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标准样本
    When unknown samples are analysed by this method, identification, classification and assessment can be carried out by compared the similarity of standard samples with the unknown ones.
    在分析未知样品时,只需计算未知样品与标准样本间的相似度,即可对未知样品进行鉴定、分类和评价。
    2. Standard samples that are needed for neural network training are made.
    2. 制作神经网络训练所需的标准样本
    We can read, input and keep datum and calculate the reflectivity, three stimulate value, color coordinate and chromatism in data input interface. And we’ll compare the chromatism of testing samples and standard samples to identify and classify the samples.
    数据输入界面模块主要完成数据的读取、存储以及三刺激值、色坐标和色差的计算,在完成各种数据的计算后,还要比较待测样本与各个标准样本色差的大小,从而实现对样本的识别分类功能。
    The function of reflectivity graph display interface is displaying the reflectivity graphs of testing samples and standard samples to provide gist for identifying and classifying of diamond color.
    反射率曲线图显示界面的主要功能是显示标准样本和待测样本的反射率曲线图,以便为钻石颜色的识别分类提供依据。
    At the same time, this system displayed the calculating results of chromatism between this testing sample and other standard samples and the the reflectivity graphs.
    但是通过比较其色差计算结果发现待测样本y26与标准样本y2的色差值要大于其与标准样本y3的色差值,再观察反射率曲线图表明待测样本y26的反射率曲线与标准样本y3的反射率曲线更接近。 这就表明是实验前的肉眼分类有误,本系统的测试结果是正确的。
    From the existing patten recognization or statistical analysis methods, we have selected the integrated parameter method for a filter of maximum output energy and the discriminant analysis method which is based on learning from standard samples. After integrated processing of seismic parameters, we can make prediction of reservoir lithology or hydrocarbon.
    从现有的模式识别或统计分析方法中,选用了输出能量最大准则滤波的综合参数法和标准样本学习的判别分析法进行储层岩性预测.
    In order to study the possibility of the application of artificial neural network to the classified forecasting of typhoon, the training to standard samples of classified typhoon is performed using B-P network with Sigmoid function. The classified forecasting is made for typhoon according to the calculated outputs of network in the basis of the trained weight and threshold values as well as the monitoring values of sample's factors.
    为了探索人工神经网络应用于台风分类预报的可能性,用具有S-型特性函数的B-P网络对每类台风的标准样本进行训练,由训练结束后的权值和阈值及待预报样本的因子测值,计算出网络输出值,作出台风分类预报。
    Selected standard samples are trained, the stable weight values and threshold value of the system are obtained.
    用选定的标准样本进行训练,得到稳定的权值和阈值。
    Using the B P algorithm of artificial neural network,selected standard samples are trained. The optimal number of sites of environmental monitoring is obtained using the stable weight values and threshold values of the network trained,as well as the network output for the standard samples.
    采用B-P算法的人工神经网络,对选定的标准样本进行训练,用训练结束后网络的稳定权值和阈值,并结合标准样本的网络输出,即可对环境监测样点进行优选。
    Through optimally selecting a group of virtual standard samples off-line, this algorithm can fulfill rapid and accurate on-line fault recognition, so it can effectively solve the problem of local convergence with FCM.
    该方法通过离线优选虚拟标准样本,达到快速、准确在线识别故障的目的,很好地解决了FCM算法经常收敛到局部极值点的问题。
    With normal and fault state signals of outside-rolling, rolling bearing, inside-rolling as the standard samples and working state signals as the example, the time-series signal is analyzed in the form of Fourier change and more important, the mean of correlation dimensions.
    以滚动轴承在正常、外圈故障、滚动体故障、内圈故障4种状态下的信号特征为标准样本,以其运行的实测信号为例,对时域信号进行了频谱分析,并进一步进行了关联维数分析。
 

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