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Standard Library Tool Set for Rough Set Theory on FPGA

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Advances in Data and Information Sciences

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 94))

Abstract

Rough Set Theory is a powerful Artificial Intelligence based tool used for data analysis and mining Inconsistent Information Systems. In the presence of inconsistent, incomplete, imprecise or vague data, normal statistical-based data analytic techniques lag behind. The various software used for the analysis of inconsistent data using Rough Set Theory runs on x86 kind of processors for various operating systems. Unlike the other software implementations, the main objective of undertaking this experimentation is to describe a new and standard library tool set for the computation of inconsistent data using Rough Set Theory which is completely synthesizable on FPGA. Further, the authors have also studied the effect of implemented design on Zybo FPGA for understanding the area, timing, and power efficiency criteria. A Rough Set Theory based Data Analytic Engine can be used as a potential candidate for knowledge discovery and data mining of inconsistent data in IoT applications at fog and/or edge interfaces. This paper defines the standard library tool for Rough Set Theory on FPGA.

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Acknowledgements

The authors would like to thank Mr. A. B. Patki, Ex-Senior Director/Scientist G and HoD, Ministry of Electronics and Information Technology, Government of India for his valuable suggestions and guidance. We also acknowledge the help provided by the officials of the College of Engineering Pune.

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Authors and Affiliations

  1. Electronics and Telecommunication Department, College of Engineering Pune, Pune, Maharashtra, India

    Vanita Agarwal & Rajendrakumar A. Patil

Authors
  1. Vanita Agarwal
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  2. Rajendrakumar A. Patil
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Corresponding author

Correspondence to Vanita Agarwal .

Editor information

Editors and Affiliations

  1. Smart Grid and Renewable Energy, University of Agder, Kristiansand, Norway

    Mohan L. Kolhe

  2. Department of Computer Science and Engineering, ABES Engineering College, Ghaziabad, Uttar Pradesh, India

    Shailesh Tiwari

  3. Department of Computer Science and Engineering, NIT Agartala, Tripura, India

    Munesh C. Trivedi

  4. Computer Science and Engineering, Motilal Nehru National Institute of Technology Allahabad, Prayagraj, India

    Krishn K. Mishra

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Agarwal, V., Patil, R.A. (2020). Standard Library Tool Set for Rough Set Theory on FPGA. In: Kolhe, M., Tiwari, S., Trivedi, M., Mishra, K. (eds) Advances in Data and Information Sciences. Lecture Notes in Networks and Systems, vol 94. Springer, Singapore. https://doi.org/10.1007/978-981-15-0694-9_23

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  • DOI: https://doi.org/10.1007/978-981-15-0694-9_23

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0693-2

  • Online ISBN: 978-981-15-0694-9

  • eBook Packages: EngineeringEngineering (R0)

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