Analyzing and forecasting the global CO2 concentration - a collaborative fuzzy - neural agent network approach
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| Natura: | Artículo científico |
| Lingua: | en |
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Universidad Nacional Autónoma de México
2015
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| _version_ | 1876434124662636544 |
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| author | T. Chen |
| author_facet | T. Chen |
| contents | Analyzing and forecasting the global CO2 concentration - a collaborative fuzzy - neural agent network approach T. Chen Ingeniería Agent Fuzzy Forecast neural network Goal programming In order to effectively analyze and forecast the global CO 2 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 CO 2 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. 2015 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47439896003 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.3 Vol.13 |
| format | Artículo científico |
| id | redalyc_47439896003 |
| institution | Redalyc |
| language | en |
| publishDate | 2015 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Analyzing and forecasting the global CO2 concentration - a collaborative fuzzy - neural agent network approach T. Chen Ingeniería Agent Fuzzy Forecast neural network Goal programming Analyzing and forecasting the global CO2 concentration - a collaborative fuzzy - neural agent network approach T. Chen Ingeniería Agent Fuzzy Forecast neural network Goal programming In order to effectively analyze and forecast the global CO 2 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 CO 2 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. 2015 artículo científico 1665-6423 https://www.redalyc.org/articulo.oa?id=47439896003 en http://www.redalyc.org/revista.oa?id=474 Journal of Applied Research and Technology application/pdf Universidad Nacional Autónoma de México Journal of Applied Research and Technology (México) Num.3 Vol.13 |
| title | Analyzing and forecasting the global CO2 concentration - a collaborative fuzzy - neural agent network approach |
| topic | Ingeniería Agent Fuzzy Forecast neural network Goal programming |
| url | https://www.redalyc.org/articulo.oa?id=47439896003 |