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目的:使用遗传算法建立针对不同错类型的各牙牙冠宽度与其它牙的相关方程,并将同类型同性别的各牙用一个公式进行表达。方法:选取安氏Ⅰ、Ⅱ、Ⅲ类患者初诊模型各100副,每种类型男女各50副,45副作为模拟样本,5副作为检验样本。用游标卡尺测量各牙冠宽度,对不同错类型分别采用遗传算法(Genetic Algorithms,简称GAS)建立各牙与其他牙冠宽度的关系方程,并与线性回归分析法进行精度比较。结果:建立了不同错类型各牙与其他牙冠宽度的相关方程。GAS法与线性回归分析法的预测值分别与实测值比较,绝大多数牙位无统计学意义,但GAS法的检验样本平均误差绝对值均小于线性回归分析法。结论:GAS法的预测精度优于线性回归分析法,建立的方程有利于对不同错类型牙列萌出不全患者进行全牙列间隙分析。
OBJECTIVE: To establish the correlation equations between the widths of the crowns and other teeth of different types of teeth according to the genetic algorithm, and to express the teeth of the same type by the same formula. Methods: A total of 100 newly diagnosed patients of Class Ⅰ, Ⅱ and Ⅲ were enrolled in this study. Fifty male and female patients of each type, 45 were selected as the simulated samples and 5 as the test samples. The width of each crown was measured by vernier calipers. The relationship equations between teeth and other crown widths were established by using Genetic Algorithms (GAS) for different types of errors. The accuracy was compared with linear regression analysis. Results: The correlation equations between different teeth and other crown widths were established. The predicted values of GAS and linear regression analysis were compared with the measured values, respectively. Most of the teeth had no statistical significance. However, the mean absolute error of the GAS test samples was less than that of the linear regression analysis. Conclusion: The prediction accuracy of GAS method is better than that of linear regression analysis. The established equation is conducive to analyze all-dentition gap in patients with different types of dentition eruptions.