粒子群优化是回归中参数估计的一种替代方法

Q3 Economics, Econometrics and Finance

Fuzzy Economic Review Pub Date : 2013-01-01 DOI:10.25102/FER.2013.02.02

S. De-Los-Cobos-Silva, A. Terceño-Gómez, M. Gutiérrez-Ándrade, E. Rincón-García, Pedro Lara-Velázquez, M. Aguilar-Cornejo

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引用次数: 4

摘要

应用曲线拟合技术来描述数据的实践在许多领域都很普遍:在生物学、医学、工程、经济等领域。提出了一种用于回归模型参数估计的启发式算法——粒子群优化算法。该算法在NIST(2001)收集的27个非线性模型数据库和11个线性模型数据库上进行了测试，这些数据库被认为具有不同的困难程度。我们给出了实验结果

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Particle swarm optimization an alternative for parameter estimation in regression

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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来源期刊

Fuzzy Economic Review Economics, Econometrics and Finance-Economics and Econometrics

CiteScore

0.40

自引率

0.00%

发文量