scholarly journals Application of adaptive neuro-fuzzy inference system and data mining approach to predict lost circulation using DOE technique (case study: Maroon oilfield)

Petroleum ◽  
2018 ◽  
Author(s):  
Farough Agin ◽  
Rasool Khosravanian ◽  
Mohsen Karimifard ◽  
Amirhosein Jahanshahi
Keyword(s):  
Data Mining ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Inference System ◽  
Lost Circulation ◽  
Data Mining Approach ◽  
Neuro Fuzzy

An Integrated Data Mining and Simulation Solution

2010 ◽  
pp. 929-948
Author(s):  
Mouhib Alnoukari ◽  
Asim El Sheikh ◽  
Zaidoun Alzoabi
Keyword(s):  
Data Mining ◽  
Fuzzy Inference ◽  
Decision Support Tools ◽  
Market Demand ◽  
Inference System ◽  
Car Market ◽  
Neuro Fuzzy ◽  
Support Tools ◽  
Quality In Higher Education

Simulation and data mining can provide managers with decision support tools. However, the heart of data mining is knowledge discovery; as it enables skilled practitioners with the power to discover relevant objects and the relationships that exist between these objects, while simulation provides a vehicle to represent those objects and their relationships. In this chapter, the authors will propose an intelligent DSS framework based on data mining and simulation integration. The main output of this framework is the increase of knowledge. Two case studies will be presented, the first one on car market demand simulation. The simulation model was built using neural networks to get the first set of prediction results. Data mining methodology used named ANFIS (Adaptive Neuro-Fuzzy Inference System). The second case study will demonstrate how applying data mining and simulation in assuring quality in higher education

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