PDEMR Model in Rare Protea Count Prediction

Abstract

In this paper, we merge partial differential equation model, regression model and credibility measure based fuzzy mathematics proposed by Liu into a new partial differential equation motivated regression model (abbreviated as PDEMR model). The creation of PDEMR model further extends DEMR model ideation proposed by Guo et al. Furthermore, we develop a PDEMR model for the quantitative modeling on multivariate small sample data. PDEMR models will be able to establish the quantitative relationship among the main factor vector and the covariate vectors, which is a major improvement of information extraction with sparse data availability. Finally, we apply the PDEMR model to South African rare Protea species predictions and even tune up the data set for a regional GIS kriging maps.