IJCIR Home
   About IJCIR
   Editorial Board
   Call for Papers
   Submit Papers
   Author Instructions
   Editorial Policies
 
   Webmail
   Contact Us
 
   Volume 4 (1) 2010
 
   Volume 3 (2) 2009
   Special Issue 2009
   Volume 3 (1) 2009
 
   Volume 2 (2) 2008
   Special Issue 2008
   Volume 2 (1) 2008
 
   Volume 1 (2) 2007
   Volume 1 (1) 2007
ISSN 1996-1065 [Online]
ISSN 1818-1139 [PRINT]
Volume 2 (2) 2008
Title:Type-2 Fuzzy User Interface for Artificial Neural Network based Decision Support System for Course Selection
Authors: Priti Srinivas Sajja*
Published: ŠIJCIR Vol2 (2) 2008, PP. 96-102
Language: English


Abstract:
Enabling information and knowledge to the right people in right time increases productivity and effectiveness of the decisions made. This article describes design for an Artificial Neural Network (ANN) based decision support system along with fuzzy user interface based on type-2 fuzzy sets. The system supports beneficiaries to select suitable course/curriculum. The major criteria for making such decisions related to proper course selection are identified to design an ANN structure. An example set of 9 normalized input parameters and 3 output situations for the case is illustrated in this paper. Output achieved for the case is shown along with error graph and weight analyzer graph. The design framework, heuristics to decide number of neurons/layers along with fully designed neural network and fuzzy interface are also discussed here. As the ordinary fuzzy set does not capture uncertainty particularly dealing with vagueness and ambiguity in complex system, type-2 fuzzy sets are used. The discussion also includes introduction and an example of type-2 fuzzy set along with an example and application systems. The design of the system is adaptive and flexible to be used widely in fields like medicine, corporate sector, engineering, job scheduling, etc. to impart quality and productivity in decision making and offer advantages of knowledgeoriented decision making in an interactive way. View full Article

Categories and Subject Descriptors: I.0.0 [Artificial Intelligence]; I.2.0: [Artificial Intelligence]:
Knowledge Representation; I.2.4: [Artificial Intelligence]: Knowledge Representation - Design of Neuro- Fuzzy System
General Terms: Design of Neuro-Fuzzy Systems
Additional Key Words and Phrases: type 2 fuzzy interface system, course selection application