| Revista: | Journal of applied research and technology |
| Base de datos: | PERIÓDICA |
| Número de sistema: | 000384079 |
| ISSN: | 1665-6423 |
| Autores: | Chen, T1 |
| Instituciones: | 1Feng Chia University, Department of Industrial Engineering and Systems Management, Taichung. Taiwán |
| Año: | 2015 |
| Periodo: | Jun |
| Volumen: | 13 |
| Número: | 3 |
| Paginación: | 364-373 |
| País: | México |
| Idioma: | Inglés |
| Tipo de documento: | Artículo |
| Enfoque: | Experimental, aplicado |
| Resumen en inglés | 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 |
| Disciplinas: | Geociencias, Ciencias de la computación, Ingeniería |
| Palabras clave: | Ciencias de la atmósfera, Redes, Ingeniería ambiental, Contaminación atmosférica, Dióxido de carbono, Predicción, Inteligencia colaborativa, Redes neurodifusas |
| Keyword: | Earth sciences, Computer science, Engineering, Atmospheric sciences, Networks, Environmental engineering, Atmospheric pollution, Carbon dioxide, Forecasting, Fuzzy neural networks, Collaborative intelligence |
| Texto completo: | Texto completo (Ver HTML) |
