An open-source control algorithm for combined sewers demonstrates how treatment plant benefits can be balanced with operation of the collection system.

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In this paper, we present the first open-source implementation of the robust random cut forest (RRCF) algorithm-an unsupervised ensemble method for anomaly detection on streaming data (Guha, Mishra, Roy, & Schrijvers, 2016). RRCF offers a number of features that many competing anomaly detection algorithms lack. Specifically, RRCF: