Dispersion Model of Volatile Organic Compounds Based on RBF Neural Network

Abstract

Abstract In this paper, we try to establish the dispersion model of Volatile Organic Compounds (VOCs). Whereas the mechanism dispersion model is too complicated and only suitable for the case where only one release source exists, we establish the black-box model based on data for the case where multiple release sources exist. After the input and output variables are determined, the Radial-Basis Function (RBF) neural network is used to describe the relationship between the inputs and the outputs because it can approximate arbitrary function with arbitrary precision. Considering the difficulty in selecting the parameters of RBF neural network, we use the Swarm Cuckoo Search (SCS) algorithm to obtain the suitable parameters. The simulation experiments demonstrate the effectiveness of the proposed model.