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Residential construction demand forecasting using economic indicators: a comparative study of artificial neural networks and multiple regression
5 references·16 citing·44 second hop
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References

  • 2000Forecasting Economic Time Series1,768 cited
  • 1986Forecasting Economic Time Series714 cited
  • 1988Economic prediction using neural networks: the case of IBM daily stock returns698 cited
  • 1974Economic Theory and the Construction Industry231 cited
  • 1985Economic Theory and the Construction Industry203 cited

Cited by

  • 2012Using ridge regression with genetic algorithm to enhance real estate appraisal forecasting97 cited
  • 2008Using genetic algorithms and linear regression analysis for private housing demand forecast81 cited
  • 2004Neural Network Model to Support International Market Entry Decisions74 cited
  • 2000Evaluating the performance of combining neural networks and genetic algorithms to forecast construction demand: the case of the Singapore residential sector73 cited
  • 2005Prediction of Organizational Effectiveness in Construction Companies73 cited
  • 2017Using Genetic Algorithms for Real Estate Appraisals70 cited
  • 2011Forecasting construction demand: a vector error correction model with dummy variables58 cited
  • 1998Forecasting residential construction demand in Singapore: a comparative study of the accuracy of time series, regression and artificial neural network techniques53 cited
  • 2005Predicting the risk of contractor default in Saudi Arabia utilizing artificial neural network (ANN) and genetic algorithm (GA) techniques

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48 cited
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  • 2005Managing Owner’s Risk of Contractor Default34 cited
  • 2004INTELLIGENT MODELS FOR PREDICTING LEVELS OF CLIENT SATISFACTION34 cited