GPU BASED TOOLBOX FOR FUZZY LOGIC SYSTEM USING WHALE OPTIMIZATION ALGORITHM

Abstract

Fuzzy Logic System (FLS) is an efficient method to solve engineering problems. However, the training of a Fuzzy Logic System is a time-consuming task. Optimization Algorithm can be used to optimize the rule base of any FLS. Out of Type-1 FLS and Type-2 FLS, the type-2 found to be more effective to deal with noisy data. Due to their computational requirements Interval Type-2 (IT2) has been preferred over General Type-2. Whale Optimization Algorithm (WOA)has been introduced recently. The algorithm has been tested on different engineering problems and is found to be more effective. General Purpose Computing using graphics Processing Unit (GPGPU) is a new way to solve compute intensive problems on Graphics Processing Unit (GPU). CUDA-C is a parallel language that can be used to execute parallel code NVIDIA GPU. This paper integrates IT2 FLS, WOA and Processing Power of GPU. A toolbox is proposed that can be used to optimize the rule base in parallel. The toolbox provides both the implementations, i.e. serial and Parallel. FLS WOA Toolbox is design in such a way that user can pass parameter dynamically according to their need without interfacing with the code.

Authors and Affiliations

SARABJEET SINGH, SATVIR SINGH AND VIJAY KUMAR BANGA

Keywords

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  • EP ID EP46503
  • DOI 10.34218/IJCET.10.1.2019.002
  • Views 241
  • Downloads 0

How To Cite

SARABJEET SINGH, SATVIR SINGH AND VIJAY KUMAR BANGA (2019). GPU BASED TOOLBOX FOR FUZZY LOGIC SYSTEM USING WHALE OPTIMIZATION ALGORITHM. International Journal of Computer Engineering & Technology (IJCET), 10(1), -. https://europub.co.uk/articles/-A-46503