Optimizing cluster of questions by using dynamic mutation in genetic algorithm

Nur Suhailayani Suhaimi, Siti Nur Kamaliah, Norazam Arbin, Zalinda Othman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Clustering dynamic data is a challenge inidentifying and forming groups. This unsupervised learningusually leads to indirect knowledge discovery. The clusterdetection algorithm searches for clusters of data which aresimilar to one another by using similarity measures.Optimizing the clustered data with certain fixed values couldbe an issue. Depending on the parameters and attributes of thedata, the results yielded probably either stuck in local optimaor bias by attributes pattern. Performing Genetic Algorithm inthe data cluster may increase the probability of the questionsbeing clustered in the optimal group cluster. DynamicMutation in Genetic Algorithm used as repair mechanism toensure the cluster is optimized enough and produce optimumindexed questions set.

Original languageEnglish
Title of host publicationProceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages15-18
Number of pages4
ISBN (Electronic)9781467386753
DOIs
Publication statusPublished - 20 Oct 2016
Event3rd International Conference on Artificial Intelligence, Modelling and Simulation, AIMS 2015 - Kota Kinabalu, Sabah, Malaysia
Duration: 2 Dec 20154 Dec 2015

Other

Other3rd International Conference on Artificial Intelligence, Modelling and Simulation, AIMS 2015
CountryMalaysia
CityKota Kinabalu, Sabah
Period2/12/154/12/15

Fingerprint

Mutation
Genetic algorithms
Genetic Algorithm
Data mining
Repair
Attribute
Clustered Data
Knowledge Discovery
Similarity Measure
Search Algorithm
Clustering

Keywords

  • Dynamic
  • Genetic Algorithm
  • Optimization

ASJC Scopus subject areas

  • Artificial Intelligence
  • Modelling and Simulation

Cite this

Suhaimi, N. S., Kamaliah, S. N., Arbin, N., & Othman, Z. (2016). Optimizing cluster of questions by using dynamic mutation in genetic algorithm. In Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation (pp. 15-18). [7604544] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AIMS.2015.81

Optimizing cluster of questions by using dynamic mutation in genetic algorithm. / Suhaimi, Nur Suhailayani; Kamaliah, Siti Nur; Arbin, Norazam; Othman, Zalinda.

Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation. Institute of Electrical and Electronics Engineers Inc., 2016. p. 15-18 7604544.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Suhaimi, NS, Kamaliah, SN, Arbin, N & Othman, Z 2016, Optimizing cluster of questions by using dynamic mutation in genetic algorithm. in Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation., 7604544, Institute of Electrical and Electronics Engineers Inc., pp. 15-18, 3rd International Conference on Artificial Intelligence, Modelling and Simulation, AIMS 2015, Kota Kinabalu, Sabah, Malaysia, 2/12/15. https://doi.org/10.1109/AIMS.2015.81
Suhaimi NS, Kamaliah SN, Arbin N, Othman Z. Optimizing cluster of questions by using dynamic mutation in genetic algorithm. In Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation. Institute of Electrical and Electronics Engineers Inc. 2016. p. 15-18. 7604544 https://doi.org/10.1109/AIMS.2015.81
Suhaimi, Nur Suhailayani ; Kamaliah, Siti Nur ; Arbin, Norazam ; Othman, Zalinda. / Optimizing cluster of questions by using dynamic mutation in genetic algorithm. Proceedings - AIMS 2015, 3rd International Conference on Artificial Intelligence, Modelling and Simulation. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 15-18
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