Analyzing and forecasting the global CO2 concentration — a collaborative fuzzy-neural agent network approach

Main Article Content

T.  Chen

Abstract

In order to effectively analyze and forecast the global CO2 concentration, a collaborative fuzzy-neural agent network is constructed in this study. In the collaborative fuzzy-neural agent network, a group of autonomous agents is used. These agents are programmed to analyze and forecast the global CO2 concentration using the fuzzy back propagation network (FBPN) approach based on their local views. A collaboration mechanism is established to communicate the settings and forecasts of these agents, and to derive a single representative value from these forecasts using a radial basis function network. The real data were used to evaluate the effectiveness of the collaborative fuzzy-neural agent network approach. All Rights Reserved © 2015 Universidad Nacional Autónoma de México, Centro de Ciencias Aplicadas y Desarrollo Tecnológico. This is an open access item distributed under the Creative Commons CC License BY-NC-ND 4.0.

 

PLUM ANALYTICS

Article Details

How to Cite
Chen, T. (2015). Analyzing and forecasting the global CO2 concentration — a collaborative fuzzy-neural agent network approach. Journal of Applied Research and Technology, 13(3). https://doi.org/10.1016/j.jart.2015.07.002