Towards automated cost analysis, benchmarking and estimating in construction: a machine learning approach

Chen, D., Hajderanj, L. ORCID: https://orcid.org/0009-0007-0445-3049 and Fiske, J. (2019) Towards automated cost analysis, benchmarking and estimating in construction: a machine learning approach. In: International Conference Big Data Analytics, Data Mining and Computational Intelligence 2019, 16-19 Jul 2019, Porto, Portugal, pp. 85-91. doi: 10.33965/bigdaci2019_201907l011

Abstract/Summary

In this paper, a novel machine learning based approach is proposed for automated cost analysis on priced bill of quantities prepared by tenders in the construction industry. The proposed approach features: 1) An effective integration of structured project-specific information with surveyor's domain knowledge in order to model the complex interrelationships between the specifications and descriptions of an item and its trade category; 2) An effective transformation by supervised t-SNE to map the original data into a 2-dimensional space to tackle issues of high dimensionality in modelling and creating classifiers, and 3) Simple classifiers with a high classification accuracy and a good generalization capability. Relevant comparative experimental results have demonstrated the effectiveness of the proposed approach.