The Application Of Data Mining Technique Based On Wavelet Neural Network In Marketing Prediction

Sale prediction holds an important position in aspects of increasing enterprises' economic profit and decision-making supporting level. With the improvement of enterprises' informationalization level and the increasingly richness of sale data, the managers' aspiration for hidden information on sale-prediction is increasingly strong. To analyze the sale information in the data of great capacity by traditional methods is very difficult and can't suit the requirement of the era any more. Therefore, it's a very important and worthy task to find a better method to mine the information on sale prediction hidden in sale data.The paper's research is based on the above said background. The paper carried out research in application of sale prediction with the data mining technique as means and Wavelet Neural Network as tool. The following work has been done: 1) Aiming at enterprises' requirement on sale prediction under new situation, we put forward that the application of data mining technique in sale prediction is an inevitable trend and construct a data mining system frame suitable for sale prediction based on predecessors. 2) Aiming at the limitation of existing method to predict sale volume and potential customer which are the two typical issues in sale prediction, we build wavelet neural network prediction model adapt to the two issues with the wavelet neural network as new method of data mining. 3) Aiming at the limitation of Back-propagation Algorithm commonly used in wavelet neural network at present, we study wavelet neural network by Genetic Back-propagation Algorithm. 4) We carried out positive analysis on the two typical issues by actual sale data in order to verify the validity and usability of the method proposed in the paper.From the result and the comparison of performances, the effect of prediction method by wavelet neural network is evident. The hidden information on sale volume and potential customer can be found in the set of sale data of great capability. Certainly, there're still many issues worthy of discussion in the application of data mining in sale prediction. The work done in the paper is only an experiment awaiting further research.