Rock Type And Permeability Prediction Of A Heterogeneous Carbonate Reservoir Using Artificial Neural Networks Based On Flow Zone Index Approach

2009 ◽  
Author(s):  
Riyaz Kharrat ◽  
Ramin Mahdavi ◽  
Mohammad Hashem Bagherpour ◽  
Shahab Hejri
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Rock Type ◽  
Carbonate Reservoir ◽  
Flow Zone ◽  
Permeability Prediction ◽  
Index Approach ◽  
Artificial Neural

Classification of Indian meteorological stations using cluster and fuzzy cluster analysis, and Kohonen artificial neural networks

2007 ◽  
Vol 38 (3) ◽  
pp. 303-314 ◽  
Author(s):  
K. Srinivasa Raju ◽  
D. Nagesh Kumar
Keyword(s):  
Neural Networks ◽  
Cluster Analysis ◽  
Artificial Neural Networks ◽  
Optimal Number ◽  
Fuzzy Cluster ◽  
Fuzzy Cluster Analysis ◽  
Homogeneous Groups ◽  
Index Approach ◽  
Artificial Neural

The present study deals with the application of cluster analysis, Fuzzy Cluster Analysis (FCA) and Kohonen Artificial Neural Networks (KANN) methods for classification of 159 meteorological stations in India into meteorologically homogeneous groups. Eight parameters, namely latitude, longitude, elevation, average temperature, humidity, wind speed, sunshine hours and solar radiation, are considered as the classification criteria for grouping. The optimal number of groups is determined as 14 based on the Davies–Bouldin index approach. It is observed that the FCA approach performed better than the other two methodologies for the present study.

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