共查询到19条相似文献,搜索用时 78 毫秒
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本文较详细的介绍了玉米脱胚前的预处理设备-水汽调节机的机械结构、工作原理、工艺性能、试验数据、安装调试和操作使用方法,指出该设备是提高玉米剥皮率和脱坯率的一种理想预处理设备。 相似文献
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为探索大数据技术在烟草商业系统中的应用,提出了一种适用于营销、专卖等部门的大数据分析方法。该方法通过数据采集、数据导入、预处理、关联分析等手段,可实现对专卖、营销等业务中结构化/非结构化数据的有效挖掘,缓解了人工数据分析面临的耗时、费力,难以处理数据关联性等问题。 相似文献
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为了实现小米米粉糊化特征指标的批量、快速检测,探索计算机深度学习结合高光谱成像技术在小米米粉糊化特征指标预测方面的应用方法,本研究运用高光谱数据提取、预处理分步运算程序获得小米米粉平均光谱数据,并以该数据矩阵为基础,运用麻雀搜索算法(sparrow search algorithm,SSA)优化误差反向传播(error back propagation,BP)算法进行待测样品糊化特征指标回归、预测。结果表明,光谱数据预处理程序能够标准化并简化光谱数据提取、预处理过程,该程序在粉末及小颗粒样本光谱数据的提取、预处理过程中具有普遍适用性;运用BP算法及SSA优化BP算法对小米米粉糊化各特征指标进行预测,从预测值与测试值间均方误差(mean squared error,MSE)可以看出,各指标MSE均下降,以峰值黏度(peak viscosity,PV)为例,其MSE从0.026 6降为0.017 5,可知运用SSA优化BP算法能够提高小米米粉糊化特征指标预测精度,降低MSE。本研究结论可以为高光谱成像结合计算机深度学习在小米米粉糊化特性预测方面应用提供理论支撑。 相似文献
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数据预处理关系到web日志挖掘的质量。本文对此领域的大量文献进行分析,深入探讨了数据预处理环节的主要任务,综述了面向Web日志挖掘中数据预处理的关键技术,指出进一步的研究方向。 相似文献
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该研究利用光栅型便携式近红外光谱仪采集不同陈化年份陈皮内囊和外壁的近红外光谱,利用光谱预处理方法结合不同模式识别方法构建不同年份陈皮的鉴别模型。结果表明:预处理方法可以有效消除光谱中存在的多种干扰;主成分分析方法无法实现不同年份陈皮的准确鉴别分析,外壁和内囊数据最优鉴别率仅为35%和44%;采用软独立模式分类法可以得到更加准确的鉴别结果,外壁和内囊数据最优鉴别率分别为94%和96%;Fisher线性判别分析方法结果最优,外壁最优鉴别率为98%,而采用内囊数据结合原始光谱便可实现不同年份陈皮100%鉴别分析。以上结果表明,采用光栅型便携式近红外光谱仪结合化学计量学方法可以实现不同年份陈皮的无损鉴别分析。 相似文献
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为研究一种可见-近红外光谱结合非线性分析检测大黄鱼储存期的方法,使用光纤光谱仪检测不同存放时间大黄鱼样品的可见-近红外漫反射光谱信号,使用主成分分析法比较3种数据预处理算法。试验结果表明,对数归一化预处理方法提高了样品的区分效果。将对数归一化预处理的大黄鱼检测数据输入非周期随机共振模型,通过输出互相关系数曲线,实现不同存放时间的大黄鱼样品的区分。基于互相关系数特征值,构建大黄鱼贮藏期预测模型。该方法在水产品品质快速分析中具有较好的应用前景。 相似文献
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提出了一种求解Moore-Penrose逆的并行预处理变形共轭梯度法,将求解Moore-Penrose逆转化求解矩阵方程极小范数解或极小范数最小二乘解的问题.给出了两种预处理方法.一种方法是给出预处理矩阵是可逆对角矩阵,然后并行求解预处理矩阵方程;另一种方法是给出预处理矩阵是严格对角占优矩阵,该方法提出了迭代法的预处理模式,构造并行迭代求解预处理矩阵方程的迭代格式,进而使用变形共轭梯度法并行求解.通过数值试验,这两种预处理方法与直接使用变形共轭梯度法相比较,第二种方法有效提高了收敛速度,而且具有很好的并行性. 相似文献
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以构树为原料,利用碱和乙醇对其进行预处理,通过分析两种预处理方法脱木质素的动力学特性,比较它们在脱木质素速率及活化能方面的差异。结果表明,碱法和乙醇预处理构树脱木质素属于一级反应,脱木质素过程主要由大量脱木质素和残余脱木质素阶段组成。在碱法和乙醇预处理中,进入残余脱木质素阶段的温度分别高于130°C和150°C。脱木质素速率会随着预处理温度的升高而提高,且大量脱木质素阶段的速率高于残余脱木质素阶段。比较两种预处理方法的脱木质素动力学数据发现,低温时,两种预处理方法的脱木质素速率相同,而在中、高温时,碱法预处理的脱木质素速率略高于乙醇预处理。在大量脱木质素阶段,碱法预处理脱木质素的活化能为100.2 kJ/mol,乙醇预处理脱木质素的活化能为82.3 kJ/mol,说明乙醇预处理较碱法预处理更容易脱除木质素。 相似文献
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基于高光谱成像的羊肉掺假可视化无损定量检测 总被引:1,自引:0,他引:1
目的:快速、准确检测羊肉掺假。方法:利用可见—近红外(400~1 000 nm)和短波近红外(900~1 700 nm)高光谱成像仪对羊肉中掺假不同比例的鸭肉进行数据采集,比较两个波段范围内不同光谱预处理方法的偏最小二乘法(PLS)建模效果,最终在可见—近红外波段选择归一化预处理方法,在短波近红外波段选择标准正态变量变换(SNV)预处理方法。分别对两个波段的光谱数据进行最优的预处理后,采用连续投影算法(SPA)、竞争性自适应重加权算法(CARS)、区间随机蛙跳算法(iRF)和组合区间偏最小二乘法(SiPLS)对特征波长进行选取。结果:在短波近红外(900~1 700 nm)波段采用SNV-SPA-PLS模型的羊肉掺假预测效果最好,预测集决定系数为0.968 4,预测标准偏差为0.058 2,预测集相对分析误差为5.625 4,并得到较好的图像反演结果。结论:利用不同波段的高光谱成像技术可实现对羊肉掺假的快速无损定量检测。 相似文献
