INVESTIGADORES
BRIGNOLE Nelida Beatriz
congresos y reuniones científicas
Título:
Neural Networks applied to small datasets: efficiency evolution of natural gas networks
Autor/es:
DE MEIO REGGIANI, M.C; CHIARVETTO PERALTA L.L.; VIEGO V; BRIGNOLE N. B.
Lugar:
Montevideo
Reunión:
Conferencia; KHIPU: Latin American Meeting In Artificial Intelligence; 2019
Institución organizadora:
Khipu
Resumen:
In January 2002, the Argentinean government enacted the Public Emergency and Exchange Regime Reform Law, which froze utility rates and forced their conversion to local currency. Despite the existence of a long-lasting inflation process, this policy remained in place for more than a decade. Natural gas transport companies were also affected by this law, affecting investment projects and their financial stability. In an attempt to evaluate whether this policy could have affected pipeline operations, a possible shift in technical efficiency was assessed by means of an Artificial Neural Network model. Results suggest that technical efficiency increased after 2002. As profits had been declining due to a combination of frozen prices and persisting inflation, operators might have been stimulated to reduce inefficiencies and limit losses.