Title

Artificial Intelligence – I: Subjective decision making using type-2 fuzzy logic advisor

Abstract/Description

In this paper, we present and compare two-stage type-2 fuzzy logic advisor (FLA) for subjective decision making in the domain of students' performance evaluation. We test our proposed model for evaluating students' performance in our computer science and engineering department at HBCC/KFUPM in two domains namely cooperating training and capstone/senior project assessment where we find these FLAs very useful and promising. In our proposed model, the assessment criteria for different components of cooperative training and senior project are transformed into linguistic labels and evaluation information is extracted into the form of IF-THEN rules from the experts. These rules are modeled using FLS, which then is used as a fuzzy logic advisor (FLA) to make decisions about students' grades. The evaluator's input for the system can be either singleton or non-singleton. Both type-1 and type-2 fuzzy logic based models are implemented and compared with individual expert's evaluation.

Session Theme

Artificial Intelligence – I

Session Type

Other

Session Chair

Dr. Sajjad Haider

Start Date

15-8-2009 2:45 PM

End Date

15-8-2009 3:05 PM

Share

COinS
 
Aug 15th, 2:45 PM Aug 15th, 3:05 PM

Artificial Intelligence – I: Subjective decision making using type-2 fuzzy logic advisor

In this paper, we present and compare two-stage type-2 fuzzy logic advisor (FLA) for subjective decision making in the domain of students' performance evaluation. We test our proposed model for evaluating students' performance in our computer science and engineering department at HBCC/KFUPM in two domains namely cooperating training and capstone/senior project assessment where we find these FLAs very useful and promising. In our proposed model, the assessment criteria for different components of cooperative training and senior project are transformed into linguistic labels and evaluation information is extracted into the form of IF-THEN rules from the experts. These rules are modeled using FLS, which then is used as a fuzzy logic advisor (FLA) to make decisions about students' grades. The evaluator's input for the system can be either singleton or non-singleton. Both type-1 and type-2 fuzzy logic based models are implemented and compared with individual expert's evaluation.