Scholarship 18/26592-5 - Análise de séries temporais, Tempo-real - BV FAPESP
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Development of a real-time forecasting model for demand and levels of reservoir with big data of water industry

Grant number: 18/26592-5
Support Opportunities:Scholarships in Brazil - Master
Start date until: March 01, 2019
End date until: February 28, 2021
Field of knowledge:Physical Sciences and Mathematics - Probability and Statistics - Statistics
Principal Investigator:Chang Chiann
Grantee:Leonardo Fonseca Larrubia
Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil
Associated research grant:17/50343-2 - Institutional development plan in the area of digital transformation: advanced manufacturing and smart and sustainable cities (PDIp), AP.PDIP

Abstract

The objective of this project is to explore a big data solution of the water industry for the unattended automation of the daily programming of the water adduction operational controls using some parametric time series models such as harmonic model with periodicity of 12 and 24 hours + autoregressive model; SARIMA model (Seasonal Autoregressive Moving Average Models); model ARFIMA (Long Memory ARMA and Fractional Differencing) and regression model using wavelets. (AU)

News published in Agência FAPESP Newsletter about the scholarship:
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Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
LARRUBIA, Leonardo Fonseca. Anomaly detection, interpolation and real-time forecasting of time series for reservoir operation and water distribution. 2021. Master's Dissertation - Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) São Paulo.

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