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A genetic algorithm approach to find the best regression/econometric model among the candidates

Hasheminia, H ; Sharif University of Technology | 2006

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  1. Type of Document: Article
  2. DOI: 10.1016/j.amc.2006.05.072
  3. Publisher: 2006
  4. Abstract:
  5. Although statistical modeling is a common task in different fields of science, it is still difficult to estimate the best model that can accurately describe inherent characteristics of a system for which historical or experimental data are available. Since we may classify estimating techniques as optimizations, we can model this problem as an optimization problem and solve it by a new heuristic algorithm like neural networks, genetic algorithms, and tabu search or by classic ones such as regression and econometric models. In this paper, we propose a new type of genetic algorithm to find the best regression model among all suggested and evaluate its performances by an economical case study. © 2006 Elsevier Inc. All rights reserved
  6. Keywords:
  7. Mathematical models ; Neural networks ; Operations research ; Problem solving ; Regression analysis ; Econometric models ; Search techniques ; Genetic algorithms
  8. Source: Applied Mathematics and Computation ; Volume 183, Issue 1 , 2006 , Pages 337-349 ; 00963003 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/abs/pii/S0096300306005662