predicting oil well site projects cost in oil-rich regions south of iran using neural networks

predicting oil well site projects cost in oil-rich regions south of iran using neural networks

cost is one of the fundamental factors in project implementation and completion, whereas prediction is a key principle of project management. when predicting the project cost, a process is implemented in the project which makes it run within a specific framework with predefined costs, thus preventing possible cost deviations. neural network modeling is one of the cost prediction methods.

this method has a prominent place in engineering sciences due to the ability to model complex relationships between variables. this paper used 22 key parameters in oil-well site projects in the south-iranian oil-rich regions as input for the neural network model and matlab program in order to predict project implementation and completion costs. after modeling the neural network, considering the error and correlation coefficients and after comparing the neural network outputs vs. the cost estimates and error assessment, it appears that the proposed neural network and model can predict the costs of such projects with acceptable error.