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This paper describes how near-infrared (NIR) spectroscopy combined with radial basis function neural networks (RBFNN) and least-squares support vector machines (LS-SVMs) based on principal component analysis (PCA) can be used to classify wines from grape varieties. The effects of different preprocessing methods (standard normal variate (SNV) and multiplicative scattering correction (MSC)) on classification results were also compared. The results show that the use of NIR preprocessing spectral data with optimum RBFNN parameters produced a very high level of correct classification rate, 90.16–98.36%. For RBF LS-SVM, identification rates were from 91.80 to 98.36%. The results demonstrate that, combined with chemometrics with appropriate spectral data pretreatment, NIR spectroscopy has potential to rapidly and nondestructively differentiate wine according to grape variety. The results of this study are helpful to develop a more rapid and nondestructive detection method of wine. 相似文献
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提出一种基于卷积神经网络的乳粉掺杂物拉曼光谱分类方法。首先利用拉曼高光谱成像平台采集足量乳粉样品的原始光谱,然后利用离散小波变换对原始光谱进行预处理,将预处理后的光谱信号作为卷积神经网络输入构建模型,并分别比较光谱预处理前后的建模效果。结果表明,不合适的光谱预处理反而会降低卷积神经网络的分类效果,而原始拉曼光谱就能被卷积神经网络精准识别,所构建的原始光谱模型对实际未知样品的识别准确率为95.5%。结果表明,卷积神经网络具备光谱预处理与建模的一体化功能,可极大简化拉曼光谱分类识别的计算过程,对乳粉质量安全筛查具有重要意义。 相似文献
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三坐标测量数据预处理系统的设计与开发 总被引:2,自引:1,他引:1
三坐标测量数据的预处理是逆向工程中的一个重要环节,其结果将直接影响到后期模型重构的质量和效率。针对目前CAD系统的数据预处理功能存在的问题,如处理能力有限,过多依赖人工,无法保证精度等。对三坐标测量数据预处理的功能原理进行了研究,主要包括数据转换、数据整合、数据处理、数据保存4个功能模块。采用VC++和Open-GL作为开发工具,实现了系统的开发。实际应用表明,所开发的系统具有较高的数据处理效率和质量。 相似文献
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《Food research international (Ottawa, Ont.)》2007,40(7):835-841
A nondestructive optical method for determining the sugar content and acidity of yogurt was investigated. Three types of preprocessing, S. Golay smoothing with multiplicative scatter correction (S. Golay smoothing with MSC), S. Golay 1st-Der and wavelet package transform (WPT), were used before the data were analyzed with chemometrics methods of partial least square (PLS). Spectral data sets as the logarithms of the reflectance reciprocal were analyzed to build a best model for predicting the sugar content and acidity of yogurt. A model using preprocessing of WPT with a correlation coefficient of 0.91 and 0.90, a root mean square error of prediction (RMSEP) of 0.36 and 0.04 showed an excellent prediction performance to sugar content and acidity. S. Golay smoothing with MSC was also finer, combined with the calibration and validation results. S. Golay 1st-Der was the worse preprocessing method in this experiment. In the paper, a multivariate calibration method of principal component artificial neural network (PC-ANN) was also established. In PC-ANN models, the scores of the principal components were chosen as the input nodes for the input layer of ANN. After adjusting the number of input nodes (principal components), hidden nodes, as well as learning rate and momentum of the network, a model with a correlation coefficient of 0.92 and 0.91, a root mean square error of prediction (RMSEP) of 0.33 and 0.04 showed an excellent prediction performance on sugar content and acidity. At the same time, the sensitive wavelengths corresponding to the sugar content and acidity of yogurt were proposed on the basis of regression coefficients by PLS. 相似文献
