A regression-tree-based model for mining capital cost estimation

ABSTRACT

Determination of mining capital cost always is a challenging issue for mining engineer. Underestimating the capital cost may postpone the construction and production phases. In addition, overestimating may decrease value of the project. Currently available capital cost estimation models cannot predict mining capital cost in a reliable range of error. Therefore, in this paper, a model based on regression tree method is developed to estimate the mining capital cost. According to the obtained results, the capability of presented model to estimate the mining capital cost in a wide range of mining capacity is significant.

KEYWORDS:

• Capital cost estimation
• initial investment
• regression tree
• machine learning

Acknowledgment

We have to express our appreciation to the National Iranian Copper Industry CO. (NICICO) for sharing their available data with us during the course of this research. These data have been extracted from a report document which has been purchased by NICICO from CRU Group Company.

Disclosure statement

No potential conflict of interest was reported by the authors.