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Fuzzy C-means-based scenario bundling for stochastic service network design (2018)
Conference Proceeding
Jiang, X., Bai, R., Landa-Silva, D., & Aickelin, U. (2018). Fuzzy C-means-based scenario bundling for stochastic service network design. In 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017 - Proceedings (1-8). https://doi.org/10.1109/SSCI.2017.8280905

Stochastic service network designs with uncertain demand represented by a set of scenarios can be modelled as a large-scale two-stage stochastic mixed-integer program (SMIP). The progressive hedging algorithm (PHA) is a decomposition method for solvi... Read More about Fuzzy C-means-based scenario bundling for stochastic service network design.

A Method for Evaluating Options for Motif Detection in Electricity Meter Data (2018)
Journal Article
Dent, I., Craig, T., Aickelin, U., & Rodden, T. (2018). A Method for Evaluating Options for Motif Detection in Electricity Meter Data. International Journal of Data Science, 16(1), 1-28. https://doi.org/10.6339/jds.201801_16%281%29.0001

Investigation of household electricity usage patterns, and matching the patterns to behaviours, is an important area of research given the centrality of such patterns in addressing the needs of the electricity industry. Additional knowledge of househ... Read More about A Method for Evaluating Options for Motif Detection in Electricity Meter Data.