Data clustering and imputing using a two-level multi-objective genetic algorithm (GA): A case study of maintenance cost data for tunnel fans
This study develops a new two-level multi-objective genetic algorithm (GA) to optimise clustering to reduce and impute missing cost data for fans used in road tunnels by the Swedish Transport Administration (Trafikverket). Level 1 uses a multi-objective GA based on fuzzy c-means to cluster cost data...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2018-01-01
|
| Series: | Cogent Engineering |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/23311916.2018.1513304 |