Grey Wolf Cuckoo Search Algorithm for Training Feedforward Neural Network and Logic Gates Design
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Abstract
This paper presents a new hybrid Swarm Intelligence (SI) algorithm based on the Cuckoo Search Algorithm (CSA) and Grey Wolf Optimizer (GWO) called the Grey Wolf Cuckoo Search (GWCS) algorithm. The GWCS algorithm extracts and combines CSA and GWO features for efficient optimization. To carry out the comprehensive validation, the developed algorithm is applied to three different scenarios with their counterparts. The first validation is carried out on standard optimization benchmark problems. Further, they are used to train Feedforward Neural Networks and finally applied to design logic gates. The comprehensive results are presented and it is found that the proposed GWCS algorithms perform better compared to the state-of-the-art.
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How to Cite
Layak Ali, et al. (2023). Grey Wolf Cuckoo Search Algorithm for Training Feedforward Neural Network and Logic Gates Design. International Journal on Recent and Innovation Trends in Computing and Communication, 11(9), 722–732. https://doi.org/10.17762/ijritcc.v11i9.8865
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