Methodologies and Applications of Artificial Intelligence in Systems Engineering

(1) Awatef K. Ali Mail (National Telecommunications Institute, Egypt)
(2) * MagdiSadek Mostafa Mahmoud Mail (Control and Instrumentation Engineering Department, KFUPM, Dhahran, Saudi Arabia, Saudi Arabia)
*corresponding author

Abstract


This paper presents an overview of the methodologies and applications of artificially intelligent systems (AIS) in different engineering disciplines with the objective of unifying the basic information and outlining the main features. These are knowledge-based systems (KBS), artificial neural networks (ANN), and fuzzy logic and systems (FLS). To illustrate the concepts, merits, and demerits, a typical application is given from each methodology. The relationship between ANN and FLS is emphasized. Two recent developments are finally presented: one is intelligent and autonomous systems (IAS) with particular emphasis on intelligent vehicle and highway systems, and the other is the very large scale integration (VLSI) systems design, verification, and testing.


Keywords


Knowledge-Based Systems; Artificial Neural Networks; Fuzzy Logic and Systems

   

DOI

https://doi.org/10.31763/ijrcs.v2i1.532
      

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References


[1] R. Penrose, The Emperor’s New Mind, Oxford University Press, Oxford, 1989, https://books.google.co.id/books?id=FZduoOiOtyMC.

[2] F. D. Peat, Artificial Intelligence: How Machines Think, Simon & Schuster, New York, 1985, https://books.google.co.id/books?id=mX5WAAAAYAAJ.

[3] S. Russell and P. Norvig, Artificial Intelligence, Prentice-Hall, New York, 1999.

[4] A. Caswsey, The Essence of Artificial Intelligence, Prentice-Hall, New York, 1998, https://books.google.co.id/books?id=EAsGAsSTCE8C.

[5] C. Manning and Hinrich Schutze, Foundations of Statistical Natural Language Processing, MIT Press, Cambridge, MA, May 1999, https://books.google.co.id/books?id=3qnuDwAAQBAJ.

[6] A. Barr and E. A. Feigenbaum (Editors), The Handbook of Artificial Intelligence: Volume 1, Volume 1, William Kaufmann Inc., CA, 1981, https://books.google.co.id/books?id=3oviBQAAQBAJ.

[7] G. F. Luger and W. A. Stubblefield, Artificial Intelligence and The Design of Expert Systems, Benjamin/Cummings, CA, 1989, https://books.google.co.id/books?id=IBQAAAAMAAJ.

[8] S. E. Umbaugh, Computer Vision and Image Processing, Prentice-Hall, New York, 1998, https://books.google.co.id/books?id=9GChGQAACAAJ.

[9] L. A. Zadeh, “Fuzzy Sets,” Information and Control, vol. 8, 1965, pp. 338-353, https://doi.org/10.1016/S0019-9958(65)90241-X.

[10] J. P. Ignizio, Introduction to Expert Systems: The Development and Implementation of Rule-based Expert Systems, McGraw-Hill, New York, 1991, https://books.google.co.id/books?id=obJQAAAAMAAJ.

[11] C. L. Dym, and R. E. Levitt, Knowledge-Based Systems in Engineering, McGraw Hill, New York, 1991, https://books.google.co.id/books?id=joVRAAAAMAAJ.

[12] N. Wiener, Cybernetics: or Control and Communication in the Animal and the Machine, MIT Press, Cambridge, MA, 1948, https://books.google.co.id/books?id=mP1XxwEACAAJ.

[13] F. Rosenblatt, "The Perceptron: A Probabilistic Model for Information Storage and Organization in the Brain," Psychological Review, vol. 65, pp. 386-408, 1958, https://doi.org/10.1037/h0042519.

[14] K. J. Hunt, D. Sbarbaro, R. Zbikowaski and P. J. Gawthrop, "Neural Networks for Control Systems-A Survey," Automatica, vol. 28, no. 6, pp. 1083-1112, 1992, https://doi.org/10.1016/0005-1098(92)90053-I.

[15] IEEE Control Systems Magazine, Special Issue on Neural Networks, volumes 8-10, 1988 -1990, https://books.google.co.id/books?id=hdA2mgEACAAJ.

[16] W. T. Miller, R. S. Sutton and P. J. Werbos, Neural Networks for Control, MIT Press, Cambridge, MA, 1995, https://books.google.co.id/books?id=prjMtIr_yT8C

[17] W. T. Miller, R. S. Sutton and P. J. Werbos, Neural Networks for Control, MIT Press, Cambridge, MA, 1990.

[18] G. Carpenter, M. Cohen and S. Grossberg, “Computing with Neural Networks,” Science, vol. 235, pp. 1226-1227, 1987, https://www.science.org/doi/pdf/10.1126/science.3823881.

[19] M. Arbib and L. Hanson, Vision Brain and Cooperative Computation, MIT Press, Cambridge, MA, 1988, https://dl.acm.org/doi/abs/10.5555/26803.26804.

