A risk assessment model using artificial neural networks case study: National Iranian oil products distribution company (NIOPDC)

The world today is full of risks and we had to deal with besides assessing them. We are forced to identify and estimate their consequences. Organizations are making large investments in information technology (IT) projects. Effective management of risks in projects is therefore extremely important. The objective of this research is design of Artificial Neural Network (ANN) model for ranking risk of project in national Iranian oil products distribution company (NIOPDC). Used data is belonged to NIOPDC during the years 2005-2010. For design of ANN the neuro solution software is used. To obtain a network capable to demonstrate the connections between the inputs, an MLP with error back propagation is used. Considering the numbers of the inputs and the space of prioritization is scope of this research for solving the problem. We have used one hidden layer with maximum 16 neuron, 42 neuron in the input layer and 5 neuron in the output layer.