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Nonlinear programming problem solving based on winner take all emotional neural network for tensegrity structure design

Lotfi, N, Lotfi, E, Mirzaei, R, Khosravi, A and Nahavandi, Saeid 2016, Nonlinear programming problem solving based on winner take all emotional neural network for tensegrity structure design, in Proceedings of the International Joint Conference on Neural Networks, pp. 826-831, doi: 10.1109/IJCNN.2016.7727285.


Title Nonlinear programming problem solving based on winner take all emotional neural network for tensegrity structure design
Author(s) Lotfi, N
Lotfi, E
Mirzaei, R
Khosravi, A
Nahavandi, Saeid
Title of proceedings Proceedings of the International Joint Conference on Neural Networks
Publication date 2016-10-31
Start page 826
End page 831
Total pages 6
Summary © 2016 IEEE.In this paper, a tensegrity structure (TS) design is formulated as a nonlinear programming (NLP) problem, and a winner-take-all artificial emotional neural network (WTA-ENN) is proposed to solve the resulting NLP. The main feature of proposed WTA-ENN is related to low number of learning weights and simplicity of its learning rules that make it a suitable model for complicated TS design problems. Numerical results indicate that WTA-ENN can effectively solve NLP problem obtained from basic module of a typical TS Tower. The proposed method can be effectively used in architectural, structural and robotics design.
ISBN 9781509006199
DOI 10.1109/IJCNN.2016.7727285
Persistent URL http://hdl.handle.net/10536/DRO/DU:30092174

Document type: Conference Paper
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