Authors: Osadee Peiris, Sanjeewa Perera, Snehashish Chakraverty and Sudheera Ranwala
Abstract: The aim of this study is to evaluate the rate of aggregate risk of Invasive Alien Species (IAS) using invasive attributes accompanied with their grade of important weights toward the invasiveness. We use one of existing Linguistic operators to calculate the important weights in the form of Linguistic terms. And develop a method to fusion the weights and risk values of each attribute to evaluate the rate of risk since these two values are come from two different Linguistic term sets. These rates are compared with the National Risk assessments scores which are in the form of Linguistic labels. Also the model is validated using few known non invasive species in Sri Lanka. The model gives better predictions and it is found to be better tracking system for identifying potential invaders than the conventional risk assessment methods.
Keywords: Invasive Alien Species; Invasive attributes; Risk assessment; Linguistic variables; Rate of aggregate risk; Fuzzy numbers