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Transportation System Architecture for Intelligent Management

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Języki publikacji
EN
Abstrakty
EN
The paper is focusing on transportation system architecture for intelligent management, especially in sea transport and transportation technology. Moreover control models of large-scale distributed en­terprises systems and transport active knowledge base management model have been presented.
Twórcy
autor
  • AGH University of Science and Technology, Krakow, Poland
Bibliografia
  • 1 Adler J.L., Blue V.J.: A cooperative multi-agent transportation management and route guidance system. Transportation Research, Part C, v. 10 (5–6), p. 433– 454, 2002.
  • 2 Alavi M., Leidner D. E.: Review: Knowledge management and knowledge management systems: Conceptual foundations and research issues. MIS Quarterly, v.25 (3), p.107–136, 2001.
  • 3 Baina S., Panetto H., Morel G.: New paradigms for a product oriented modeling: Case study for traceability. Computers in Industry, January 2009.
  • 4 Barton R., Thomas A.: Implementation of intelligent systems, enabling integration of SMEs to high-value supply chain networks. Engineering Applications of Artificial Intelli-gence, January 2009.
  • 5 Blanc P., Demongodin I., Castagna P.: A holonic approach for manufacturing execution system design: An industrial ap-plication. Engineering Applications of Artificial Intelli-gence, v. 21 (3), p. 315-330, April 2008.
  • 6 Brennan R.W., Balasubramanian S., Norrie D.H.: A dynamic control architecture for metamorphic control of advanced manufacturing systems. Proceedings of International Con-ference on Intelligent Systems for Advanced Manufactur-ing, Pittsburgh, 1997.
  • 7 Chang L. K., Lee S., Kang I. W.: KMPI: Measuring knowledge management performance. Information and Management, v. 42 (3), p. 469–482, 2005
  • 8 Gray R., Kotz D., Cybenko G., Rus D.: Mobile agents: motiva-tions and state-of-the-art systems. In Bradshaw J. (Ed.), Handbook of Agent Technology. AAAI/ MIT Press, Bos-ton, 2002.
  • 9 Gruber T.R.: A translation approach to portable ontology speci-fications. Knowledge Acquisition, v.5 (2), p. 199–220, 1993.
  • 10 Hernandez J.Z., Ossowski S., Garcia-Serrano A.: Multiagent architectures for intelligent traffic management systems. Transportation Research, Part C, v. 10 (5–6), p. 473–506, 2002.
  • 11 Herve P., Molina A.: Enterprise integration and interoperability in manufacturing systems: trends and issues. Computers in Industry, v. 59 (7), p. 641-646, September 2008.
  • 12 Nof S.Y., Morel G., Monostori L., Molina A., Filip F.: From plant and logistics control to multi-enterprise collaboration. Milestone Report of the Manufacturing & Logistics Sys-tems, IFAC Coordinating Committee, Annual Reviews of Control 30, 2008.
  • 13 Irma B., Rajiv S.: Organizational knowledge management: A contingency perspective. Journal of Management Informa-tion Systems, v.18 (1), p. 23–55, 2001.
  • 14 Lange D.B., Oshima M.: Seven good reasons for mobile agents. Communications of the ACM, v. 42 (3), p. 88–89, 1999.
  • 15 Le Duigou J., Bernard A., Perry N., Delplace J.C.: Global ap-proach for technical data management. Application to ship equipment part families. CIRP Journal of Manufacturing Science and Technology, v. 1 (3), p. 185-190, 2009.
  • 16 Malhotra Y.: Enabling knowledge exchanges for e-business communities. Information Strategy, v.18 (3), p.26–31, 2002.
  • 17 McFarlane D., Sarma S., Chirn J.L., Wong C.Y., Ashton K.: Auto ID systems and intelligent manufacturing control. En-gineering Applications of Artificial Intelligence, v. 16 (4), p. 365–376, 2003.
  • 18 Morel G., Valckenaers P., Faure J.M., Pereira C.E., Dietrich C.: Manufacturing Plant Control Challenges and Issues. Computers in Industry, v.15 (11), p. 1321–1331, 2007.
  • 19 Noy N.F., McGuinness D.L.: Ontology Development 101: A Guide to Creating Your First Ontology, 2001, Last accessed 15 April, 2007 from http://www.lsi.upc.edu/~bejar/ aia/aia-web/ontology101.pdf
  • 20 Oztemel E., Tekez E.K.: A general framework of a Reference Model for Intelligent Integrated Manufacturing Systems (REMIMS). Engineering Applications of Artificial Intelli-gence, January 2009.
  • 21 Panetto H.: Towards a classification framework for interopera-bility of enterprise applications. International Journal of CIM, v. 20, p. 727–740, December 2007.
  • 22 Pannequin R., Morel G., Thomas A.: The performance of prod-uct-driven manufacturing control: An emulation-based benchmarking study. Computers in Industry, January 2009.
  • 23 Penttila H.: Describing the changes in architectural information technology to understand design complexity and free-form architectural expression. ITCON 11, Special Issue the Ef-fects of CAD on Building Form and Design Quality, p. 395– 408, 2006.
  • 24 Savvas I., Bassiliades N.: A process-oriented ontology-based knowledge management system for facilitating operational procedures in public administration. Expert Systems with Applications, v. 36 (3), Part 1, p. 4467-4478, April 2009.
  • 25 Smalko Z., Szpytko J.: The Man -Machine Type Systems Mod-eling Approach. Journal of KONBIN, 5(8), p. 175-192, 2008.
  • 26 Studer R., Benjamins V.R., Fensel D.: Knowledge engineering: principles and methods. Data & Knowledge Engineering, v. 25 (1–2), p. 161–197, 1998.
  • 27 Succar B.: Building information modeling framework: A re-search and delivery foundation for industry stakeholders. Automation in Construction, v.18 (3), p.357-375, May 2009.
  • 28 Szpytko J., Kocerba A.: Safety and reliability of dispersed transport devices -selected problems. ITE -PIB, Kraków -Radom, 2008.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-39157ba0-ba5a-459c-8f61-ce2a394f229b
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