Irfan Subakti | 司馬伊凡
Adaptive Loose Coupling Intelligent Rule System (ALCIRS)
30 July 2013
Thesis Group Report #4: Thesis Group Meeting
04 July 2013
Thesis Group Report #4: Revised Version
29 April 2013
Thesis Group Report #4
- Irfan Subakti - 2013-04-29 Thesis Group Report #4
15 March 2013
Meeting #16
27 February 2013
Meeting #15
15 February 2013
Meeting #14
30 January 2013
Meeting #13
29 October 2012
Meeting #12
02 November 2012
PhD Thesis Proposal
22 October 2012
Meeting #11
19 September 2012
Meeting #10
18 September 2012
Thesis Group Meeting #3
13 September 2012
Meeting #9
04 September 2012
Raymond Priestly Centre at Lake Coniston: Team Building Course - PhD Thesis Poster
28 June 2012
Meeting #8
06 June 2012
Meeting #7
24 April 2012
Thesis Group Meeting #2
23 April 2012
Meeting #6
09 April 2012
Thesis Group Report #2 (RSMG2 Form)
29 March 2012
Meeting #5
01 March 2012
Meeting #4
25 January 2012
Meeting #3
28 December 2011
Research Skills (06-06991) - Assessment
- Irfan Subakti - 2012-01-25 ALCIRS - Presentation
- Irfan Subakti - 2011-12-28 Report Writing - Evaluating Citation Services & Coverage and Currency Analysis
16 December 2011
Meeting #2
07 December 2011
Thesis Group Meeting #1
01 December 2011
Meeting #1
03 November 2011
Thesis Group Report #1 (RSMG1 Form) has been submitted.
Abstract
We propose a novel Adaptive Loose Coupling Intelligent Rule System (ALCIRS). It's an enhancement of a Variable-Centered Intelligent Rule System (VCIRS)3,4,5,6,7 as we proposed before. In this research, a new method for learning and maintain knowledge in Rule-Based Systems (RBS) will be investigated and developed. This will in part involve combining existing methods for learning and clustering rules by its characteristic for continually optimising the usefulness of the rules. We propose a novel Particle Swarm Optimisation Robust Growing Neural Gas (PSORGNG) for this adaptive purpose, i.e., for rule clustering. This novel method, which is an enhancement from Robust Growing Neural Gas (RGNG)2 bolstered by Particle Swarm Optimisation (PSO)1, resulted in better speed up performance in rule clustering, in addition to its insensitiveness in initialisation, input sequence ordering and the presence of outliers. An optimal number of clusters also can be obtained as well. A novel framework for implementing loose coupling rules is proposed to overcome the rule dependency changing problem. A novel framework for implementing semantics rule-based system is also proposed. It’s achieved by employing the conceptual ontologies. We will synergise all of those novel approaches into a novel system which can achieve an adaptive, loose coupling self-learning rule system and work autonomously. It can be applied for Expert System, eLearning, KDD (Knowledge Discovery and Data Mining), database maintaining and refining system, etc.
References
- Kennedy, J. and Eberhart, R.C. (2001) Swarm Intelligence. San Francisco: Morgan Kaufmann.
- Qin, A.K. and Suganthan, P.N. (2004) Robust Growing Neural Gas Algorithm with Application in Cluster Analysis. Neural Networks, 17, pp. 1135-1148.
- Subakti, I. (2005) A Variable-Centered Intelligent Rule System. In: Proceedings of the 1st Annual International Conference: Information and Communication Technology Seminar (ICTS2005), 1 (1), Surabaya-Indonesia, 11 August 2005. Surabaya-Indonesia: Sepuluh Nopember Institute of Technology (ITS), pp. 167-174.
- Subakti, I. (2006) Some Revisions in VCIRS and Cases Reconstructing Perspectives. In: Proceedings of the 2nd Annual International Conference: Information and Communication Technology Seminar (ICTS2006), 1 (1), Surabaya-Indonesia, 29 August 2006. Surabaya-Indonesia: Sepuluh Nopember Institute of Technology (ITS), Surabaya-Indonesia, pp. 233-238.
- Subakti, I. and Hidayatullah, R. (2007) Aplikasi Sistem Pakar Untuk Diagnosis Awal Gangguan Kesehatan Secara Mandiri Menggunakan Variable-Centered Intelligent Rule System (An Application of Expert System for Independent Healthy Problem Pre-diagnosis Using Variable-Centered Intelligent Rule System). Jurnal Ilmiah Teknologi Informasi (JUTI - Scientific Journal of Information Technology), 6 (1), January 2007, ISSN: 1412-6389. Surabaya-Indonesia: Sepuluh Nopember Institute of Technology (ITS), pp. 11-16.
- Subakti, I. and Wijaya, A.B.A. (2006) Pembuatan Role-Playing Game Berbasis Web Menggunakan Variable-Centered Intelligent Rule System (A Role Playing Game Web-Based Building Using Variable-Centered Intelligent Rule System). Undergraduate Thesis, Department of Informatics, Faculty of Information Technology, Sepuluh Nopember Institute of Technology (ITS), Surabaya-Indonesia.
- Subakti, I. and Wijayanto, O. (2006) Penerapan Konsep Fuzzy dalam Variable-Centered Intelligent Rule System (Studi Kasus: Pemilihan Jurusan di Chinese University of Hongkong) (The Implementation of Fuzzy Concepts in Variable-Centered Intelligent Rule System (Case Study: Department Admission in Chinese University of Hongkong)). Jurnal Informatika, 7 (2), November 2006. Surabaya-Indonesia: The Institute of Research & Community Outreach - Petra Christian University, pp. 98-107.