Medical Disease Prediction with Grey Wolf Optimizer Using Levy and Gaussian Random Walk Distributions

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Kamala Srinidhi.V
Sheeba Betsy
Alamelu.T
S.Kanmani

Abstract

This paper proposes an enhancement of the optimization algorithm called Grey Wolf optimizer (GWO) [1] using various random walk distributions. GWO algorithm is used for the relevant attributes selection process. This helps in improving the efficiency of the medical disease prediction system. GWO algorithm recognizes the different related attributes such as breast cancer, heart related disease, diabetes and etc. It also, employs minimum parameters such as blood pressure, cholesterol, and etc. GWO, which is nature, bio-inspired algorithm that logically divides search process into two categories: Exploration and Exploitation. The proposed idea is to enhance the exploration characteristics of the algorithm. This can be achieved by incorporating Levy or Gaussian distribution along with Random Walk (RW) in Grey Wolf Optimization Algorithm (GWO) [4] instead of Cauchy Distribution that fully concentrated on maximizing exploitation, which is proven by the outperformance of the algorithm in all seven unimodal benchmark functions.

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How to Cite
Kamala Srinidhi.V, Sheeba Betsy, Alamelu.T, & S.Kanmani. (2022). Medical Disease Prediction with Grey Wolf Optimizer Using Levy and Gaussian Random Walk Distributions. IIRJET, 5(3). https://doi.org/10.32595/iirjet.org/v5i3.2020.126