THE USE OF ARTIFICIAL NEURAL NETWORKS IN ASPECTS OF CONSTRUCTION PRODUCTIVITY LEVELS ANALISYS

Authors

  • Julio Baeza Pereyra Universidad Autónoma de Yucatán (Mexico)
  • José González Fajardo Universidad Autónoma de Yucatán (Mexico)
  • Guillermo Salazar Ledezma Instituto Politécnico de Worcester (Estados Unidos)

Abstract

This paper presents some of the results obtained in applying Artificial Neural Networks (ANN), Knowledge-Based Expert Systems (KBES), and Discrete Event Simulation technologies to different aspects of construction analysis and estimation. A brief introduction on the major problems in construction appraisal and analysis is presented. The basic approach proposed for applying Neural Networks technology to construction environment classification, construction methods feasibilityanalysis, and overall productivity rates estimation under circunstances of construction environment variability is then described. This paper concludes with an indication of  areas for furtherdevelopment and conclusions.

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Author Biographies

Julio Baeza Pereyra, Universidad Autónoma de Yucatán (Mexico)

Unit of Graduate Studies and Research School of Engineering, Autonomous University of Yucatan

José González Fajardo, Universidad Autónoma de Yucatán (Mexico)

Professor Unit of Graduate Studies and Research School of Engineering Autonomous University of Yucatan

Guillermo Salazar Ledezma, Instituto Politécnico de Worcester (Estados Unidos)

Associate Professor Coordinator of the Master Builder Program Department of Civil and Environmental Engineering Worcester Polytechnic Institute

Published

2001-04-30

How to Cite

Baeza Pereyra, J., González Fajardo, J., & Salazar Ledezma, G. (2001). THE USE OF ARTIFICIAL NEURAL NETWORKS IN ASPECTS OF CONSTRUCTION PRODUCTIVITY LEVELS ANALISYS. Revista Ingeniería De Construcción, 16(1), 29–38. Retrieved from https://ojs.uc.cl/index.php/ric/article/view/17171

Issue

Section

Original Research