@Article{10798587.2017.1327154,
AUTHOR = {Rheleh Jfri, Wen Yu, Xioou Li},
TITLE = {Numerical Solution of Fuzzy Equations with Z-numbers Using Neural Networks},
JOURNAL = {Intelligent Automation \& Soft Computing},
VOLUME = {24},
YEAR = {2018},
NUMBER = {1},
PAGES = {151--158},
URL = {http://www.techscience.com/iasc/v24n1/39738},
ISSN = {2326-005X},
ABSTRACT = {In this paper, the uncertainty property is represented by the Z-number as the coefficients of the fuzzy
equation. This modification for the fuzzy equation is suitable for nonlinear system modeling with
uncertain parameters. We also extend the fuzzy equation into dual type, which is natural for linearin-parameter nonlinear systems. The solutions of these fuzzy equations are the controllers when the
desired references are regarded as the outputs. The existence conditions of the solutions (controllability)
are proposed. Two types of neural networks are implemented to approximate solutions of the fuzzy
equations with Z-number coefficients.},
DOI = {10.1080/10798587.2017.1327154}
}