Abstract
An intelligent information system based on the use of LPR formalism , integrating basic features such as access to knowledge, reasoning, search, and expert advice, is presented. This system has been implemented and tested in the Department of Computer Science at the AGH University of Science and Technology. The methodology for the system use has been exemplified in the area of the foundry industry by the selection and conversion of technologies for making products from ADI.
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References
Abramowicz, W., Bukowska, E., Dzikowski, J., Filipowska, A., Kaczmarek, M.: Semantically enabled experts finding system ontologies. Reasoning approach and web interface design. In: Proceedings of the 15th East-European Conference on Advances in Databases and Information Systems, pp. 1–10 (2011)
Al-Kanhal, T., Abbod, M.: Multi-agent system for dynamic manufacturing system optimization. In: Lecture Notes in Computer Science, vol. 5103, pp. 634–643 (2008)
Alkharouf, N.W., Michalski, R.S.: Multistrategy task-adaptive learning using dynamically interlaced hierarchies. In: Michalski, R.S., Wnek, J. (eds.) Proceedings of the of 3rd International Workshop on Multistrategy Learning, pp. 112–130 (1996)
Althoff, K., Bach, K., Deutch, J., Hanft, A., Manz, J., Muller, T., Newo, R., Reichle, M., Schaaf, M., Weis, K.: Collaborative multi-expert-systems realizing knowledge-lines with case factories and distributed learning systems. In: Proceedings of the 3rd Workshop on Knowledge Engineering and Software Engineering (2007)
Boehm-Davis, D., Dontas, K., Michalski, R.S.: Plausible reasoning: an outline of theory and the validation of its structural properties. In: Intelligent Systems: State of the Art and Future Directions. North Holland (1990)
Dontas, K., Boehm-Davis, D., Michalski, R.S.: A validation and exploration of the Collins-Michalski theory of plausible reasoning. Reports of the Machine Learning and Inference Laboratory, George Mason University (1990)
Esterline, A.C., Wiriyacoonkasem, S.: Adaptive learning expert systems. In: Proceedings of the IEEE Southeastcon, pp. 445–448 (2000)
Hieb, M.R., Michalski, R.S.: Multitype inference in multistrategy task-adaptive learning: dynamic interlaced hierarchies. Reports of the Machine Learning and Inference Laboratory, George Mason University (1993a)
Hieb, M.R., Michalski, R.S.: A knowledge representation system based on dynamically interlaced hierarchies: basic ideas and examples. Reports of the Machine Learning and Inference Laboratory, George Mason University (1993b)
Ho Chung, L., Ah Hwee, T., Hoon Heng, T., Boon Toh, L.: Connectionist expert system with adaptive learning capability. Knowledge and Data Engineering IEEE Transactions 3(2), 200–207 (1991)
Klochkova, K.V., Petrovich, S.V., Simonova, L.A., Yusupov, L.R.: Stages of vermicular cast iron properties modeling in the intelligent design system. In: IOP Conference Series: Materials Science and Engineering, vol. 86 (2015)
Kluska-Nawarecka, S., Nawarecki, E., Śnieżynski, B., Wilk-Kołodziejczyk, D.: The recommendation system knowledge representation and reasoning procedures under uncertainty for metal casting. Metalurgija 54, 263–266 (2015)
Legień, G., Śnieżyński, B., Wilk-Kołodziejczyk, D., Kluska-Nawarecka, S., Nawarecki, E., Jaśkowiec, K.: Expert system with web interface based on logic of plausible reasoning. In: Proceedings of the Database and Expert Systems Applications, pp. 13–20. Springer International Publishing (2015)
Ma, X., Li, Z., Achenie, L.E.K., Xin, H.: Machine-learning-augmented chemisorption model for CO2 electroreduction catalyst screening. J. Phys. Chem. Lett. 6(18), 3528–3533 (2015)
Michalski, R.S.: Inferential theory of learning: developing foundations for multistrategy learning. In: Michalski, R.S. (ed.) Machine Learning: A Multistrategy Approach, vol. IV, pp. 1–48. Morgan Kaufmann Publishers (1994)
Neuhauser, N., Michalski, A., Cox, J., Mann, M.: Expert system for computer-assisted annotation of MS/MS spectra. Mol. Cell. Proteomics 11(11), 1500–1509 (2012)
Nieves, J., Santos, I., Bringas, P.G., Penya, Y.K.: Machine-learning-based defect prediction in high-precision foundry production. In: Becker, L.M. (ed.) Structural Steel and Castings: Shapes and Standards. Nova Science Publishers (2009)
Parada, W., Lustofin, M.: System ekspertowy z możliwością uzupełniania wiedzy oparty o logikę wiarygodnego rozumowania. Master thesis, AGH University of Science and Technology (2012). (in Polish)
Santos, I., Javier Nieves, I., Penya, Y.K., Bringas, P.G., Omatu, S.: Optimising machine-learning-based fault prediction in foundry production. In: Part II. LNCS, vol. 5518, pp. 553–560. Springer, Heidelberg (2009)
Śnieżyński, B.: Proof searching algorithm for the logic of plausible reasoning. In: Kłopotek, M., et al. (eds.) Intelligent Information Processing and Web Mining. Advances in Soft Computing, pp. 393–398. Springer, Heidelberg (2003)
Śnieżyński, B., Kluska-Nawarecka, S., Nawarecki, E., Wilk-Kołodziejczyk, D.: Intelligent information system based on logic of plausible reasoning. Issues Chall. Artif. Intell. 559, 57–74 (2014)
Trappey, A.J.C., Tung-Hung, L., Li-Dien, F.: Development of an intelligent agent system for collaborative mold production with RFID technology. Robot. Comput. Integr. Manuf. 25, 42–56 (2009)
Verhodubs, O., Grundspenkis, J.: Towards the semantic web expert system. Sci. J. Riga Tech. Univ. 11, 116–123 (2011)
Acknowledgements
This paper is based upon work supported by the The National Centre for Research and Development (LIDER/028/593/L-4/12/NCBR/2013) and No. 820/N-Czechy/2010/0.
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Nawarecki, E., Kluska-Nawarecka, S., Wilk-Kołodziejczyk, D., Śnieżynski, B., Legień, G. (2018). Integrated Multi-functional LPR Intelligent Information System. In: Hippe, Z., Kulikowski, J., Mroczek, T. (eds) Human-Computer Systems Interaction. Advances in Intelligent Systems and Computing, vol 551. Springer, Cham. https://doi.org/10.1007/978-3-319-62120-3_12
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