A Decision Support System for Industry based upon Multivariate Spatial Outlier Detection Techniques

Abstract

Decision support systems are computer based programs which assists decision makers in effective and efficient decision making. Outliers are the data sets which are highly irrelevant with respect to main data sets. Spatial outliers are the spatial objects with distinct features from their surrounding neighbours. In this paper we have proposed a decision support system for strategic decision makers to establish an industry. We have shown how spatial outlier detection techniques may be used to aid decision makers. Each site is evaluated based upon multiple decision variables. Here, we use two different outlier detection algorithms to detect a site which is most unsuitable to establish an industry. We also perform an experiment on a synthetic dataset of fifteen different sites to locate ambiguous sites. We found that decision making process for site selection may be improved by using spatial outlier detection techniques.