(untitled) (International Journal of Engineering and Computer Science, 2016)
Neural Networks (NN) are important data mining (Extraction of Knowledge) tool used for classification and clustering (Grouping of nodes together). It is a branch of Artificial Intelligence which plays an important role in almost all field of science. It is an attempt to build machine that will mimic brain activities and be able to learn. NN usually learns by examples. If NN is supplied with enough examples, it should be able to perform classification and even discover new trends or patterns in data. If we consider the architecture point of view then, NN is composed of three layers, such as input, output and hidden layer. Each layer can have number of nodes and nodes from input layer are connected to the nodes from hidden layer. Nodes from hidden layer are connected to the nodes from output layer. Those connections represent weights between nodes. The Back Propagation (BP) Algorithm is one of most popular NN algorithms, which is applied in every sector of real time application. BP algorithm is quite simple, eases to handle and works on the principle of, output of NN, which is evaluated against desired output. If results are not satisfactory, connection (weights) between layers are modified and process is repeated again and again until error is small enough. In underground mine area, we apply this algorithm to determine the valuable data like, signal analysis, rock characterization, etc.