CFP last date
20 January 2025
Reseach Article

Process Modelling from Insurance

by P.V.Kumaraguru, Dr.S.P.Rajagopalan
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 38 - Number 6
Year of Publication: 2012
Authors: P.V.Kumaraguru, Dr.S.P.Rajagopalan
10.5120/4693-6835

P.V.Kumaraguru, Dr.S.P.Rajagopalan . Process Modelling from Insurance. International Journal of Computer Applications. 38, 6 ( January 2012), 25-29. DOI=10.5120/4693-6835

@article{ 10.5120/4693-6835,
author = { P.V.Kumaraguru, Dr.S.P.Rajagopalan },
title = { Process Modelling from Insurance },
journal = { International Journal of Computer Applications },
issue_date = { January 2012 },
volume = { 38 },
number = { 6 },
month = { January },
year = { 2012 },
issn = { 0975-8887 },
pages = { 25-29 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume38/number6/4693-6835/ },
doi = { 10.5120/4693-6835 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:24:51.984049+05:30
%A P.V.Kumaraguru
%A Dr.S.P.Rajagopalan
%T Process Modelling from Insurance
%J International Journal of Computer Applications
%@ 0975-8887
%V 38
%N 6
%P 25-29
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Converting the mysterious mind process in to a most tangible, structured and understandable, process model is not only a great challenge of the day but also the need of the hour for many industries. Since 2005 the evolution of modern business industry has taken one step forward from business intelligence to business optimization. In the resent past all the business industries are in search of the means and ways to handle the data explosion of the digital universe. Machine learning and data mining are the only solutions to enable the business industries, not only to tackle the data explosion but also to convert the vital data to optimize the potential business resource. This paper has made an attempt to convert the event logs of the insurance process in to process model using petri net.

