SAM-kNN Regressor for Online Learning in Water Distribution Networks

Water distribution networks are a key component of modern infrastructure for housing and industry. They transport distribute water via widely branched from sources to consumers. In order guarantee working network at all times, the supply company continuously monitors takes actions when necessary – e.g. reacting leakages, sensor faults drops in quality. Since real world too large complex be monitored by human, algorithmic monitoring systems have been developed. A popular type such residual based anomaly detection that can detect events as leakages faults. For continuous high quality monitoring, it is these adapt changed demands presence various anomalies. this work, we propose an adaption incremental SAM-kNN classifier regression build system able any kind change.