光电工程, 2014, 41 (8): 66, 网络出版: 2014-09-01  

改进的KNN算法在光测图像关键事件评估中的应用

The Application of Improved KNN Algorithm in Optical Image Key Events Assessment
作者单位
1 中国科学院光电技术研究所, 成都 610209
2 中国科学院大学, 北京 100049
摘要
KNN算法是光测图像关键事件评估中常用的算法, 经典的 KNN算法只注重候选范例的个数, 而忽视候选范例个体的特殊性, 因此 KNN方法在某些时候会使得评估结论极不合理。基于此, 本文提出了改进的 KNN算法, 该算法更加注重候选范例的个体性, 候选范例到目标范例的距离、候选范例的概率分布等, 对目标范例的评估结论都有重要影响。实验结果表明, 本文提出的 KNN改进算法比经典 KNN算法评估结论更准确, 计算出的隶属度表征了关键事件成功失败的程度, 结论更实际更合理。
Abstract
KNN algorithm is a commonly used algorithm in the assessment of optical image key event. However, classical KNN algorithm always makes conclusion unreasonable, because it only concerns about the number of candidate cases, neglecting of candidate cases’ private characters. To solve this problem, an improved KNN algorithm was proposed, which focused on the private characters of candidate cases. This paper argued that, the distance between candidate cases and target case, and the probability distribution of the candidate cases, both had important influence on last conclusion of target case. The test results showed that, the KNN algorithm proposed was more accurate than classical KNN algorithm, and the membership in proposed KNN algorithm represented degree of success or failure, which were more practical and more reasonable in the engineering practice.

陈帅均, 蒋平, 吴钦章. 改进的KNN算法在光测图像关键事件评估中的应用[J]. 光电工程, 2014, 41(8): 66. CHEN Shuaijun, JIANG Ping, WU Qinzhang. The Application of Improved KNN Algorithm in Optical Image Key Events Assessment[J]. Opto-Electronic Engineering, 2014, 41(8): 66.

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