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).
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Why is it important?
Our model shows better clustering, suitable geometry and evaluation compared with k-means.
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This page is a summary of: Data clustering and imputing using a two-level multi-objective genetic algorithm (GA): A case study of maintenance cost data for tunnel fans, Cogent Engineering, August 2018, Taylor & Francis,
DOI: 10.1080/23311916.2018.1513304.
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