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作物学报 ›› 2016, Vol. 42 ›› Issue (01): 141-148.doi: 10.3724/SP.J.1006.2016.00141

• 研究简报 • 上一篇    下一篇

一种新的符合度算法及其应用

张慧1 ,2，顾世梁1,*，李韬1   

  1. 1扬州大学农学院, 江苏扬州225009; 2桐庐县农业技术推广中心, 浙江杭州311500
  • 收稿日期:2015-02-05 修回日期:2015-09-06 出版日期:2016-01-12 网络出版日期:2015-10-13
  • 通讯作者: 顾世梁, E-mail: slgu@yzu.edu.cn, Tel: 0514-87979358
  • 基金资助:

    本研究由国家农业信息化工程技术研究中心开放课题“小麦育种材料评价研究”项目资助。

A New Algorithm for Conformity and Its Application

ZHANG Hui1,2,GU Shi-Liang1,*,LI Tao1   

  1. 1Agricultural College of Yangzhou University, Yangzhou 225009, China; 2Agricultural Extension Station of Tonglu County, Hangzhou 311500, China
  • Received:2015-02-05 Revised:2015-09-06 Published:2016-01-12 Published online:2015-10-13
  • Contact: 顾世梁, E-mail: slgu@yzu.edu.cn, Tel: 0514-87979358
  • Supported by:

    The study was supported by open project of the National Agricultural Information Engineering Center.

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摘要：

在总结分析了几种常用综合评价方法的基础上, 提出了一种反映观察值与理论值之间相似性的新算法——符合度。该算法就评价信息个体(观察值)与标准值(期望值)的马氏距离, 再由马氏距离转化为评价对象与标准的接近程度, 即符合度(r)。首先进行指标数(p)、相似度(r)与马氏距离(d)的模拟试验, 再通过曲面拟合的方法找出它们之间的关系模型。通过大量抽样试验, 验证符合度的次数分布与原先设定的符合度的良好对应关系, 说明模型的可行性与可靠性。以小麦RVA性状为指标, 利用该算法分析扬麦系统若干品种之间的接近程度, 并评价多变数复杂效应回归分析模拟试验的结果。符合度算法不需要数据标准化处理, 直接利用原始数据, 减少了计算工作量, 降低了因数据标准化处理方法不同而引起的评价结果差异, 同时由于不需要赋权, 排除了主观性的影响, 保证了信息的完整性以及评价结果的可靠性。

关键词: 符合度, 综合评价, 计算机模拟, 马氏距离

Abstract:

This article proposed a new algorithm of conformity using original data to calculate similarities between the target object and the expected value based on the Mahalanobis distance, providing an objective and reasonable analysis. Firstly, simulation experiments were conducted to obtain Mahalanobis distance (d) related to number (p) of different variables (traits) and similarity (r). Then, a surface fitting method was used to establish the function relationship between conformity (r) and index number (p), as well as Mahalanobis distance (d). Monte Carlo experiment for frequency distribution of conformity verified its good performance of the relationship model. The simulation results fully validated the feasibility and reliability of the model. Conformity algorithm was applied to calculating the similarity of a panel of Yangmai wheat varieties released in recent years referring to RVA parameters. The assessment of simulated multivariate regression for complex effects was also conducted. This study showed that conformity algorithm using raw data directly instead of standardized data reduces the work load and decreases inconsistency in similarity assessment with different data processing methods. In addition, conformity algorithm does not need weight assignment to each trait, thus can eliminate potential subjective impacts on traits or data and guarantee integrity of information and reliability of evaluation results.

Key words: Conformity algorithm, Comprehensive evaluation, Computer simulation, Mahalanobis distance

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