A New Multivariate Markov Chain Model with Applications to Sales Demand Forecasting

摘要：

Markov chains are popular tools for modeling a lot of practical systems such as queueing systems, manufactur-ing systems and categorical data sequences. Multiple categorical sequences occur in many applications such as inventory control, finance and data mining. In many situations, one would like to consider multiple categorical sequences together at the same time. The reason is that the data sequences can be correlated and therefore by exploring their relationships, one can develop better models. In this paper, we propose a new multivariate Markov chain model for modeling multiple categorical data sequences. W.?then test, the proposed model with synthetic data and apply it to practical sales demand data.

关键词： Inventory Markov Process Multivariate Markov Chains Categorical Data Sequences Demand Prediction

作者: Wai-Ki CHING Li-Min LI Tang LI Shu-Qin ZHANG

作者单位: Advanced Modeling and Applied Computing Laboratory and Department of Mathematics,The University of Hong Kong,Pokfulam Road,Hong Kong,China

会议类型: 国际会议

会议名称: 工业工程与系统管理2007年国际会议(International Conference on Industrial Engineering and Systems Management)(IESM 2007)

会议地点: 北京

会议语种:英文

在线出版日期: 2007-05-30（万方平台首次上网日期，不代表论文的发表时间）