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Unknown genetic regulation mechanisms are expected to be discovered by information technology using large amount of biological data especially for gene expression data. In this study, we propose a novel inferring method for genetic interactions that combines our original preprocessing method and the Boolean algorithm. First, the performance of our method was evaluated using artificial data. The results showed that our method was able to infer genetic interactions with high specificity (specificity=0.629). Then, using our method, the genetic interaction was inferred from the experimental time course data collected using microarray on 69 genes of cell cycle for Saccharomyces cerevisiae. Our method estimated about 80% of all genetic interactions in Kyoto Encyclopedia Genes and Genomes (KEGG) for these genes. Furthermore, our method was able to infer several other genetic interactions that are not included in KEGG but whose existence is supported by other biological reports. 相似文献
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Results from recently conducted collaborative trials on the determination of aflatoxin B1 in various matrices have been evaluated to establish whether the use of recovery data would result in a distinct change of the relative between-laboratory standard deviation (RSDR) of the corrected data compared with the uncorrected data. In addition, we applied conventional and robust statistics to evaluate whether the impact of the use of recovery data on the estimation of RSD R depended on the statistical method applied for data analysis. This investigation was based on means before and after correction for recovery. The method performance characteristics were calculated using results from naturally contaminated test materials, while the results from test materials fortified with the target analytes were used to estimate the recovery. The study revealed that applying conventional and robust statistics in general led to comparable estimates for RSDR. The comparison about the use of recovery data showed that in most cases, the RSDR obtained from the analysis of aflatoxin B1 decreased after correction of the results for recovery. This tendency was similar when the comparison was done using robust or conventional statistics. However, in three cases, conventional statistics yielded a higher RSDR for the corrected data, whereas robust statistics showed the opposite. Looking carefully at the data, the treatment of conventional statistics indicated that the way outliers are detected and removed could result in an under- or overestimation of RSDR. Applying the law of error propagation revealed that most likely the correlation between the uncorrected data and the recovery rate led to a reduced variability of the data corrected for recovery. 相似文献