Research and Application of Enterprise Operating Situation Prediction Based on Decision Tree

Ye Qin; Song Yang; Wei Wang; Xiao Dong Luo; Jian Li Cheng; Ting Ting Li

doi:10.4028/www.scientific.net/AMM.631-632.70

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 631-632Research and Application of Enterprise Operating...

Research and Application of Enterprise Operating Situation Prediction Based on Decision Tree

Abstract:

After years of stable operation, a group enterprise equity management information system has accumulated a large amount of historical operating data. At present, the enterprise operating situation analysis is primarily based on statistical inquiry, so we cannot find out the operational decisions information which includes future trends among the data, and that information are often deeply hidden. In this paper, the decision tree applying to the situation classification prediction is presented, including the construction of a professional field data warehouse, data preprocessing and discretization, decision tree algorithm and tree pruning optimization algorithm using weights. Through the experiment, the prediction accuracy may reach 95.8%. By use of enterprise operating situation analysis based on data mining technology, we can find out useful information for the enterprise management decision, strengthen the correct judgment in marketing operation and other aspects, thereby enhancing the market competitiveness.

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Periodical:

Applied Mechanics and Materials (Volumes 631-632)

Pages:

70-74

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.631-632.70

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Online since:

September 2014

Authors:

Ye Qin*, Song Yang, Wei Wang, Xiao Dong Luo, Jian Li Cheng, Ting Ting Li

Keywords:

Data Classification, Data Mining (DM), Decision Tree, Operating Situation

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