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Using Particle Swarm Optimization Algorithm as an Optimization Tool Within Developed Neural Networks

Using Particle Swarm Optimization Algorithm as an Optimization Tool Within Developed Neural Networks
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Author(s): Goran Klepac (Raiffeisenbank Austria, Croatia)
Copyright: 2018
Pages: 30
Source title: Critical Developments and Applications of Swarm Intelligence
Source Author(s)/Editor(s): Yuhui Shi (Southern University of Science and Technology, China)
DOI: 10.4018/978-1-5225-5134-8.ch009

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Abstract

Developed neural networks as an output could have numerous potential outputs caused by numerous combinations of input values. When we are in position to find optimal combination of input values for achieving specific output value within neural network model it is not a trivial task. This request comes from profiling purposes if, for example, neural network gives information of specific profile regarding input or recommendation system realized by neural networks, etc. Utilizing evolutionary algorithms like particle swarm optimization algorithm, which will be illustrated in this chapter, can solve these problems.

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