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论文类型：期刊论文

发表时间：2016-03-11

发表刊物：JOURNAL OF APPLIED STATISTICS

收录刊物：SCIE

卷号：43

期号：4

页面范围：767-781

ISSN号：0266-4763

关键字：disaster; missing values; trapezoidal fuzzy numbers; K nearest neighbor

摘要：Due to destructiveness of natural disasters, restriction of disaster scenarios and some human causes, missing data usually occur in disaster decision-making problems. In order to estimate missing values of alternatives, this paper focuses on imputing heterogeneous attribute values of disaster based on an improved K nearest neighbor imputation (KNNI) method. Firstly, some definitions of trapezoidal fuzzy numbers (TFNs) are introduced and three types of attributes (i.e. linguistic term sets, intervals and real numbers) are converted to TFNs. Then the correlated degree model is utilized to extract related attributes to form instances that will be used in K nearest neighbor algorithm, and a novel KNNI method merging with correlated degree model is presented. Finally, an illustrative example is given to verify the proposed method and to demonstrate its feasibility and effectiveness.