Radial Basis Function Neural Network Model for Optimizing Thermal Annealing Process Operating Condition
Optimum thermal annealing process operating condition for nanostructured porous silicon (nPSi) by using radial basis function neural network (RBFNN) was proposed. The nanostructured porous silicon (nPSi) layer samples prepared by electrochemical etching process (EC) of p-type silicon wafers under di...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
scientific.net
2013
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/4705/ http://umpir.ump.edu.my/id/eprint/4705/ http://umpir.ump.edu.my/id/eprint/4705/ http://umpir.ump.edu.my/id/eprint/4705/1/Radial_Basis_Function_Neural_Network_Model_for_Optimizing_Thermal_Annealing_Process_Operating_Condition.pdf |