References
  1. H. Amin, A. R. Khan, Acquiring Knowledge for Evaluation of Teachers ‘Performance in Higher Education – using a Questionnaire. International Journal of Computer Science and Information Security (IJCSIS) 2(2009), 180-187.
  2. Daniel Kahneman, P. S. (1982). Judgment under uncertainty Heuristics and biases . New York: Cambridge University Press.
  3. S.Ammar, W.Duncombe, B.Jump, R.Wright, Constructing a fuzzyknowledge-based-system: An application for assessing the financial condition of public schools. Expert Systems with Applications, 27(2004), 349–364.
  4. S.M.Bai, S.M.Chen, A new method for students‘ learning achievement using fuzzy membership functions. In Proceedings of the 11th Conference on artificial intelligence, Kaohsiung, Taiwan, Republic of China. (2006).
  5. D.Biggs, M.Sagheb-Tehrani, Providing developmental feedback to individuals from different ethnic minority groups using expert systems. Expert Systems, 25(2008), 87-97.
  6. A.Berrais, A knowledge-based expert system for earthquake resistant design of reinforced concrete buildings. Expert Systems with Applications, 28 (2005), 519–530.
  7. S.M.Chen, C.H.Lee, New methods for students‘ evaluating using fuzzy sets. Fuzzy Sets and Systems, 104(1999), 209–218.
  8. D.F.Chang, C.M.Sun, Fuzzy assessment of learning performance of junior high school students. In Proceedings of the 1993 first national Symposium on fuzzy theory and applications, Hsinchu, Taiwan, Republic of China, 1993, pp. 1–10.
  9. C. F.Cheung, W.B.Lee, W. M.Wang, K.F.Chu, S.To, A multi-perspective knowledge-based system for customer service management. Expert Systems with Applications, 24(2003), 457–470.
  10. T.T.Chiang, C.M.Lin, Application of fuzzy theory to teaching assessment. In Proceedings of the 1994 second national conference on fuzzy theory and applications, Taipei, Taiwan, Republic of China, 1994, pp. 92–97.
  11. H. K. H.Chow, K.L.Choy, W.B.Lee, F.T.S.Chan, Design of a knowledge-based logistics strategy system. Expert Systems with Applications, 29(2005), 272–290.
  12. J.A.Clark, F.Soliman, A graphical method for assessing knowledge-based systems investments. Logistics Information Management, 12(1999), 63–77.
  13. A.J.Day, A.K.Suri, A knowledge-based system for postgraduate engineering courses. Journal of Computer Assisted Learning, 15(1999), 14–27.
  14. J. Durkin, Application of Expert Systems in the Sciences. OHIO J. SCI. 90 (1990), 171-179.
  15. D.J.Fonseca, G.Uppal, T.J.Greene, A knowledge-based system for conveyor equipment selection. Expert Systems with Applications, 26(2004), 615–623.
  16. M.Hamidullah, Comparisons of the Quality of Higher Educations in Public and Private Sector Institutions, PhD Thesis, University of Arid Agriculture Rawalpindi, PAK, 2005.
  17. H.Iranmanesh, M.Madadi, An Intelligent System Framework for Generating Activity List of a Project Using WBS Mind map and Semantic Network. Proceedings of World Academy of Science, Engineering and Technology. 30 (2008), 338-345.
  18. A.Kazaz, Application of an Expert System on the Fracture Mechanics of Concrete. Artificial Intelligence Review. 19(2003), 177–190.
  19. R.Kumra, R.M.Stein, I.Assersohn, Assessing a knowledgebase approach to commercial loan underwriting. Expert Systems with Applications, 30(2006), 507–518.
  20. S. H. Liao, Problem solving and knowledge inertia. Expert Systems with Applications, 22(2002), 21–31.
  21. J.Ma, D.Zhou, Fuzzy set approach to the assessment of student- centered learning. IEEE Transactions on Education, 43(2000), 237– 241.
  22. W.W.Melek, A.Sadeghian, A theoretic framework for intelligent expert systems in medical encounter evaluation. Expert Systems, 26(2009), 87-97.
  23. M.Naeemullah, Designing a Model for Staff Development in Higher Education of Pakistan, PhD Thesis, University of Arid Agriculture Rawalpindi, PAK, 2005.
  24. T.T.Pham, G.Chen, Some applications of fuzzy logic in rules-based expert systems, Expert System, 19(2002), 208-223.
  25. J.Pomar,C.Pomar, A knowledge-based decision support system to improve sow farm productivity. Expert Systems with Applications, 29(2005), 33–40.
  26. W. K.Wang, A knowledge-based decision support system for measuring the performance of government real estate investment. Expert Systems with Applications, 29(2005), 901–912.
  27. W. K.Wang, H.C.Huang, M.C.Lai, Design of a knowledgebase performance evaluation system: A case of high-tech state-owned enterprises in an emerging economy. Expert Systems with Applications. doi:10.1016/j.eswa.2007.01.032.
  28. W.Wen, W. K.Wang, T.H.Wang, A hybrid knowledge based decision support system for enterprise mergers and acquisitions. Expert Systems with Applications, 28(2005a), 569–582.
  29. W.Wen, W.K.Wang, C.H.Wang, A knowledge-based intelligent decision support system for national defence budget planning. Expert Systems with Applications, 28(2005b), 55–66.
  30. M.H.Wu, Research on applying fuzzy set theory and item response theory to evaluate learning performance. Master Thesis, Department of Information Management, Chaoyang University of Technology, Wufeng, Taichung County, Taiwan, Republic of China,2003.
  31. M.R.Shen, Y.Y.Tang, Z.T.Zhang, The intelligent assessment system in Web-based distance learning education. 31st Annual Frontiers in Education Conference, 1(2001), TIF-7-TIF-11.
  32. N.H.Yim, S.H.Kim, H.W.Kim, K.Y.Kwahk, Knowledge based decision making on higher level strategic concerns: System dynamics approach. Expert Systems with Applications, 27(2004), 143–158.
  33. L.A. Zadeh, Fuzzy sets. Inform. and control, 8 (1965), 338-353.
  34. L.A.Zadeh, The concept of a linguistic variable and its application to appropriate reasoning. Information sciences, 8(1975), 43-80.
  35. Wil M.P. Van der Aalst, 2010,Process Mining, Springer
  36. W.M.P. Van der Aalst 1998 The applications of Petri Nets to wotk flow management , The journal of Circuits, Systems and computers
  37. W.M.P. Van der Aalst and K.M.Van Hee. Workflow Management: Models, Methods , and system. MIT press, Cambridge, MA, 2002.
  38. S.Kumaran and K.Raja, Modeling and simulation of Projects with Petri Nets. American journal of applied Sciences, 2008.
  39. A.J.M.M Weijters and W.M.P Van der Aalst, Process Mining : 2001 Discovering workflow Models from Event based Data, 13th Belgium- Netherlands Conference on Artificial intelligence(BNAIC 2001).
  40. W.M.P van der Aalst A.J.M.M. Weijters, and L. Maruster. 2004, Work flow Mining: Discovering process models from Event Logs. IEEE Transactions on Knowledge and Data Engineering
  41. H.Ananathakrishnan,V.A.Pai 2004, Motor Insurance, Insurance Institute of India.
Index Terms

Computer Science
Information Sciences

Keywords

Business intelligence Data explosion Digital universe Event logs process model four eye a-priori token game stochastic