Problem Solving Techniques with Extensive Computational Network and Applying in an Educational Software

Knowledge bases are basic components of expert systems or intelligent computational programs. Knowledge bases provide knowledge, events that serve deduction activity, computation and control. Therefore, researching and developing of models for knowledge representation play an important role in computer science, especially in Artificial Intelligence Science and intelligent educational software. In this paper, the extensive deduction computational model is proposed to design knowledge bases whose attributes are able to be real values or functional values. The system can also solve problems based on knowledge bases. Moreover, the models and algorithms are applied to produce the educational software for solving alternating current problems or solving set of equations automatically.

Authors:



References:
[1] Joseph C. Giarratano & Gary D. Riley, Expert Systems: Principles and
programming, fourth edition, International Thomson Publishing (2004).
[2] Nhon Van Do, Constructing of Intelligent Computation Systems, Ph.D
Thesis, National University of Ho Chi Minh City (2002).
[3] Nhon Van Do, Computational network and its applications, Journal of
computer science and cybernetics, Vietnam ( 2001).
[4] Nhon Van Do & Tam Pham Huu, The Extensive Computational
Network and Applying in an Education Software, ICAIE 2009 -
Wuhan, P.R China, August, 22-23, 2009, pp 720-727, ISBN 978-1-
84626-010-0 (Volume 2).
[5] Nhon Do, An Ontology for Knowledge Representation and Applications,
Proceeding of World Academy of Science, Engineering and
Technology, Volume 32, August 2008, ISSN 2070-3740.
[6] Kiem Hoang & Nhon V. Do, Extension of the knowledge model of
Computational objects, Proceedings of the National Conference on
Information Technology, Vietnam (2005).
[7] Nhon Do & Tuyen T. Tran & Phan H. Truong, Design Method for
Kowledge Base Systems in Education using COKB-ONT, Proceedings
of CITE 2008 (International Conference on Communication and
Information Technologies in Education), Thailand (2008).
[8] John McCarthy, What is Artificial Intelligence , Computer Science
Department - Revised Septemper 1, 2007. Website:
www.formal.stanford.edu/jmc/whatisai
[9] L. Stojanovic, J. Schneider, A. Maedche, S. Libischer, R. Suder, T.
Lumpp, A. Abecker, G. Breiter, J. Dinger, The Role of Onotologies in
Autonomic Computing Systems, IBM Systems Journal, Vol 43, No 3
(2004).
[10] Nie Guihua, Jiang Xiangjie, Chen Donglin, Liang Yueling, Li Xiaofei,
The Research of Personalized Learning Based On Ontology, ICAIE
2009 - Wuhan, P.R China, August, 22-23, 2009, pp 22-26, ISBN 978-
1-84626-010-0 (Volume 1).
[11] Hongwen Xia, Zheng Zhe, The system of E-learning Based on affective
computing, ICAIE 2009 - Wuhan, P.R China, August, 22-23, 2009, pp
571-575, ISBN 978-1-84626-010-0 (Volume 2).
[12] Wang Huiyun, Research of the Multimedia Technology Application in
University Teaching, ICAIE 2009 - Wuhan, P.R China, August, 22-23,
2009, pp 576-580, ISBN 978-1-84626-010-0 (Volume 2).