A novel technique for solving fully fuzzy nonlinear systems based on neural networks
Research output: Contribution to journal › Article › peer-review
Predicting the solutions of complex systems is a crucial challenge. Complexity exists because of the uncertainty as well as nonlinearity. The nonlinearity in complex systems makes uncertainty irreducible in several cases. In this paper, two new approaches based on neural networks are proposed in order to find the estimated solutions of the fully fuzzy nonlinear system (FFNS). For obtaining the estimated solutions, a gradient descent algorithm is proposed in order to train the proposed networks. An example is proposed in order to show the efficiency of the considered approaches.
|Number of pages||15|
|Journal||Vietnam Journal of Computer Science|
|Publication status||Published - 18 Feb 2020|
Final published version, 2.68 MB, PDF document
Licence: CC BY