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
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.
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