A Three-Step Combined Genetic Programming and Neural Networks Method of Forecasting the S\&P/Case-Shiller Home Price Index

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@Article{journals/ijcia/KaboudanC13,

• author = "Mak Kaboudan and Mark Conover",
• title = "A Three-Step Combined Genetic Programming and Neural Networks Method of Forecasting the {S\&P/Case-Shiller} Home Price Index",
• journal = "International Journal of Computational Intelligence and Applications",
• year = "2013",
• number = "1",
• volume = "12",
• pages = "1350001",
• month = mar,
• keywords = "genetic algorithms, genetic programming, Forecasting home prices, neural networks, ANN, case-Shiller index",
• ISSN = "1469-0268",
• bibdate = "2013-04-22",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/journals/ijcia/ijcia12.html#KaboudanC13",
• URL = "http://www.worldscientific.com/doi/abs/10.1142/S1469026813500016",
• DOI = "doi:10.1142/S1469026813500016",
• abstract = "Forecasts of the San Diego and San Francisco S&P/Case-Shiller Home Price Indices through December 2012 are obtained using a multi-agent system that uses January, 2002 to June, 2011 data. Agents employ genetic programming (GP) and neural networks (NN) in a three-stage process to produce fits and forecasts. First, GP and NN compete to provide independent predictions. In the second stage, they cooperate by fitting the first-stage competitor's residuals. Outputs from the first two stages then become inputs to produce two final GP and NN outputs. The NN output from the third stage using the combined method produces improved forecasts over the 3-stage GP method as well as those produced by either method alone. The proposed methodology serves as an example of how combining more than one estimation/forecasting technique may lead to more accurate forecasts.",

}

Genetic Programming entries for Mahmoud A Kaboudan Mark Conover

Citations