German Credit Data 和 Australian Credit Data 上,与传统 KNN、朴素贝叶斯、SVM、随机森林、决策树相比,改进的 SBL 算法分类精度平均提高了 5.26%、4.65%、2.11%、2.125%、4.66%,与稀疏贝叶斯学习算法（SBL）相比,平均提高 0.965%,从而证明 PCA-SBL 算法具有更高的分类效果。 相似文献
11.
ＩＮＴＲＯＤＵＣＴＩＯＮＳｐｅｃｔｒｏｓｃｏｐｉｃｍｅｔｈｏｄｓａｒｅｉｎｃｒｅａｓｉｎｇｌｙｂｅｉｎｇｅｍｐｌｏｙｅｄｆｏｒｑｕａｎｔｉｔａｔｉｖｅａｐｐｌｉｃａｔｉｏｎｉｎｃｈｅｍ ｉｓｔｒｙ,ｂｉｏｌｏｇｙａｎｄｍｅｄｉｃｉｎｅ .Ｗｈｉｌｅａｄｖａｎｃｅｓｉｎｉｎｓｔｒｕｍｅｎｔａｔｉｏｎｂｒｉｎｇｉｎｃｒｅａｓｅｄｒｅｓｏｌｕｔｉｏｎａｎｄｓｅｎｓｉｔｉｖｉｔｙ ,ｔｈｅｍｕｌｔｉｖａｒｉａｔｅｃａｌｉｂｒａｔｉｏｎｍｏｄｅｌｓａｓｓｔａｔｉｓｔｉｃａｌｔｏｏｌｓｈａｖｅａｌｓｏｂｅｅｎｓｈ… 相似文献
12.
This paper proposes a new algorithm for multivariate calibration named Principal Component Regression Based on Wavelet (PCRW)
which combines wavelet decomposition technique with the factor analysis method for establishing a duplicate denoising mechanism.
A practical example in spectral analysis of a typical multicomponent pharmaceutical system was used to verify the effectiveness
of the algorithm. It was shown that PCRW produced fewer prediction errors than those obtained by using PCR.
Project (39870940) supported by NSFC. 相似文献
13.
INTRODUCTION Consumers’ acceptance of fresh or processedapples is the ultimate goal of apple breeders, foodscientists and supermarket managers. Internal qualityassessment has focused on two major objectives:removal of fruit with internal defects and taste selec-tion. Three major parameters including sugar content,acidity and firmness have to be taken into account todetermine the internal quality and the taste of an apple.Near infrared spectroscopy has been used to measureseveral properti… 相似文献
14.
To develop nondestructive acidity prediction for intact Fuji apples, the potential of Fourier transform near infrared (FT-NIR) method with fiber optics in interactance mode was investigated. Interactance in the 800 nm to 2619 nm region was measured for intact apples, harvested from early to late maturity stages. Spectral data were analyzed by two multivariate calibration techniques including partial least squares (PLS) and principal component regression (PCR) methods. A total of 120 Fuji apples were tested and 80 of them were used to form a calibration data set. The influences of different data preprocessing and spectra treatments were also quantified. Calibration models based on smoothing spectra were slightly worse than that based on derivative spectra, and the best result was obtained when the segment length was 5 nm and the gap size was 10 points. Depending on data preprocessing and PLS method, the best prediction model yielded correlation coefficient of determination (r^2) of 0.759,low root mean square error of prediction (RMSEP) of 0.0677, low root mean square error of calibration (RMSEC) of 0.0562. The results indicated the feasibility of FT-NIR spectral analysis for predicting apple valid acidity in a nondestructive way. 相似文献
15.
A new motion-compensated 3-D wavelet transform (MC-3DWT) video coding scheme is presented in thispaper. The new coding scheme has a good performance in average PSNR, compression ratio and visual quality of re-constructions compared with the existing 3-D wavelet transform (3DWT) coding methods and motion-compensated2-D wavelet transform (MC-WT) coding method. The new MC-3DWT coding scheme is suitable for very low bit-rate video coding. 相似文献
16.
