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IJAT Vol.4 No.2 pp. 178-183
doi: 10.20965/ijat.2010.p0178
(2010)

Paper:

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Development of Neural-Net-Based Decision Support System for Mattress Patterns Using Particle Swarm Optimization

Mitsue Kato* and Toru Yamamoto**

*Teisei Gakuen Junior College, 1-26-13 Kohinata, Bunkyo-ku, Tokyo 112-8630, Japan

**Hiroshima University, 1-1-1 Kagamiyama, Higashi Hiroshima, Hiroshima 739-8511, Japan

Received:
December 1, 2009
Accepted:
January 8, 2010
Published:
March 5, 2010
Creative Commons License
Keywords:
neural network, evolutionary computation, learning, particle swarm optimization, metaheuristics
Abstract
The particle swarm optimization (PSO) concept simulating a simplified social milieu, is optimization useful for solving nonconvex continuous optimization problems. We discuss a new learning algorithm for simultaneously adjusting connection weights in neural networks and user-specified parameters included in units. Based on our algorithm, neural network learning, e.g., learning cost or adaptability, can be improved, as demonstrated in mattress decision support system.
Cite this article as:
M. Kato and T. Yamamoto, “Development of Neural-Net-Based Decision Support System for Mattress Patterns Using Particle Swarm Optimization,” Int. J. Automation Technol., Vol.4 No.2, pp. 178-183, 2010.
Data files:
References
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Last updated on Apr. 22, 2024