Title: A new bio-inspired algorithm: lizard optimisation

Authors: Dharmpal Singh

Addresses: Department of Computer Science and Engineering, JIS College of Engineering, Block 'A' Phase III, Kalyani, Nadia-741235, West Bengal, India

Abstract: A new bio-inspired, lizard algorithm (LA) is proposed for optimisation of soft computing used in data mining. Here, an effort has been made to mimic the anole lizard behaviour to optimise problems of the dataset. Furthermore, the experiments have been carried out on five benchmark problems with ten benchmark algorithms like statistical, fuzzy, neural network, tabu search, simulated annealing, HS, DEA, PCO, ABC and ACO on dataset. The concept of average error and residual error were conducted to compare the performance of LA with that of other used algorithms. The concepts of residual analysis and chi test (χ²) have also been performed on the proposed algorithm to check the righteous among the algorithms. And the result has shown that LA has achieved good optimisation results in terms of both optimisation accuracy and robustness.

Keywords: data mining; association rule; fuzzy logic; neural network; particle swarm optimisation; PSO; artificial bee colony algorithm; ant colony optimisation; ACO; differential evolution algorithm; DEA; tabu search; simulating annealing; harmony search algorithm; lizard algorithm.

DOI: 10.1504/IJCAET.2021.111634

International Journal of Computer Aided Engineering and Technology, 2021 Vol.14 No.1, pp.1 - 26

Received: 23 Dec 2017
Accepted: 14 May 2018
Published online: 07 Dec 2020 *

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