@inproceedings{42f9e056f481451c8d095a52a5484730,
title = "A new computational method for solving fully fuzzy nonlinear systems",
abstract = "Predicting the solution of complex systems is a significant challenge. Complexity is caused mainly by uncertainty and nonlinearity. The nonlinear nature of many complex systems leaves uncertainty irreducible in many cases. In this work, a novel iterative strategy based on the feedback neural network is recommended to obtain the approximated solutions of the fully fuzzy nonlinear system (FFNS). In order to obtain the estimated solutions, a gradient descent algorithm is suggested for training the feedback neural network. An example is laid down in order to demonstrate the high accuracy of this suggested technique.",
keywords = "approximate solution, complex system, feedback neural network, gradient descent algorithm, simulation",
author = "Raheleh Jafari and Sina Razvarz and Alexander Gegov",
year = "2018",
month = sep,
doi = "10.1007/978-3-319-98443-8\_46",
language = "English",
isbn = "978-3-319-98442-1",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "503--512",
editor = "Nguyen, \{Ngoc Thanh\} and Elias Pimenidis and Zaheer Khan and Bogdan Trawi{\'n}ski",
booktitle = "Computational Collective Intelligence",
address = "Netherlands",
note = "10th International Conference on Collective Intelligence, ICCCI 2018 ; Conference date: 05-09-2018 Through 07-09-2018",
}