CAJ | 학술논문

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。
재총결분석료궤충상용종합평개방법적기출상，제출료일충반영관찰치여이론치지간상사성적신산법——부합도。해산법취평개신식개체(관찰치)여표준치(기망치)적마씨거리，재유마씨거리전화위평개대상여표준적접근정도，즉부합도(r)。수선진행지표수(p)、상사도(r)여마씨거리(d)적모의시험，재통과곡면의합적방법조출타문지간적관계모형。통과대량추양시험，험증부합도적차수분포여원선설정적부합도적량호대응관계，설명모형적가행성여가고성。이소맥 RVA 성상위지표，이용해산법분석양맥계통약간품충지간적접근정도，병평개다변수복잡효응회귀분석모의시험적결과。부합도산법불수요수거표준화처리，직접이용원시수거，감소료계산공작량，강저료인수거표준화처리방법불동이인기적평개결과차이，동시유우불수요부권，배제료주관성적영향，보증료신식적완정성이급평개결과적가고성。
This article proposed a new algorithm of conformity using original data to calculate similarities between the target ob-ject 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 calculate 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.