Banca de DEFESA: TARCISO DE CASTRO ROSARIO

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : TARCISO DE CASTRO ROSARIO
DATE: 25/07/2022
TIME: 09:00
LOCAL: videoconferência na plataforma RNP (sala PEI-UFBA)
TITLE:

SIMULTANEOUS DATA RECONCILIATION AND ESTIMATION OF PARAMETERS: METHODOLOGY FOR EVALUATION OF THE MATRIX OF COVARIANCE AND REGIONS COVERED BY VARIABLES OF DECISION.

KEY WORDS:

data reconciliation, parameter estimation, simultaneous data reconciliation and parameter estimation, covariance matrix, coverage region, SDRPE, modeling uncertainty, measurement uncertainty, information uncertainty.

PAGES: 150
BIG AREA: Engenharias
AREA: Engenharia de Produção
SUMMARY:

Data reconciliation (DR) and parameter estimation (PE) problems require measured or estimated quantities that necessarily have uncertainty which is propagated to the decision variables of the optimization problem. In the same way that the quality of the measured data is evaluated, the quality of the results obtained after solving the optimization problem must be evaluated, which is often neglected. Thus, the objective of this dissertation is to show the importance and discuss ways to evaluate reconciled quantities and model parameters obtained in DR problems and in problems in which there is simultaneous data reconciliation and parameter estimation (SDRPE), as well as the residual characteristics. Three routes were explored: (i) proposal of a method for evaluating the covariance matrix of the decision variables, which was able not only to reproduce results similar to the methods in the literature, but also to calculate the covariance matrix in cases where these were not were successful;(ii) proposal of a method for the construction of the coverage regions, basedon the bootstrap technique, which proved to be useful to evaluate the quality of the model and the phenomeno logical coherence of the reconciled quantities obtained;and (iii) analysis of residuals through graphs and statistical tests, which showed theimportance of validating the hypotheses adopted in the construction of the objective function as well as the need to use adequate analysis tools depending on the type of case, univariate or multivariate. In addition, the use of coverage regions as a decisive criterion for choosing among certain models proved to be effective for cases in which it is not possible to carry out this analysis using criteria such as AIC, AICc, BIC. 𝑅2 and 𝑅2 𝑎𝑑𝑗.

BANKING MEMBERS:
Externo à Instituição - Diego Martínez Prata
Externo ao Programa - 2411885 - DANIEL DINIZ SANTANA
Externo à Instituição - LUIS CLAUDIO OLIVEIRA LOPES
Presidente - 297.221.365-34 - RICARDO DE ARAUJO KALID - UFBA