The week's pick
Random Articles
Reseach Article
A Brief Survey on Fuzzy Logic Systems for Performance Appraisal
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 181 - Number 24 |
| Year of Publication: 2018 |
| Authors: Ramit Manuja, Sandeep Singh Bindra, S. C. Gupta |
10.5120/ijca2018918036
|
Ramit Manuja, Sandeep Singh Bindra, S. C. Gupta . A Brief Survey on Fuzzy Logic Systems for Performance Appraisal. International Journal of Computer Applications. 181, 24 ( Oct 2018), 39-42. DOI=10.5120/ijca2018918036
Abstract
Effective monitoring of student’s performance is an important task for successful higher learning. Performance appraisal enables institutions to foresee student progression as well as inform the students well in time, the areas they need to improve. Traditional evaluation methods do not fully justify these objectives whereas Fuzzy logic based appraisal approaches are like human inference and give better evaluation results. In this paper we describe the advantages of the fuzzy logic approach for performance evaluation over the traditional method as fuzzy expert system can be built not only with the given information in the dataset but can also include the vital knowledge of experts at various levels as and when required. Furthermore, various existing approaches using fuzzy logic approach in this field have been investigated and compared for their merits and demerits.
References
- N. A. Kumari, D. N. Rao, “Indexing Student Performance with Fuzzy Logics Evaluation in Engineering Education”, Issue 9, Volume 4, ISSN 2394-3386, 2017.
- D. Deliktas, O. Ustun, “Student Selection and Assignment Methodology based on Multimoora and multi choice goal programming”, International transactions in Operational research, Issue 5, Volume 24, pp. 1173-1195, 2017.
- K. Chrysafiadi, M. Virvou, “Evaluating the intergration of Fuzzy logic into the student model of a web learning environment”, Elsevier Journal of Expert Systems and Applications, Volume 39, pp. 13127-13134, 2012
- S. Deb, P. Bhattacharya, “A Framework to enhance the Learning Outcome with Fuzzy Logic ABLS”, Advances in Intelligent Systems and Computing, Volume 564, pp. 3-11, 2017
- A. Kharola, S. Kunwar, “Student Performance Evaluation: A Fuzzy Logic Reasoning Approach”, PM world Journal, Issue 4, Volume 9, pp. 1-11, 2015.
- L. A. Zadeh, “The Concept of Linguistic Variable and its application to Approximate Reasoning”, Information Sciences, Volume 8, pp. 199-249, 1975.
- S. G. Tzafestas, S. Terjakis, “Fuzzy Sets and Fuzzy Reasoning: An Introduction”, Fuzzy Reasoning in Information and Decision Control Systems, pp. 3-29, 1994.
- A. Kaur, A.Kaur, “Comparison of Mamdani type and Surgeno type Fuzzy Inference System for AC system”, International Journal of Soft Computing and Engineering (IJSCE), Issue 2, Volume 2, pp. 325-329, 2012.
- A. A. Surya, M. K. Kurian, “Overall Performance Evaluation Engineering Students using Fuzzy Logic”, International Journal on Cybernetics and Informatics, Issue 2, Volume 5, 2016.
- M. Guruprasad, A. Arora, “Fuzzy Logic as a tool for evaluation of performance of Faculty in higher Education Systems”, SHS web of Conference by EDP Sciences, 2016.
- G. Jyothi, P. Parvathi, “Fuzzy Expert model of Evaluation of faculty performance in Technical Education Institutions”, International Journal of Engineering Research and Applications, Issue 4, Volume 5, pp. 41-50, 2014.
- A. Shout, M. K. Yousif, “Employee Performance Appraisal System using Fuzzy logic”, International Journal of Computer Science and Information Technology (IJCSIT), Issue 6, Volume 4, pp. 1-19, 2014.
- M. H. Wang, C. S. Wang “Type 2 Fuzzy Set construction and Application for Adaptive Student Assessment System”, IEEE internal conference on Fuzzy Systems (FUZZ-IEEE), pp. 888-894, 2014.
- R. S. Yadav, A. K. Soni, “A Study of Academic Performance Evaluation using Fuzzy Logic Techniques”, In Proceedings of IEEE conference on Computing for Sustainable global development, pp. 48-53, 2014
- Z. Yildiz, A. F. Baba, “Evaluation of Student Performance in Laboratory Applications using Fuzzy Decision Support Model”, In Proceedings of IEEE Global Engineering Education Conference (EDUCON), pp. 1023-1027, 2014
- N. Arora, J. K. Saini, “A Fuzzy Probabilistic Neural Network for student Academic Performance Evaluation ”, International Journal of Innovative Research in Science, Issue 2, Volume 9, ISSN 2319-8573, 2013
- S. S. Jamsandekar, R. R. Mudholkar, “Performance Evaluation by Fuzzy Inference Technique”, International Journal of Soft Computing and Engineering (IJSCE), Issue 3, Volume 2, pp. 158-164, ISSN 2231-2307, 2013.
Index Terms
Keywords