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RISPredicting Resilient Modulus of Cementitiously Stabilized Subgrade Soils Using Neural Network, Support Vector Machine, and Gaussian Process Regression
Publisher: ASCE
Abstract: Artificial neural network (ANN), support vector machine (SVM), and Gaussian process regression (GPR) were developed in this study for predicting resilient modulus (Mr) values of cementitously stabilized subgrade soils. A ...
Improving the Predictive Analytics of Machine-Learning Pipelines for Bridge Infrastructure Asset Management Applications: An Upstream Data Workflow to Address Data Quality Issues in the National Bridge Inventory Database
Publisher: ASCE
Abstract: The increasing availability of bridge data from the National Bridge Inventory (NBI) offers a great opportunity to perform predictive analytics (such as bridge deterioration prediction) using machine learning (ML) pipelines ...
Expert Knowledge–Guided Bayesian Belief Networks for Predicting Bridge Pile Capacity
Publisher: ASCE
Abstract: Bridge pile capacity is a vital criterion used to assure the durability and stability of a bridge pile foundation. In fact, reliably predicting the pile capacity plays a significant role in supporting data-driven decisions ...