Given a non-equidistant sequence or an equidistant series with one or more outliers, a grey interpolation approach considering the time lags is established for producing the missing data or correcting the abnormal val...Given a non-equidistant sequence or an equidistant series with one or more outliers, a grey interpolation approach considering the time lags is established for producing the missing data or correcting the abnormal values. To accomplish this, a new grey incidence model, called the grey dynamic incidence model GDIM(t), is constructed for determining whether the factors are effective to the known factor and what the time lag is between a useful factor and the specified sequence. Based on the results of the GDIM(t) model, two programming problems are designed to obtain the upper and lower bounds of the unknown or abnormal values which are regarded as grey numbers. The solutions based on the particle swarm optimization(PSO) for the nonlinear programming problems are given. To explain how it can be used in practice, this new grey interpolation approach is applied to correct an abnormal value in the sequence of an agriculture environment problem.展开更多
基金supported by the National Natural Science Foundation of China(7137109871071077)+4 种基金Funding of Jiangsu Innovation Program for Graduate Education(KYZZ15 0093)Fundamental Research Funds for the Central Universities(2017301)Natural Science Fund Project of Colleges in Jiangsu Province(16KJD120001)Funding for Major Project of Jiangsu Social Science(16GLA001)Funding for Outstanding Doctoral Dissertation in Nanjing University of Aeronautics and Astronautics(BCXJ15-10)
文摘Given a non-equidistant sequence or an equidistant series with one or more outliers, a grey interpolation approach considering the time lags is established for producing the missing data or correcting the abnormal values. To accomplish this, a new grey incidence model, called the grey dynamic incidence model GDIM(t), is constructed for determining whether the factors are effective to the known factor and what the time lag is between a useful factor and the specified sequence. Based on the results of the GDIM(t) model, two programming problems are designed to obtain the upper and lower bounds of the unknown or abnormal values which are regarded as grey numbers. The solutions based on the particle swarm optimization(PSO) for the nonlinear programming problems are given. To explain how it can be used in practice, this new grey interpolation approach is applied to correct an abnormal value in the sequence of an agriculture environment problem.
