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An FPGA-Based Smart Classifier for Decision Support Systems

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Book cover Intelligent Distributed Computing VII

Part of the book series: Studies in Computational Intelligence ((SCI,volume 511))

Abstract

In recent years, the accuracy and performance of decision support systems have become a bottleneck in many monitoring applications. As for the accuracy, different classification algorithms are available but the overall performance are related to the specific software implementation. In this paper we propose a novel hardware implementation to fasten a decision tree classifier. We also present the evaluation of our architecture by putting in evidence the positive performance results obtained with the proposed implementation.

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References

  1. Amato, F., Casola, V., Gaglione, A., Mazzeo, A.: A common data model for sensor network integration. In: Proceedings of the 4th International Conference on Complex, Intelligent and Software Intensive Systems, pp. 1081–1086 (2010)

    Google Scholar 

  2. Amato, F., Casola, V., Gaglione, A., Mazzeo, A.: A semantic enriched data model for sensor network interoperability. Simulation Modelling Practice and Theory 19(8), 1745–1757 (2011)

    Article  Google Scholar 

  3. Amato, F., Casola, V., Mazzeo, A., Romano, S.: A semantic based methodology to classify and protect sensitive data in medical records. In: 2010 Sixth International Conference on Information Assurance and Security (IAS), pp. 240–246. IEEE (2010)

    Google Scholar 

  4. Berger, A.L., Pietra, V.J.D., Pietra, S.A.D.: A maximum entropy approach to natural language processing. Computational linguistics 22(1), 39–71 (1996)

    Google Scholar 

  5. Berthold, M.R., Cebron, N., Dill, F., Gabriel, T.R., Kötter, T., Meinl, T., Ohl, P., Thiel, K., Wiswedel, B.: Knime - the konstanz information miner: version 2.0 and beyond. SIGKDD Explor. Newsl. 11(1), 26–31 (2009)

    Article  Google Scholar 

  6. Bhowmik, D., Amavasai, B.P., Mulroy, T.J.: Real-time object classification on fpga using moment invariants and kohonen neural networks. In: IEEE SMC UK-RI Chapter Conference 2006 on Advances in Cybernetic Systems, pp. 43–48 (2006)

    Google Scholar 

  7. Casola, V., Esposito, M., Mazzocca, N., Flammini, F.: Freight train monitoring: A case-study for the pshield project. In: Proceedings - 6th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS 2012, pp. 597–602 (2012)

    Google Scholar 

  8. Casola, V., Gaglione, A., Mazzeo, A.: A reference architecture for sensor networks integration and management. In: Trigoni, N., Markham, A., Nawaz, S. (eds.) GSN 2009. LNCS, vol. 5659, pp. 158–168. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Cho, J., Mirzaei, S., Oberg, J., Kastner, R.: Fpga-based face detection system using haar classifiers. In: FPGA, pp. 103–112 (2009)

    Google Scholar 

  10. Deng, H., Runger, G.C., Tuv, E.: Bias of importance measures for multi-valued attributes and solutions. In: Proceedings of the ICANN, pp. 293–300 (2011)

    Google Scholar 

  11. Ficco, M.: Security event correlation approach for cloud computing. Journal of High Performance Computing and Networking 7(3) (2013)

    Google Scholar 

  12. Liu, B., Ma, Y., Wong, C.K.: Improving an association rule based classifier. In: Zighed, D.A., Komorowski, J., Żytkow, J.M. (eds.) PKDD 2000. LNCS (LNAI), vol. 1910, pp. 504–509. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  13. Wittig, R.D., Chow, P.: Onechip: An fpga processor with reconfigurable logic. In: IEEE Symposium on FPGAs for Custom Computing Machines, pp. 126–135. IEEE (1996)

    Google Scholar 

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Correspondence to Flora Amato .

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Amato, F., Barbareschi, M., Casola, V., Mazzeo, A. (2014). An FPGA-Based Smart Classifier for Decision Support Systems. In: Zavoral, F., Jung, J., Badica, C. (eds) Intelligent Distributed Computing VII. Studies in Computational Intelligence, vol 511. Springer, Cham. https://doi.org/10.1007/978-3-319-01571-2_34

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  • DOI: https://doi.org/10.1007/978-3-319-01571-2_34

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01570-5

  • Online ISBN: 978-3-319-01571-2

  • eBook Packages: EngineeringEngineering (R0)

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