Artificial Neural Network Modeling in Hadrons Collisions
نویسنده
چکیده
Evolutions in artificial intelligence (AI) techniques and their applications to physics have made it feasible to develop and implement new modeling techniques for high-energy interactions. In particular, AI techniques of artificial neural networks (ANN) have recently been used to design and implement more effective models. The neural network (NN) model and parton two fireball model (PTFM) have been used to study the charged particles multiplicity distributions for antiproton-neutron ( n p ) and proton-neutron ( n p ) collisions at different lab momenta. The neural network model performance was also tested at non-trained space (predicted) and matched them effectively. The trained NN shows a better fitting with experimental data than the PTFM calculations. The NN simulation results prove a strong presence modeling in hadrons collisions. Index Terms —. Neural Network Model; Parton Model; Multiparticle Production. —————————— ——————————
منابع مشابه
Modeling and Simulation of Water Softening by Nanofiltration Using Artificial Neural Network
An artificial neural network has been used to determine the volume flux and rejections of Ca2+ , Na+ and Cl¯, as a function of transmembrane pressure and concentrations of Ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. The feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidde...
متن کاملOptimization of Plastic Injection Molding Process by Combination of Artificial Neural Network and Genetic Algorithm
Injection molding is one of the most important and common plastic formation methods. Combination of modeling tools and optimization algorithms can be used in order to determine optimum process conditions for the injection molding of a special part. Because of the complication of the injection molding process and multiplicity of parameters and their interactive effects on one another, analytical...
متن کاملComparison between artificial neural network and radiobiological modeling for prediction of thyroid gland complications of after radiotherapy
Introduction: Hypothyroidism is one of the frequent side effects of radiotherapy of head and neck cancers, breast cancer, and Hodgkin's lymphoma. It is recommended to estimate the normal tissue complication probability of thyroid gland using radiobiological modeling during treatment planning. Moreover, the use of artificial neural network is also proposed as a new method for t...
متن کاملCell Deformation Modeling Under External Force Using Artificial Neural Network
Embryogenesis, regeneration and cell differentiation in microbiological entities are influenced by mechanical forces. Therefore, development of mechanical properties of these materials is important. Neural network technique is a useful method which can be used to obtain cell deformation by the means of force-geometric deformation data or vice versa. Prior to insertion in the needle injection pr...
متن کامل