Name
Abstract | ||
|---|---|---|
In this paper, a representation of a recurrent neural network to solve quadratic programming problems with fuzzy parameters (FQP) is given. The motivation of the paper is to design a new effective one-layer structure neural network model for solving the FQP. As far as we know, there is not a study for the neural network on the FQP. Here, we change the FQP to a bi-objective problem. Furthermore, the bi-objective problem is reduced to a weighting problem and then the Lagrangian dual is constructed. In addition, we consider a neural network model to solve the FQP. Finally, some illustrative examples are given to show the effectiveness of our proposed approach. |
Year | DOI | Venue |
|---|---|---|
2018 | https://doi.org/10.1007/s10700-016-9261-9 | FO & DM |
Keywords | Field | DocType |
Quadratic programming problem with fuzzy parameters,Neural network model,Fuzzy mapping,Bi-objective problem,Weighting problem | Mathematical optimization,Lagrangian,Fuzzy logic,Recurrent neural network,Quadratic programming,Artificial neural network,A-weighting,Mathematics,Fuzzy mapping | Journal |
Volume | Issue | ISSN |
17 | 1 | 1568-4539 |
Citations | PageRank | References |
5 | 0.46 | 15 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Amin Mansoori | 1 | 58 | 5.31 |
| Effati Sohrab | 2 | 276 | 30.31 |
| Mohammad Eshaghnezhad | 3 | 54 | 3.91 |