Fuzzy clustering based models applied to petroleum processes
Abstract:
The application of fuzzy clustering techniques has recently become in a very useful alternative in the area of modeling and identification of complex industrial processes. In particular, fuzzy clustering techniques such as Fuzzy C-Means and the Gustafson-Kessel (GK) algorithms will be analyzed and applied in details in this paper. These algorithms will be implemented in the construction of Takagi-Sugeno fuzzy models for the gas-liquid separation process, the water-oil separation process and the oil-heating process, which are important processes in the oil industry. Validations of the obtained fuzzy models will be performed and some conclusions will be established.
Año de publicación:
2008
Keywords:
- Fuzzy C-means
- Production separator
- Gustafson-Kessel (GK) algorithm
- Washing-tanks and fired heaters
- Least-squares method
- Fuzzy Clustering
- Artificial lift production methods
Fuente:
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Tipo de documento:
Article
Estado:
Acceso restringido
Áreas de conocimiento:
- Petróleo
Áreas temáticas:
- Física aplicada
- Aceites, grasas, ceras y gases industriales
- Tecnología alimentaria