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Developing Web-based Semantic and Fuzzy Expert Systems using Proposed Tool

by Mostafa A. Nofal, Khaled M. Fouad
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 112 - Number 7
Year of Publication: 2015
Authors: Mostafa A. Nofal, Khaled M. Fouad
10.5120/19682-1414

Mostafa A. Nofal, Khaled M. Fouad . Developing Web-based Semantic and Fuzzy Expert Systems using Proposed Tool. International Journal of Computer Applications. 112, 7 ( February 2015), 38-45. DOI=10.5120/19682-1414

@article{ 10.5120/19682-1414,
author = { Mostafa A. Nofal, Khaled M. Fouad },
title = { Developing Web-based Semantic and Fuzzy Expert Systems using Proposed Tool },
journal = { International Journal of Computer Applications },
issue_date = { February 2015 },
volume = { 112 },
number = { 7 },
month = { February },
year = { 2015 },
issn = { 0975-8887 },
pages = { 38-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume112/number7/19682-1414/ },
doi = { 10.5120/19682-1414 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:48:53.045912+05:30
%A Mostafa A. Nofal
%A Khaled M. Fouad
%T Developing Web-based Semantic and Fuzzy Expert Systems using Proposed Tool
%J International Journal of Computer Applications
%@ 0975-8887
%V 112
%N 7
%P 38-45
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Developing the expert system (ES) using conventional programming languages is very tedious task. Therefore, it is not surprising that tools have been developed that can support the knowledge engineer. Separate tools now exist to support the knowledge acquisition and to support the implementation. Fuzzy set theory is used to capture imprecision in inputs and outputs of models, and fuzzy expert systems are used as a method of reasoning with imprecision. Fuzzy expert system permits handling uncertainties, ambiguities, and contradictions in the knowledge. In this research, a tool is proposed for development of web-based expert systems and utilizes fuzzy logic and semantic web technology which permits the knowledge engineer and domain expert to define the knowledge without having to know anything about programming languages and AI. The knowledge can be conceptualized using WordNet. The tool can induce new rules based on the semantic similarity of the concepts using WordNet. During acquiring the knowledge by a proposed tool using domain expert, the fuzzification process can be performed for values of in the acquired knowledge, then, the fuzzy inference can be initiated that has derivation of the control outputs based on the calculated fire strength and the defined fuzzy sets for each output variable in the consequent part of each rule. Finally, defuzzification is performed that involves weighting and combining a number of fuzzy sets resulting from the fuzzy inference process in a calculation, which gives a single crisp value for each output. Using a proposed tool, the Web-based fuzzy expert system can be developed simply and takes short time and effort. The proposed tool is evaluated by using the diagnosis domain of air pollution diseases.

