A Method of Predicting Crude Oil Output Based on RS-C4.5 Algorithm

An accurate prediction of crude oil output is crucial to oilfield enterprise in reasonable production arrangement and the production management improvement. This paper proposes a RS-C4.5 data mining method based on the rough set theory and decision tree C4.5 algorithm to predict the crude oil output. Firstly, relevant data of crude oil production is pre-processed by K-Means algorithm to obtain a discrete decision-making data set. Next the attribute reduction by RS-C4.5 algorithm is applied to construct a decision tree to obtain the corresponding rules of classification. Experiment data proved that compared with the traditional decision tree C4.5 algorithm, this algorithm has the advantage of a simpler tree structure and higher operation efficiency, thus becoming a promising method in crude oil output prediction.