TY  - JOUR
T1  - Neural Network Prediction of Electromagnetic Field Strength in Hybrid Micro-Grid System
AU - Abdalla, Ahmed N. AU - Haidar, Ahmed M.A. AU - Ahmed, Ibrahim A. 
JO  - International Journal of Soft Computing
VL  - 5
IS  - 2
SP  - 62
EP  - 66
PY  - 2010
DA  - 2001/08/19
SN  - 1816-9503
DO  - ijscomp.2010.62.66
UR  - https://makhillpublications.co/view-article.php?doi=ijscomp.2010.62.66
KW  - electromegnatic field
KW  -Probabilistic neural network
KW  -electromagnetic interference
KW  -hybrid micro-grid system
KW  -dalaset
KW  -Malaysia
AB  - Location of any Hybrid Micro-Grid System requires efficiently prediction of the electromagnetic field strength. This study proposes a novel Electromagnetic Field Strength (EFS) predication based on Probabilistic Neural Network (PNN). Learning data sets have been generated using Electromagnetic Transients Program EMTP. The PNN model has three input nodes representing the Switching Distance, Busbar Interference Voltage and Current waveforms, the output node representing the EFS. Testing datasets have deliberately been chosen outside the region of the learning datasets so as to check the performance of the neural network. The results indicate that the proposed technique can be used successfully to detect the maximum Electromagnetic Field Strength Level at any Location.
ER  -