A Gaussian function model for simulation of complex environmental sensing

Abstract

Background: Sensors can be used to sense not only simple behavior but also complex ones. Previous work has demonstrated how agent-based modeling can be used to model sensing of complex behavior in Complex Environments. Findings: Here, we propose a mathematical model using Gaussian function for the previously developed Agent Based Model (ABM) for Sensing of Emergent behavior in Complex Adaptive System (SECAS). The goodness of the fitted curve was observed by using standard tools, e.g. by determining SSE, SSM, ASSM and RMSE. Conclusions: Our proposed model provides a good fit for data obtained from the earlier model. Also the developed model provides a bench mark against the data obtained from a former Agent Based Model.