%0 Journal Article %A Gitanjali Devi and Kandarpa Kumar Sarma and Pranayee Datta and Anjana Kakoti Mahanta %D 2011 %J International Journal of Physical and Mathematical Sciences %B World Academy of Science, Engineering and Technology %I Open Science Index 58, 2011 %T Prediction of Location of High Energy Shower Cores using Artificial Neural Networks %U https://publications.waset.org/pdf/1674 %V 58 %X Artificial Neural Network (ANN)s can be modeled for High Energy Particle analysis with special emphasis on shower core location. The work describes the use of an ANN based system which has been configured to predict locations of cores of showers in the range 1010.5 to 1020.5 eV. The system receives density values as inputs and generates coordinates of shower events recorded for values captured by 20 core positions and 80 detectors in an area of 100 meters. Twenty ANNs are trained for the purpose and the positions of shower events optimized by using cooperative ANN learning. The results derived with variations of input upto 50% show success rates in the range of 90s. %P 1634 - 1640