Abstract: There are many kinds of raw materials required, and the market price of materials is affected by the price of raw materials. Under such conditions, the price of raw materials has changed, but the market price of materials has not changed. In order to improve the effect of prediction, it is necessary to obtain the time delay of price. This study uses binary density clustering method combined with DTW ( Dynamic Time Warping ) algorithm, to calculate the similarity between the market prices of commodities over different time intervals and the trends in raw material prices. It has been determined that the market prices of commodities lag behind the fluctuations in raw material prices by 11 weeks. As a result, the market price of cable materials can be predicted based on the trends in raw material prices from 11 weeks ago. This information can assist the procurement department of businesses in formulating rational procurement strategies.

Key words: forecast price, binary density clustering, dynamic time warping(DTW), data fusion