Applying CI in Biology through PSO

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Author(s): Rojalina Priyadarshini (C. V. Raman College of Engineering, India), Nilamadhab Dash (C. V. Raman College of Engineering, India), Brojo Kishore Mishra (C. V. Raman College of Engineering, India)and Rachita Misra (C. V. Raman College of Engineering, India)
Copyright: 2020
Pages: 26
Source title: Data Analytics in Medicine: Concepts, Methodologies, Tools, and Applications
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-1204-3.ch028

Keywords: Data Analysis & Statistics / Library & Information Science / Medical Information Science Reference / Medical Technologies

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Abstract

Conventional computing methods face challenges dealing with real world problems, which are characterised by noisy or incomplete data. To find solutions for such problems, natural systems have evolved over the years and on analysis it has been found these contain many simple elements when working together to solve real life complex problems. Swarm Intelligence (SI) is one of the techniques which is inspired by nature and is a population based algorithm motivated by the collective behaviour of a group of social insects. Particle swarm optimization (PSO) is one of the techniques belonging to this group, used to solve some optimization problems. This chapter will discuss some of the problems existing in computational biology, their contemporary solution methods followed by the use of PSO to address those problems. Along with this several applications of PSO are discussed in few of the relevant fields are discussed having some future research directions on this field.

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Applying CI in Biology through PSO

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