"Applications of Artificial Neural Networks in Physics"

Abstract

The term Artificial Inteligence refers to systems or devices that simulate human intelligence to perform tasks that can improve themselves based on the information they collect. Artificial intelligence manifests itself in a number of forms. Artificial intelligence is more about the ability to think and analyze data than it is about a specific shape or function. Neural networks are a model of intelligence models and are known as (Nodes, Neurons) to watch them with the property of experience, experimental information, to make them, by adjusting the weights. It is analogous to the human brain in an industry that gains knowledge by training and stores knowledge using forces within neurons called synaptic weights. There is also a dynamic ring, which gives biologists the opportunity to draw on these networks to understand the evolution of biological phenomena. The present work deals with a theoretical study of some parameters in solid state and in p-p collisions at high energy in the framework of Artificial intelligence (AI) which contains the model of Artificial Neural Network (ANN) for simulation these parameters and also prediction the values of experiments that have not been made yet with describing them by mathematical function obtained from obtained this model. The first chapter : This chapter deals with a concept the Artificial intelligence , Philosophy of AI , Goals of AI , What Contributes to AI? , Programming without and with AI , Applications of AI. In the second chapter: We discussed the study of one model from Artificial Intelligence (AI) which is the model of the Artificial Neural Network for studying some photovoltaic characteristics of NiPc/p-Si and some characteristics of p-p interactions .This chapter explains philosophy of AI , goals and techniques of AI , classification and task domain of AI, difference between Human and Machine