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About Full Online Version-Hybrid CI Models For Characterization of Oil and Gas Reservoirs
This document discusses two hybrid computational models for characterizing oil and gas reservoirs. The hybrid models combine fuzzy logic, support vector machines, and functional networks. In the first model, functional networks select predictor variables from input data, which are then passed to a type-2 fuzzy logic system for uncertainty handling and rule extraction before final predictions by support vector machines. In the second model, the selected variables are passed to support vector machines for training before type-2 fuzzy logic for uncertainty handling and final predictions. Simulation results show the hybrid models outperform the individual techniques alone in terms of higher correlation coefficients and faster execution times.
Detailed Information
| Author: | ['Fatai Anifowose'] |
|---|---|
| Publication Year: | 2010 |
| Pages: | 11 |
| Language: | English |
| Format: | |
| Price: | FREE |
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