References
  1. C. S. Krishnamoorthy; S. Rajeev. (1996). Artificial Intelligence and Expert Systems for Engineers. CRC Press, CRC Press LLC.
  2. B. Ruiz-Mezcua, A. Garcia-Crespo, J. L. Lopez-Cuadrado & I. Gonzalez-Carrasco. (2011). An expert system development tool for non AI experts. Expert Systems with Applications 38 (2011) 597–609.
  3. R. Grove. (2000). Internet-based expert systems, Expert Systems, July 2000, Vol. 17, No. 3, 129-136.
  4. D. Yanqing. (2009). Web-Based Expert Systems. Encyclopedia of Information Science and Technology, Second Edition. IGI Global.
  5. Hogo, M. , Fouad, K. & Mousa, F. (2010). Web-Based Expert System for Civil Service Regulations: RCSES. International Journal of Computer Science and Information Security, IJCSIS, Vol. 6, No. 3, pp. 007-016.
  6. Kumar, S. & Mishra, R. (2010). Expert systems and services. The Knowledge Engineering Review, Vol. 25:2, 167–198, DOI: 10. 1017/S0269888910000020. Cambridge University Press.
  7. Grove, F. (2000). Design and development of knowledge-based systems on the web. In Proceedings of ISCA 2000: 9th International Conference on Intelligence Systems: Artificial Intelligence Applications for the New Millennium, Louisville, KY, USA, 147–150.
  8. Shang, Y. (2005). Expert Systems. In: The Electrical Engineering Handbook, 2005, Pages 367-377, Academic Press, Elsevier.
  9. Zadeh, L. A. (1965). Fuzzy sets, Information and Control 8(3):338–353.
  10. Dubey, S. , Pandey, R. K. & Gautam, S. S. (2013). Literature Review on Fuzzy Expert System in Agriculture. International Journal of Soft Computing and Engineering (IJSCE), Volume-2, Issue-6.
  11. Siler, W. & Buckley, J. (2005). Fuzzy Expert Systems and Fuzzy Reasoning. John Wiley & Sons, Inc.
  12. Ruiz-Mezcua, B. , Garcia-Crespo, A. , Lopez-Cuadrado, J. & Gonzalez-Carrasco, I. (2011). An expert system development tool for non AI experts. Expert Systems with Applications 38 (2011) 597–609. Elsevier Ltd.
  13. KOLLU, K. (2011). Prototype of an intelligent tutoring system using the java expert system shell. Master of science engineering. Electrical & Computer Engineering Department, Temple University.
  14. Buydens, L. , Leeuwen, H. & Wehrens, R. (1993). 4: Expert-System-Development Tools. Data Handling in Science and Technology. Volume 13, 1993, Pages 121–151. Intelligent software for chemical analysis. Elsevier B. V.
  15. Yun, W. & Chan, L. (2009). Semantic Web-based Seismic Disaster management Expert System. 978-1-4244-4507-3/09. IEEE.
  16. Prcela, M. , Gamberger, D. & Jovic, A. (2008). Semantic Web Ontology Utilization for Heart Failure Expert System Design. Organizing Committee of MIE 2008. IOS Press.
  17. Sahin, S. , Tolun, M. & Hassanpour, R. (2012). Hybrid expert systems: A survey of current approaches and applications. Expert Systems with Applications 39 (2012) 4609–4617. Elsevier Ltd.
  18. Dunstan, N. (2008). Generating domain-specific web-based expert systems. Expert Systems with Applications 35 (2008) 686–690. Elsevier Ltd.
  19. Chitra, D. , Ahmad, A. & Mahsa, A. (2005). Design a Tool for Construction of Unique Knowledge Base For Expert systems. Proceedings of the 18th International Conference on Systems Engineering (ISCEng'05). 0-7695-2359-5/05, IEEE.
  20. Jain, M. , Jain, A. & Srinivas, M. (2008). A Web based Expert System Shell for Fault Diagnosis and Control of Power System Equipment. 2008 International Conference on Condition Monitoring and Diagnosis, Beijing, China, April 21-24, 2008. 978-1-4244-1622-6/08, IEEE.
  21. Rafe, V. & Goodarzi, M. (2013) . A Novel Web-based Human Advisor Fuzzy Expert System. Journal of Applied Research and Technology. Vol. 11, February 2013.
  22. Muñoz-Velascoa, E. & Burriezab, A. & Ojeda-Aciegoa , M. (2014). A logic framework for reasoning with movement based on fuzzy qualitative representation. Fuzzy Sets and Systems 242 (2014) 114–131.
  23. Chevalier, R. , Hoogenboom, G. , McClendon R. , Paz, J. (2012). A web-based fuzzy expert system for frost warnings in horticultural crops. Environmental Modelling & Software 35 (2012) 84-91.
