首页> 外国专利> PROGRAM FOR CONSTRUCTING EXPANSION WEIGHT UPDATE TYPE SELF-ORGANIZATION MAP, PROGRAM FOR ESTIMATING CHARACTERISTIC VALUE USING CONSTRUCTED EXPANSION WEIGHT UPDATE TYPE SELF-ORGANIZATION MAP AND CHARACTERISTIC VALUE ESTIMATION APPARATUS EMPLOYING EXPANSION WEIGHT UPDATE TYPE SELF-ORGANIZATION MAP

PROGRAM FOR CONSTRUCTING EXPANSION WEIGHT UPDATE TYPE SELF-ORGANIZATION MAP, PROGRAM FOR ESTIMATING CHARACTERISTIC VALUE USING CONSTRUCTED EXPANSION WEIGHT UPDATE TYPE SELF-ORGANIZATION MAP AND CHARACTERISTIC VALUE ESTIMATION APPARATUS EMPLOYING EXPANSION WEIGHT UPDATE TYPE SELF-ORGANIZATION MAP

机译:用于构造扩展权重更新类型的自组织映射的程序,用于利用构造的扩展权重更新类型的自组织映射和用于特征值估计的装置来估计特征值的程序,用于应用扩展权重的更新模型

摘要

PROBLEM TO BE SOLVED: To provide a program for constructing an expansion weight update type self-organization map while using much data for learning.SOLUTION: When a feature amount obtained by measuring a substance is inputted, a program for constructing an expansion weight update type self-organization map for quantitatively calculating and outputting a characteristic value of which the character is different from the feature amount, allows a computer to execute the steps of accepting input of a plurality of measurements of the feature amount and a plurality of measurements of the characteristic value which are measured under different conditions (step S1), and calculating variance of the measurements and excludes the measurements of which the variance is equal to or more than a predetermined threshold value (step S3). Further, outlier values are excluded from among the measurements (step S4) and a learning sample is created by making the remaining measurements of the feature amount and the characteristic value through statistical analysis (step S5). In accordance with the created learning sample, the self-organization map is allowed to perform expansion weight update learning so as to be constructed as an expansion weight update type self-organization map having a competitive layer in which a relationship between feature amounts is mapped (step S6).
机译:解决的问题:提供一种用于在使用大量数据进行学习的同时构造扩展权重更新类型自组织图的程序。解决方案:当输入通过测量物质获得的特征量时,用于构建扩展权重更新类型的程序。用于定量计算和输出其字符与特征量不同的特征值的自组织图,允许计算机执行以下步骤:接受特征量的多个测量值和特征的多个测量值的输入在不同条件下测量的值(步骤S1),计算测量值的方差,并且排除方差等于或大于预定阈值的测量值(步骤S3)。此外,从测量值中排除异常值(步骤S4),并且通过统计分析对特征量和特征值进行剩余测量,从而创建学习样本(步骤S5)。根据创建的学习样本,允许自组织图执行扩展权重更新学习,以构造为具有竞争层的扩展权重更新类型自组织图,其中特征量之间的关系被映射(步骤S6)。

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