Using an Artificial Neural Network to Forecast the Market Share of Thai Rice

被引：1
|
作者：
Apichottanakul, A. [1 ]
Piewthongngam, K. [2 ]
Pathumnakul, S. [3 ]
机构：
[1] Khon Kaen Univ, Grad Sch, Khon Kaen, Thailand
[2] Khon Kaen Univ, Fac Management Sci, Esaan Ctr Business & Econ Res, Khon Kaen, Thailand
[3] Khon Kaen Univ, Fac Engn, Dept Ind Engn, Khon Kaen, Thailand
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ENGINEERING AND ENGINEERING MANAGEMENT, VOLS 1-4 | 2009年
关键词：
Neural networks; back propagation; demand for rice; market share; POWDER-METALLURGY MATERIALS; PARAMETERS; SELECTION; MODEL;
D O I：
10.1109/IEEM.2009.5373247
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
In this paper, the artificial neural networks (ANN) is used to estimate the market share of Thai rice in the global market. Two models are formulated under two assumptions. First, the market share depending on exporting prices of rice of Thailand, Vietnam, India, USA, Pakistan, China. Second, only the, export prices of rice from Thailand, Vietnam, USA, and China are considered. The export prices are used as input parameters, while the market share of Thai's rice in the global market is the only output parameter of the models. Annual data from 1980 to 2005 are gathered from United States Department of Agriculture (USDA) and Food and Agriculture Organization of the United Nations (FAO). The study showed that the second model provide more promising results with the minimum mean absolute percent error (MAPE) of 4.69% and the average MAPE of 10.92%.
引用
收藏
页码：665 / 668
页数：4
相关论文
共 50 条
  • [1] Analyze of using fuzzy neural network in market share prediction
    Zhang Xiaoli
    [J]. Advanced Computer Technology, New Education, Proceedings, 2007, : 159 - 162
  • [2] Diabetes mellitus forecast using artificial neural network (ANN)
    Jaafar, Siti Farhanah Bt
    Ali, Darmawaty Mohd
    [J]. 2005 ASIAN CONFERENCE ON SENSORS AND THE INTERNATIONAL CONFERENCE ON NEW TECHNIQUES IN PHARMACEUTICAL AND BIOMEDICAL RESEARCH, PROCEEDINGS, 2005, : 135 - 139
  • [3] Day Ahead Hourly Load Forecast of PJM Electricity Market and ISO New England Market by Using Artificial Neural Network
    Sahay, Kishan Bhushan
    Tripathi, M. M.
    [J]. 2013 IEEE INNOVATIVE SMART GRID TECHNOLOGIES - ASIA (ISGT ASIA), 2013,
  • [4] Day Ahead Hourly Load Forecast of PJM Electricity Market and ISO New England Market by Using Artificial Neural Network
    Sahay, Kishan Bhushan
    Tripathi, M. M.
    [J]. 2014 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT), 2014,
  • [5] Artificial neural network model for soil moisture forecast in deficit irrigation rice field
    Zhou, MY
    Chen, HW
    [J]. Land and Water Management: Decision Tools and Practices, Vols 1 and 2, 2004, : 96 - 100
  • [6] Market Basket Analysis using Artificial Neural Network
    Bhargav, Anshul
    Mathur, Robin Prakash
    Bhargav, Munish
    [J]. 2014 INTERNATIONAL CONFERENCE FOR CONVERGENCE OF TECHNOLOGY (I2CT), 2014,
  • [7] Stock Market Prediction by Using Artificial Neural Network
    Yetis, Yunus
    Kaplan, Halid
    Jamshidi, Mo
    [J]. 2014 WORLD AUTOMATION CONGRESS (WAC): EMERGING TECHNOLOGIES FOR A NEW PARADIGM IN SYSTEM OF SYSTEMS ENGINEERING, 2014,
  • [8] Sequential forecast of incident duration using Artificial Neural Network models
    Wei, Chien-Hung
    Lee, Ying
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2007, 39 (05): : 944 - 954
  • [9] Autoregression and artificial neural networks for rinancial market forecast
    De Leone, R
    Marchitto, E
    Quaranta, AG
    [J]. NEURAL NETWORK WORLD, 2006, 16 (02) : 109 - 128
  • [10] The Forecast of Energy Demand on Artificial Neural Network
    Wang Jin-ming
    Liang Xin-heng
    [J]. 2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL III, PROCEEDINGS, 2009, : 31 - 35
12345