HOU Wei dong MO Yu long 《上海大学学报(英文版)》1999,(4)
１ Ｉｎｔｒｏｄｕｃｔｉｏｎ Ｔｈｅｐｕｂｌｉｃｓｗｉｔｃｈｅｄｔｅｌｅｐｈｏｎｅｎｅｔｗｏｒｋ（ＰＳＴＮ）ａｎｄｉｔｓｂｒｏａｄｃｏｖｅｒａｇｅｐｒｏｍｏｔｅｔｈｅｄｅｖｅｌｏｐｍｅｎｔｏｆｖａｒｉｏｕｓｖｉｓｕａｌｃｏｍｍｕｎｉｃａｔｉｏｎｓｓｅｒｖｉｃｅｓｏｖｅｒＰＳＴＮ［１］．ＴｈｅａｌｌｏｗｅｄｂｉｔｒａｔｅｏｖｅｒＰＳＴＮｗｉｔｈｖｏｉｃｅｂａｎｄｍｏｄｅｍｉｓｓｔｉｌｌｌｉｍｉｔｅｄｔｏｌｏｗｅｒｔｈａｎ６４ｋｂｉｔ／ｓ,ｗｈｉｃｈｐｒｅｓｅｎｔｓａｇｒｅａｔｃｈａｌｌｅｎｇｅ… 相似文献
17.
A new motion-compensated 3-D wavelet transform (MC-3DWT) video coding scheme is presented in this paper. The new coding scheme
has a good performance in average PSNR, compression ratio and visual quality of reconstructions compared with the existing
3-D wavelet transform (3DWT) coding methods and motion-compensated 2-D wavelet transform (MC-WT) coding method. The new MC-3DWT
coding scheme is suitable for very low bit-rate video coding.
Project supported by the National Natural Science Foundation of China(69875009) 相似文献
18.
功能核磁共振和弥散张量这2种成像方式能够反应人类大脑不同方面的信息,采用小波变换的方法来对这2种医学图像进行融合可以有效改善抑郁症的识别准确率.首先,利用多尺度小波分解方法把每种类型的图像都转换到频域,以得到各频率的成分参数.其次,对于每个被试,将2种图像的分解参数根据频率各自相加,并且通过小波逆变换重建出融合图像.然后,使用主成分分析方法对融合的数据进行降维并得到图像特征.基于融合后图像的特征,采用留一检验方法最终得到了80.95%的抑郁症识别率.可以看出,该小波融合方法能够对当前抑郁症的诊断识别进行有效的改进. 相似文献
19.
为了提高脱机手写藏文字符的识别效果,提出了一种在小波变换基础上计算局部梯度方向直方图的特征提取方法.首先,对一个脱机手写藏文字符样本图像进行一次Haar小波变换,得到相应的一级近似分量;然后,将这个一级近似分量划分成几个等尺寸的子区域;最后,计算每个等尺寸子区域的局部梯度方向直方图,并将所有子区域的全部局部梯度方向直方图的值作为该字符图片的特征.在最近建立的脱机手写藏文字符样本数据库(THCDB)上的实验结果表明:提出的特征提取方法识别效率较高,且识别效果较好;和细节分量相比,近似分量对提高识别精度具有更大的贡献. 相似文献
20.
YU Bin TIAN Feng-chun HE Qing-hu RAN Jian LV Bo HONG Xin LIU Tao BI Yu-tian 《重庆大学学报(英文版)》2016,15(4):127-138
In this paper, a wavelet packet feature selection method for lung sounds based on optimization is proposed to obtain the best feature set which maximizes the differences between normal lung sounds and abnormal lung sounds (sounds with wheezes or rales). The proposed method includes two main steps: Firstly, the wavelet packet transform (WPT) is used to extract the original features of lung sounds; then the genetic algorithm (GA) is used to select the best feature set. The obtained optimal feature set is sent to four different classifiers to evaluate the performance of the proposed method. Experimental results show that the feature set obtained by the proposed method provides a higher classification accuracy of 94.6% in comparison with the best wavelet packet basis approach and multi-scale principal component analysis (PCA) approach. Meanwhile, the proposed method has effective generalization performance and can obtain the best feature set without priori knowledge of lung sounds. 相似文献