Baker Botts LLP
Metrics monitoring and financial validation system (M2FVS) for tracking performance of capital, operations, and maintenance investments to an infrastructure
Techniques for evaluating the accuracy of a predicted effectiveness of an improvement to an infrastructure include collecting data, representative of at least one pre-defined metric, from the infrastructure during first and second time periods corresponding to before and after a change has been implemented, respectively. A machine learning system can receive compiled data representative of the first time period and generate corresponding machine learning data. A machine learning results evaluator can empirically analyze the generated machine learning data. An implementer can implement the change to the infrastructure based at least in part on the data from a machine learning data outputer. A system performance improvement evaluator can compare the compiled data representative of the first time period to that of the second time period to determine a difference, if any, and compare the difference, if any, to a prediction based on the generated machine learning data.
The Trustees of Columbia University in the City of New York
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G06Q
inventional
Leon Serena Roger N. Albert
Wu Lee Anderson Boulanger