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.
2016 3rd International Conference on Information Science and Control Engineering (ICISCE)