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

Tin-Chih Chen*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


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.

Original languageEnglish
Pages (from-to)364-373
Number of pages10
JournalJournal of Applied Research and Technology
Issue number3
StatePublished - 1 Jan 2015


  • Agent
  • Collaborative intelligence
  • Forecast
  • Fuzzy-neural network
  • Global CO concentration
  • Goal programming

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