PRODUCT PRICE FORECASTING BASED ON CORRELATIVE PRICE NET AND NEURAL NETWORKS

Authors

  • Hong-Sen Yan Southeast University
  • Nan-Yun Jiang Southeast University
  • Wen-Wu Shi Southeast University
  • Xian-Gang Meng Southeast University
  • Tian-Hua Jiang Southeast University

DOI:

https://doi.org/10.23055/ijietap.2017.24.3.2381

Keywords:

industrial engineering, manufacturing engineering

Abstract

The manufacturing enterprise need price forecasting in order to attain maximum profit and guild production. However, it is difficult to trace the changing rules of their historical data since product price may fluctuate abruptly. Therefore, a price forecasting method based on correlative price net and neural networks is proposed in the paper. Firstly, by analyzing the main factors to product price changes, a model of correlative price net (CPN) that connects many products whose prices affect each other is set up. Then, the theoretical proof that the whole CPN can be substituted by its correlative price sub-net for price forecasting is provided. Based on the correlative price sub net, a set of BP neural networks are introduced for building a new network, named the price forecasting net (PFN), which can reflect the factors of price fluctuation in the correlative price sub net. Finally, since the change of factors in the correlative price sub net relates to the variation of product price caused by it, the product price can be forecasted on basis of the change of factors in the correlative price sub net by means of PFN. The theoretic analysis and simulation experiment show that the proposed method adapts well to product price forecasting, especially when prices change abruptly.

Author Biographies

Hong-Sen Yan, Southeast University

Hong-Sen Yan received the B.S. degree in automatic control from the Harbin Ship Building Engineering Institute,Harbin,China, in 1982 and the M.S. degree in industrial automation and the Ph.D. degree in automatic control theory and application from the Harbin Institute of Technology,Harbin, in 1989 and 1992, respectively.

From February 1982 to August 1986, he was an Assistant Engineer with the Yangzhou Marine Electronic Instruments Institute, Yangzhou, China. From July 1992 to June 1994, he was a Postdoctoral Fellow with the CIMS Laboratory, Department of Mechanical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, China. From July 1994 to March 1998, he was an Associate Professor with the Research Institute of Automation, SoutheastUniversity, Nanjing, where he was a Professor from April 1998 to September 2007. Since October 2007, he has been a Professor with the MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering, and the Superintendent of the Research Institute of Control and Optimization of Manufacturing Systems, Schoolof Automation, SoutheastUniversity. He is the founder of knowledgeable manufacturing and knowledge meshes theory. He has been engaged in or finished the design and development of four computer-integrated manufacturing systems in enterprises with his colleagues. He has authored or coauthored more than 210 research papers in refereed journals such as Applied Artificial Intelligence, Computers and Industrial Engineering, Computers in Industry, Concurrent Engineering: Research & Applications, European Journal of Operational Research, Expert Systems with Applications, IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Engineering Management, IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Neural Networks, IEEE Transactions on Systems, Man and Cybernetics, Part A, IIE Transactions, Information Sciences, International Journal of Advanced Manufacturing Technology, International Journal of Computer Integrated Manufacturing, International Journal of Industrial Engineering, International Journal of Production Research, Journal of Intelligent and Fuzzy Systems, Journal of Intelligent Manufacturing, Journal of Optimization Theory and Applications, Journal of the Operational Research Society, Proceedings of IMechE Part B: Journal of Engineering Manufacture, and Robotics and Computer-Integrated Manufacturing. His research interests include flexible manufacturing systems, computer integrated manufacturing systems (CIMS), agile manufacturing, concurrent engineering, and knowledgeable manufacturing systems.

Dr. Yan is a Senior Member of theInstituteofIndustrial Engineers, a director of the Chinese Association for Artificial Intelligence, a Director of the Jiangsu Association of Automation inChina, and a Senior Member of the Chinese Mechanical Engineering Society. He won the Best Journal Paper Prize for one of the best 200 papers selected from the 2001–2005 years’ papers in the 283 journals sponsored by 105 institutes, societies, institutions, and associations of the China Association for Science and Technology, and also seven other prizes from the State, the ministry, the province, and universities. 

Nan-Yun Jiang, Southeast University

Nan-Yun Jiang is a doctoral candidate in the MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering andSchool ofAutomation at Southeast University of China. Her major research interest is integrated optimization of production planning and scheduling. 

Wen-Wu Shi, Southeast University

Wen-Wu Shi received the Ph.D. degree in the MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering and School of Automation at Southeast University of China in 2007. His major research interest is the self-learning problem of knowledgeable manufacturing systems. His recent publications have appeared in some peer reviewed journals such as Journal of Intelligent and Fuzzy Systems, etc.

Xian-Gang Meng, Southeast University

Xian-Gang Meng received the Ph.D. degree in the MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering and School of Automation at Southeast University of China in 2010. He currently works in School of Automation at Tianjin University of Technology of China.

Tian-Hua Jiang, Southeast University

Tian-Hua Jiang is a doctoral candidate in the MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering and School of Automation at Southeast University of China. His major research interest is the self-evolution problem of knowledgeable manufacturing systems. His recent publications have appeared in some peer reviewed journals such as Journal of Intelligent and Fuzzy Systems, Proceedings of IMechE Part B: Journal of Engineering Manufacture, etc.

Published

2017-10-29

How to Cite

Yan, H.-S., Jiang, N.-Y., Shi, W.-W., Meng, X.-G., & Jiang, T.-H. (2017). PRODUCT PRICE FORECASTING BASED ON CORRELATIVE PRICE NET AND NEURAL NETWORKS. International Journal of Industrial Engineering: Theory, Applications and Practice, 24(3). https://doi.org/10.23055/ijietap.2017.24.3.2381

Issue

Section

Logistics and Material Handling

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