Data clustering and imputing using a two-level multi-objective genetic algorithm (GA): A case study of maintenance cost data for tunnel fans

  • Yamur K. Aldouri, Hassan Al-Chalabi, Liangwei Zhang
  • Cogent Engineering, August 2018, Taylor & Francis
  • DOI: 10.1080/23311916.2018.1513304

Data clustering, Data imputing, Multi-objective GA, Fuzzy c-means, K-means clustering

What is it about?

This study develops a new two-level multi-objective genetic algorithm (GA) to optimize clustering in order to redact and impute missing cost data for fans used in road tunnels by the Swedish Transport Administration (Trafikverket).

Why is it important?

Our model shows better clustering, suitable geometry and evaluation compared with k-means.

Read Publication

http://dx.doi.org/10.1080/23311916.2018.1513304

The following have contributed to this page: Dr Hussan Hamodi and Yamur Douri