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What is Adaptive Neuro-Fuzzy Inference System (ANFIS)

Handbook of Research on Discrete Event Simulation Environments: Technologies and Applications
Is a data mining methodology based on a combination of fuzzy logic & neural networks by clustering values in fuzzy sets, membership functions are estimated during training, and using neural networks to estimate weights (Alnoukari, Alzoabi, and Hanna, 2008).
Published in Chapter:
An Integrated Data Mining and Simulation Solution
Mouhib Alnoukari (Arab Academy for Banking and Financial Sciences, Syria), Asim El Sheikh (Arab Academy for Banking and Financial Sciences, Jordan), and Zaidoun Alzoabi (Arab Academy for Banking and Financial Sciences, Syria)
DOI: 10.4018/978-1-60566-774-4.ch016
Abstract
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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