1. Predicting commodity and virtual water flows using machine learning: Analysis of modeling experiments and time series predictions with Random Forest Open Access Author: Oreggioni Weiberlen, Fiorella Title: Predicting commodity and virtual water flows using machine learning: Analysis of modeling experiments and time series predictions with Random Forest Graduate Program: Civil Engineering Keywords: complex networkspatial networkgravity modelrandom foresttradewater footprintcomplex networksspatial networksmachine learninig File: Download Thesis_FiorellaOreggioni_Final.pdf Committee Members: Alfonso Ignacio Mejia, Thesis Advisor/Co-AdvisorCaitlin A Grady, Committee MemberLauren Mc Phillips, Committee MemberPatrick Joseph Fox, Program Head/Chair