[20] W. J. Daunicht, ”Defanet-A Deterministic Approach to Function Approximation by Neural Networks,” IEEE Int. Joint Conference on Neural Networks, IJCNN’90, 1990, pp. 161-164.

[21] T. Kohone, ”Self-Organization and Associative Memory,” Springer-Verlag, Berlin, 1987, https://link.springer.com/book/10.1007/978-3-662-00784-6

[22] J. J. Hopfield, ”Neurons with Graded Response have Collective Computational Properties like those of Two-State Neurons,” Proc. of the National Academy of Sciences, vol. 81, pp. 3088-3092, 1984, https://doi.org/10.1073/pnas.81.10.3088.

[23] H. Rahmanifard, T. Plaksina, "Application of artificial intelligence techniques in the petroleum industry: a review," Artif. Intell. Rev., 2018, https://doi.org/10.1007/s10462-018-9612-8.

[24] O. Araque, I. Corcuera-Platas, J. F. Sanchez-Rada, C. A. Iglesias, ”Enhancing deep learning sentiment analysis with ensemble techniques in social applications,” Expert Syst. Appl., vol. 77, 2017, https://doi.org/10.1016/j.eswa.2017.02.002.

[25] M. Jahnavi, ”Introduction to Neural Networks, Advantages and Applications,” Towards Data Science, 2017, https://towardsdatascience.com/introduction-to-neural-networks-advantages-and-applications-96851bd1a207.

[26] S. B. Kotsiantis, “Supervised machine learning: a review of classification techniques,” Informatica, vol. 31, no. 3, pp. 249–268, 2007, https://www.informatica.si/index.php/informatica/article/view/148.

[27] L. Zhang, S. Wan, B., and Liu, “Deep Learning for Sentiment Analysis: A Survey,” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 8, no. 4, 2018, https://doi.org/10.1002/widm.1253.

[28] M. Gheisari, G. Wang, M. Z. A. Bhuiyan, “A survey on deep learning in big data,” 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), 2017, https://doi.org/10.1109/CSE-EUC.2017.215.

[29] D. E. Rumelhart, and J. L, McClelland (Editors), ”Parallel Distributed Processing: Explorations in the Microstructures of Cognition vol. I: Foundations,” MIT Press, Cambridge, 1986, https://doi.org/10.7551/mitpress/5236.001.0001.

[30] R. S. Scalero and N. Teoedelenlioglu, ”A Fast Algorithm for Neural Networks,” IEEE Int. Joint Conference on Neural Networks, IJCNN’90, 1990, pp. 70-74.

[31] Hinton, Geoffrey & Osindero, Simon & Teh, Yee-Whye, “A Fast Learning Algorithm for Deep Belief Nets. Neural computation,” Neural Computation, vol. 18, pp. 1527–1554, 2006, https://doi.org/10.1162/neco.2006.18.7.1527.

[32] V. S. Dave, K. Dutta, “Neural network-based models for software effort estimation: a review,” Artif. Intell. Rev., vol. 42, no. 2, pp. 295-307, 2014, https://doi.org/10.1007/s10462-012-9339-x.

[33] S. Haykin, Neural Networks: A Comprehensive Foundation, Prentice-Hall, New York, 1999, https://books.google.co.id/books?id=bX4pAQAAMAAJ.

[34] T. Soderstrom and P. Stocia, System Identification, Prentice Hall, New York, 1989, https://books.google.co.id/books?id=X_xQAAAAMAAJ.

[35] M. J. Willis, C. Di Massimo, G. A. Montague, M. T. Tham and A. J. Morris, ”On Artificial Neural Networks in Process Engineering,” Proc. IEE Part D., vol. 138, 1991, pp. 256 266, https://doi.org/10.1049/ip-d.1991.0036.

[36] K. S. Narendra and K. Parthasarathy, ”Identification and Control of Dynamical Systems using Neural Networks,” IEEE Trans. Neural Networks, vol. 1, no. 1, pp. 4-27, 1990, https://doi.org/10.1109/72.80202.

[37] K. S. Narendra, ”Neural networks for control theory and practice,” in Proceedings of the IEEE, vol. 84, no. 10, pp. 1385-1406, Oct. 1996, https://doi.org/10.1109/5.537106.

[38] B. Buchanan and E. Shortliffe, Rule-Based Expert Systems, Addison-Wesley, Reading, Mass., 1984, https://books.google.co.id/books?id=0uZQAAAAMAAJ.

[39] L. Brownston, R. Farrell, E. Kent and N. Martin, Programming Expert Systems in OPS5: An Introduction to Rule-Based Programming, Addison-Wesley, Reading, Mass., 1985, https://books.google.co.id/books?id=9_2yAAAAIAAJ.

