Comparative study of an intelligent dynamic approaches in predicting exchange rate

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "S. Indrakala and T. Chitrakalarani",
  booktitle =    "2016 International Conference on Emerging Trends in
                 Engineering, Technology and Science (ICETETS)",
  title =        "Comparative study of an intelligent dynamic approaches
                 in predicting exchange rate",
  year =         "2016",
  abstract =     "The objective of the projected paper is to do study,
                 development in an intelligent dynamic methods to expect
                 the financial goods. For financial shop expectation
                 different methods like Rough Set, Genetic Programming
                 with Boosting Technique, Best Replacement Optimisation
                 (BRO), and Genetic Programming with Rough Set and BRO
                 with Rough Set are used. These models tested with five
                 datasets representing different sectors in S&P 50 stock
                 market and used to predict daily stock prices. Results
                 presented in this paper showed that the proposed BRO-RS
                 model have quick convergence rate at early stages of
                 the iterations. BRO-RS model achieved better accuracy
                 than compared models in price and trend prediction.",
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1109/ICETETS.2016.7603125",
  month =        feb,
  notes =        "Also known as \cite{7603125}",

Genetic Programming entries for S Indrakala T Chitrakalarani