Modified Barzilai-Borwein (MBB) gradient method for solving fuzzy nonlinear equations

Research has demonstrated that conventional analytical techniques such as the SD, BB, CG, and N approaches are insufficient to solve a collection of fuzzy non-linear equations that involve fuzzy number coefficients[1]. Because of this, the two-step extended gradient method is suggested as an alternative way to resolve these kinds of unclear nonlinear equations. This work uses a six-step technique to solve ambiguous nonlinear equations[7]. This method does not require the Jacobi method and only requires finding a line for t = 0. In order to provide clarification and enhance understanding, two well-known numerical examples are provided to demonstrate the suggested concept, along with their practical results implemented in MATLAB in tables and curves.

Authors

Publication Details

Journal
Journal of Information and Optimization Sciences
Published
2025-01-01
DOI
https://doi.org/10.47974/jios-1805
Primary Topic
Metaheuristic Optimization Algorithms Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modified Barzilai-Borwein (MBB) gradient method for solving fuzzy nonlinear equations

Marwan S. Jameel, Fanar N. Jardow
Journal of Information and Optimization Sciences
Metaheuristic Optimization Algorithms Research
article

Modified Barzilai-Borwein (MBB) gradient method for solving fuzzy nonlinear equations

Marwan S. Jameel, Fanar N. Jardow
article en

Abstract

Research has demonstrated that conventional analytical techniques such as the SD, BB, CG, and N approaches are insufficient to solve a collection of fuzzy non-linear equations that involve fuzzy number coefficients[1]. Because of this, the two-step extended gradient method is suggested as an alternative way to resolve these kinds of unclear nonlinear equations. This work uses a six-step technique to solve ambiguous nonlinear equations[7]. This method does not require the Jacobi method and only requires finding a line for t = 0. In order to provide clarification and enhance understanding, two well-known numerical examples are provided to demonstrate the suggested concept, along with their practical results implemented in MATLAB in tables and curves.

Journal of Information and Optimization SciencesVol. 46(5)
Openalex Percentile: Top 91%
Metaheuristic Optimization Algorithms Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.