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RISAn Active-Learning Framework for Efficient Training and Bias Mitigation in Probabilistic Forecasting of Water Pipeline Failures
Publisher: American Society of Civil Engineers
Abstract: AbstractDespite recent advancements in forecasting models for water pipe failures, their implementation
remains challenging in many urban environments due to data scarcity. Because water
pipe breaks are irregular and ...
A Context-Aware Progressive Approach to Imputing Multivariate Heterogeneous Data in Water Pipe Networks
Publisher: American Society of Civil Engineers
Abstract: AbstractGiven the logistical and financial complications in routine inspection of water pipelines,
data-driven forecasting models play a crucial role in prioritizing inspection and
maintenance tasks for pipes with a higher ...