Management studies of inflow forecasting with advanced queries module

• Grant number: 11/09178-1
• Support Opportunities: Regular Research Grants
• Start date: January 01, 2012
• End date: December 31, 2012
• Field of knowledge: Engineering - Civil Engineering - Hydraulic Engineering
• Principal Investigator: Ieda Geriberto Hidalgo
• Grantee: Ieda Geriberto Hidalgo
• Host Institution: Faculdade de Tecnologia (FT). Universidade Estadual de Campinas (UNICAMP). Limeira , SP, Brazil

Abstract

This research project aims to develop a methodology for management studies of inflow forecasting with a specific module for creating advanced queries. The methodology will be implemented in order to become a tool that supports researchers and professionals in Civil Engineering, Electrical Engineering, Mathematics, Statistics and Computation.The tool will consist of five already existing mathematical models that are based on: linear regression, artificial neural networks and hydrologic simulation. These models provide daily and monthly inflows for hydroelectric plants of National Interconnected System. The main objective of the proposed methodology is to facilitate the result's analysis of inflow predictors and compare different models developed for the same purpose. It is hoped to improve the accuracy of the predicted streamflow used as input to computational models of the Brazilian electric sector for planning and scheduling of hydroelectric plants. (AU)

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

IVETTE LUNA; IEDA G. HIDALGO; PAULO S.M. PEDRO; PAULO S.F. BARBOSA; ALBERTO L. FRANCATO; PAULO B. CORREIA. FUZZY INFERENCE SYSTEMS FOR MULTI-STEP AHEAD DAILY INFLOW FORECASTING. Pesquisa Operacional, v. 37, n. 1, p. 129-144, 2017-01-00. (11/09178-1)