[40] R. Fikes and T. Kehler, ”The Role of Frame-Based Representation in Reasoning,” Comm. ACM, vol. 28, 1985, pp. 904-920, https://doi.org/10.1145/4284.4285.

[41] P. Hirsch, M. Meier, S. Snyder and Stillman, ”Interfaces for Knowledge Builder’s Control Knowledge and Application-Specific Procedures,” IBM J. Research and Development, vol. 30, 1986, pp. 29-38, https://doi.org/10.1147/rd.301.0029.

[42] M. Stefik, D. G. Borow, S. Mittal and L. Conway, ”Knowledge Programming in LOOPS: Report on an Experimental Course,” The Artificial Intelligent Magazine, vol. 4, no. 3, pp. 3-18, 1983, https://ojs.aaai.org//index.php/aimagazine/article/view/400.

[43] R. H. Michaelson, D. Michie and A. Boulanger, ”The Technology of Expert Systems,” Byte, vol. 10, 1985, pp. 303-312.

[44] E. H. Mamdani, ”Applications of Fuzzy Algorithms for Simple Dynamic Plant,” Proc. IEE, vol. 121, 1974, pp. 1585-1588, https://doi.org/10.1049/piee.1974.0328.

[45] M. Jamshidi, N. Vadiee and T. J. Ross (Editors), Fuzzy Logic and Control: Software and Hardware Applications, Prentice Hall, New York, 1993, https://books.google.co.id/books?id=fN9SAAAAMAAJ.

[46] T. J. Ross, Fuzzy Logic with Engineering Applications, John Wiley & Sons, 2016, https://books.google.co.id/books?id=ijsbDQAAQBAJ.

[47] J. T. Spooner and K. M. Passino, “Stable Adaptive Control using Fuzzy Systems and Neural Networks,” IEEE Trans. Fuzzy Systems, vol. 4, pp. 339-359, 1996, https://doi.org/10.1109/91.531775.

[48] R. F. Stengel, “Toward Intelligent Flight Control,” IEEE Trans. Systems Man and Cybernetics, vol. 23, pp. 1699-1717, 1993, https://doi.org/10.1109/21.257764

[49] B. Kosko, Neural Networks and Fuzzy Systems, Prentice Hall, New York, 1992, https://books.google.co.id/books?id=fbJQAAAAMAAJ.

[50] K. M. Passino, Intelligent Control for Autonomous Systems, IEEE Spectrum, vol. 32, no. 6, pp. 55-62, 1995, https://doi.org/10.1109/6.387144.

[51] K. P. Valavanis and G. N. Saridis, Intelligent Robotic Systems: Theory Design and Applications, Springer Science & Business Media, 2012, https://doi.org/10.1007/978-1-4615-3568-3.

[52] D. White and D. Sofge (Editors), Handbook of Intelligent Control: Neural Fuzzy and Adaptive Approaches, Van Nostrand Reinhold, New York, 1992, https://books.google.co.id/books?id=qEeAQAAIAAJ.

[53] M. C. McFarland and T. J. Kowalski, “Incorporating Bottom-up Design Into Hardware Design,” IEEE Trans. CAD, vol. 9, no. 9, pp. 938-950, Sept. 1990, https://doi.org/10.1109/43.59070.

[54] F. Brewer, et al., “CHIPPE: A System for Constraint Driven Behavioral Synthesis,” IEEE Trans. CAD, 9, pp. 681-695, July 1990, https://doi.org/10.1109/43.55208.

[55] M. S. Abadir, M. A. Breuer, “A Knowledge-based System for Designing Testable VLSI Circuits,” IEEE Design and Test, 2, pp.56-68, Aug., 1985, https://doi.org/10.1109/MDT.1985.294746.

[56] A. J. Wilkinson, “MIND: An inside Look at an Expert System for Electronic Diagnosis,” IEEE Design and Test, vol. 2, no. 4, pp. 69-77, 1985, https://doi.org/10.1109/MDT.1985.294748.

[57] R. Davis, “Diagnostic Reasoning Based on Structure and Behavior,” Art. Intell., 24, pp. 347-410, 1984, https://doi.org/10.1016/B978-0-444-87670-6.50010-8.

[58] H. Tolba and A. K. Ali, “Fault Diagnosis of Digital Circuits Using CSP Techniques,” 4th IEEE International Conf. On Electrical Circuits and Systems ICECS, Dec. 1997.

[59] S. J. Cosgrove and G. Musgrave, “Test Generation within an Expert System Environment,” IEE Proc. –E (Computers and Digital Techniques), vol. 138, no. 1, pp. 36-40, Jan. 1991, https://doi.org/10.1049/ip-e.1991.0005.

[60] M. J. Bending, “HITEST: A Knowledge-based test Generation System,” IEEE Design and Test, 1, pp.83-92, May, 1984, https://doi.org/10.1109/MDT.1984.5005617.


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International Journal of Robotics and Control Systems
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