Abstract
The practice of applying curve fitting techniques to describe data is widespread in many fields: in biology, in medicine, in engineer, in economy, etc. This paper presents a heuristic technique named Particle Swarm Optimization to be used for parameter estimation in regression models. The algorithm was tested on 27 databases for nonlinear models and 11 for linear models by collection NIST (2001), which are considered with different degrees of difficulty. We present experimental results
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