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RISActive Probabilistic Fast Kernel Extreme-Learning Machine for Data-Efficient Bridge Condition Prediction
Publisher: American Society of Civil Engineers
Abstract: AbstractBridge condition assessment in many countries, including the US, relies on routine
inspections of all bridges at predetermined intervals, costing millions of dollars
each year. The significant cost of this approach, ...
An 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 ...