A Particle Swarm Optimization-Based Approach for Finding Reliability in a Total Hip Prosthesis

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Author(s): Bouakkar Loubna (1 Research Laboratory in Production (LRP), University of Batna 2, Batna, Algeria), Ameddah Hacene (2 Laboratory of Innovation in Construction, Eco-Design, and Seismic Engineering (LICEGS), University of Batna 2, Batna, Algeria)and Mazouz Hammoudi (University of Batna 2, Batna, Algeria)
Copyright: 2021
Pages: 21
Source title: Artificial Neural Network Applications in Business and Engineering
Source Author(s)/Editor(s): Quang Hung Do (University of Transport Technology, Vietnam)
DOI: 10.4018/978-1-7998-3238-6.ch010

Keywords: Artificial Intelligence / Computer Science & IT / Engineering Science Reference / Neural Networks

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Abstract

Nowadays, we assist the global extension of reliability optimization problems from the design phase of systems and sub-systems to the design and operational phases, not only of systems and sub-systems, but also of bio functionality design. This chapter investigates the relative performances of particle swarm optimization (PSO) variants when used to find reliability in the total hip prosthesis by finding the maximization of jumping distance (JD) to avoid dislocation and the minimization of system's stability to offer mobility. Statistical analysis of different cases of head diameters of 22, 28, 36, 40 mm has been conducted to survey the convergence and relative performances of the main PSO variants when applied to solve reliability in the total hip prosthesis.

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A Particle Swarm Optimization-Based Approach for Finding Reliability in a Total Hip Prosthesis

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