Modelling and simulation of coal gases in a nano-porous medium: a biologically inspired stochastic simulation

摘要: This paper aims to study the dynamics of unsteady pressure flow coal gases caused by temperature conditions and compressibility in presence a nano-porous medium using soft computing technique. To immaculately understand mechanism, novelty partial differential equation is augmented considering fractional-order Caputo derivative, which produces theoretically significant accurate approximation. Subsequently, constructed model experimentally simulated means artificial neural network (ANN) stochastic process based on firefly algorithm (FFA). ANN has ability approximate transform into an error minimization problem, while FFA efficiently minimizes function optimizes unknown weights network. Furthermore, two measuring tools; mean absolute root square error, also formulated evaluate performance index designed scheme. Accordingly, scheme systematically elaborated assess sorption such as nitrogen (N2) carbon dioxide (CO2). The accuracy obtained approximation shows competitiveness considered Notably, deliberation provides substantial indications about dynamical behaviour gases, can be implemented significantly various problems.