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This paper presents a new algorithm to produce a near optimal mixture of experts model (MEM) architecture for a continuous mapping. The MEM is applied to a new method incorporating photon scatter for designing compensators for intensity modulated radiation therapy. The algorithm utilizes the fuzzy C-means clustering algorithm to partition data before training commences. A reduction in the size of training sets also allows the Levenberg–Marquardt algorithm to be implemented. As a result, both training time and validation error are reduced. A 71% reduction in prediction error compared with that of a single neural network is achieved.
|Publication status||Published - Sep 2006|
Bibliographical noteThis paper is not yet available on the repository
FunderEngineering and Physical Sciences Research Council, Industrial Case Training award no. 02303507
- Committee machines
- Neural networks
- Fuzzy C-means
- Radiation therapy
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- 1 Finished
MAESTRO: Methods and Advanced Equipment for Simulation and Treatment in Radiation Oncology
Haas, O., Burnham, K., Skworcow, P. & Sahih, A.
1/05/04 → 30/04/09