Evaluating of academic journals in management of key academic journal fund:An application of simplified principal component analysis based on interval data

National Natural Science Foundation of China(NSFC) encountered many problems,such as an increasing number of applicants and a great many indices,when selecting excellent academic journals as grantees of "Key Academic Journal Fund"and evaluating funding effects.This paper puts forward a method for Principal Component Analysis on interval data,referred to as Simplified Principal Component Analysis(SPCA),specific for large-scaled and high-dimensional data.The proposed method involves two steps,first look for factor axes of the original large-scaled data and then illustrate the analytical results on a low-dimensional space with strengthened visibility and high interpretation.Performing SPCA on academic journal dataset helps to understand the differences in all disciplines and to choose key criteria for selecting excellent journals and measuring funding effect dynamically.