@article {25568,
	title = {An efficient RADFET sensors model using Artificial Neural Network (ANN)},
	journal = {Key Engineering Materials},
	volume = {644},
	year = {2015},
	pages = {196-202},
	abstract = {In this work, a new approach is proposed to design the neutron angle and fluence radiation sensor. It is based on an Artificial Neural Network (ANN) model which has the advantage of efficient nonlinear mapping in addition to noise tolerance. This model allows us to obtain the angle and the fluence radiation from the drain source current, the drain source voltage, the gate source voltage and the temperature parameters. The obtained results are nearly closed to the experimental results in the literature.},
	url = {https://www.scientific.net/KEM.644.196},
	author = {Fay{\c c}al Meddour and Zohir Dibi and Souhil KOUDA and Fay{\c c}al DJEFFAL}
}
