Data-driven Modelling for decision making under uncertainty

4th International Conference on Operational Research

Angria S, Layla^1 ; Dwi Sari, Yunita^1 ; Zarlis, Muhammad^1 ; Tulus^1

Department of Mathematics, University of Sumatera Utara, Medan, Indonesia^1

关键词: Bayesian approaches;    Best model;    Data driven modelling;    Data-driven model;    Decision making under uncertainty;    Decision-making problem;    Nonlinear differential equation;    Operation research;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/300/1/012013/pdf
DOI  :  10.1088/1757-899X/300/1/012013

来源: IOP

【 摘 要 】

The rise of the issues with the uncertainty of decision making has become a very warm conversation in operation research. Many models have been presented, one of which is with data-driven modelling (DDM). The purpose of this paper is to extract and recognize patterns in data, and find the best model in decision-making problem under uncertainty by using data-driven modeling approach with linear programming, linear and nonlinear differential equation, bayesian approach. Model criteria tested to determine the smallest error, and it will be the best model that can be used.