  24. Abdullah, A. , Zakaria, Z. & Mohammad, N. (2011). Design and Development of Fuzzy Expert System for Diagnosis of Hypertension. Second International Conference on Intelligent Systems, Modelling and Simulation. 978-0-7695-4336-9/11, IEEE.
  25. Pitchipoo. p, Venkumar. P & Rajakarunakaran. S. (2012). Development of Fuzzy Expert System for Supplier Evaluation and Selection. IEEE-International Conference On Advances In Engineering, Science And Management (lCAESM -2012) March 30, 31, ISBN: 978-81-909042-2-3, IEEE.
  26. Nofal. M. & Fouad, K. (2014). Developing Web-Based Semantic Expert Systems. IJCSI International Journal of Computer Science Issues, Vol. 11, Issue 1, No 1, January 2014.
  27. Zeid, I. & Gupta, S. (2000). Disassembly knowledge representation via XML. Paper 39. http://hdl. handle. net/2047/d1000313.
  28. Yan, S. , Yun, L. , Luan, L. & C. Ling. (2009), A Personalized Search Results Ranking Method Based on WordNet, 2009 Sixth International Conference on Fuzzy Systems and Knowledge Discovery, 978-0-7695-3735-1/09, IEEE.
  29. Fellbaum, C. (2010). WordNet. In: R. Poli et al. (eds. ), Theory and Applications of Ontology: Computer Applications, DOI 10. 1007/978-90-481-8847-5_10, Springer Science+Business Media B. V.
  30. Deshmukh, P. & Ali, M. (2014). Overview of Xml based Knowledge Representation using Scripts. International Journal of Advance Research in Computer Science and Management Studies. Volume 2, Issue 1, January 2014.
  31. GAINFS, B. (1976). Foundations of fuzzy reasoning. International Journal Man-Machine Studies (1976) 8, 623-668.
  32. Pappis, C. (2005). FUZZY REASONING. In: Introductory Tutorials in Optimization and Decision Support Techniques. pp 437-474. Springer US.
  33. Millette, L. (2012). IMPROVING THE KNOWLEDGE-BASED EXPERT SYSTEM LIFECYCLE. Master of Science in Computer and Information Sciences. UNIVERSITY OF NORTH FLORIDA SCHOOL OF COMPUTING.
  34. Forsythe, D. , and B. Buchanan. "Knowledge acquisition for expert systems: some pitfalls and suggestions," Systems, Man and Cybernetics, IEEE Transactions, 19, 3, pp. 435-442.
  35. B. F. Leao and A. F. Rocha. (1990). Proposed methodology for knowledge acquisition: a study on congenital heart disease diagnosis. Methods Inform. Medicine 29:3(M-0).
  36. BUCHANAN, "Constructing an expert system. " In F. Hayes-Roth, D. Waterman, and D. Lenat, eds. Building Expert Systems, Reading, MA: Addison-Wesley, 1983.
  37. Szyma´nski, J. & Duch, W. (2012). Annotating Words Using WordNet Semantic Glosses. ICONIP 2012, Part IV, LNCS 7666, pp. 180–187, 2012. Springer-Verlag Berlin Heidelberg.
  38. Qasim, I. & Khan, S. (2009). Semantic Mapping between Global and Source Ontology using WordNet. Computer, Control and Communication, 2009. IC4 2009. IEEE.
  39. Amalanathan, A. , Shanmugam. S, Senthilnathan. M & Harikumar. S. (2012). Semantic Annotations for Customizing Geographical Maps Based on WordNet. Procedia Technology 4 ( 2012 ) 375 – 383.
  40. M. C. A. Klein, J. Broekstra, D. Fensel, V. Harmelen, and I. Horrocks, "Ontologies and Schema Languages on the Web. Spinning the Semantic Web", 2003, pp: 95-139. MIT Press, IEEE.
  41. Gomez-Perez, A. ; Fac. de Inf. , Univ. Politecnica de Madrid, Spain ; Corcho, O. (2002). Ontology languages for the Semantic Web. Intelligent Systems, Page: 54 - 60 , IEEE (Volume:17 , Issue: 1 ).
  42. Liebowitz, J. (1999). The Handbook of APPLIED EXPERT SYSTEMS. VámosChapter, T. Chapter 3: Knowledge Representation. CRC Press LLC.
  43. Boegl, K. , Adlassnig, K. , Hayashi, Y. Rothenfluh, T. Leitich, H. (2004). Knowledge acquisition in the fuzzy knowledge representation framework of a medical consultation system. Artificial Intelligence in Medicine 30 (2004) 1–26.
Index Terms

Computer Science
Information Sciences

Keywords

Fuzzy Expert Systems XML Web-based User Interface.

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