A knowledge-based intelligent electronic commerce system for selling agricultural products

被引:63
作者
Wen, W.
机构
[1] Department of Information Management, LungHwa University of Science and Technology
关键词
knowledge-based intelligent system; e-commerce; rule base; model base;
D O I
10.1016/j.compag.2007.01.016
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
This paper presents a knowledge-based intelligent e-commerce system for selling agricultural products. The KIES system not only provides agricultural products sales, financial analysis and sales forecasting, but also provides feasible solutions or actions based on the results of rule-based reasoning. The intelligent system integrates a database, a rule base and a model base to create a tool of which managers can use to deal with decision-making problems via the Internet. Rules in the rule base are explained in detail to illustrate the processes of reasoning. Also, an automatic and practical inference engine that provides monitoring and controlling a verity of processes is presented to show how the system can deal with knowledge management. In order to obtain more profits and manage future change, artificial neural network models in the model base have been developed and compared for demand forecasting. Finally, for offering convenient delivery and user-friendly services to customers, an e-map combined with a GPS is used. (c) 2007 Elsevier B.V. All rights reserved.
引用
收藏
页码:33 / 46
页数:14
相关论文
共 28 条
[1]   Enhancing customer value through click-and-mortar e-commerce: Implications for geographical market reach and customer type [J].
Adelaar, Thomas ;
Bouwman, Harry ;
Steinfield, Charles .
Telematics and Informatics, 2004, 21 (02) :167-182
[2]   Artificial neural networks as applied to long-term demand forecasting [J].
Al-Saba, T ;
El-Amin, I .
ARTIFICIAL INTELLIGENCE IN ENGINEERING, 1999, 13 (02) :189-197
[3]   The development of intelligent decision support tools to aid the design of flexible manufacturing systems [J].
Chan, FTS ;
Jiang, B ;
Tang, NKH .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2000, 65 (01) :73-84
[4]  
ERIKSSON H, 1996, IEEE EXPERT JUN, P14
[5]   ARTIFICIAL NEURAL NETWORKS - A NEW METHODOLOGY FOR INDUSTRIAL MARKET-SEGMENTATION [J].
FISH, KE ;
BARNES, JH ;
AIKEN, MW .
INDUSTRIAL MARKETING MANAGEMENT, 1995, 24 (05) :431-438
[6]   Enabling information sharing between E-commerce systems for construction material procurement [J].
Kong, SCW ;
Li, H ;
Hung, TPL ;
Shi, JWZ ;
Castro-Lacouture, D ;
Skibniewski, M .
AUTOMATION IN CONSTRUCTION, 2004, 13 (02) :261-276
[7]   A decision support system for sales forecasting through fuzzy neural networks with asymmetric fuzzy weights [J].
Kuo, RJ ;
Xue, KC .
DECISION SUPPORT SYSTEMS, 1998, 24 (02) :105-126
[8]   The development of a hybrid intelligent system for developing marketing strategy [J].
Li, SL .
DECISION SUPPORT SYSTEMS, 2000, 27 (04) :395-409
[9]   A framework for applying intelligent agents to support electronic trading [J].
Liang, TP ;
Huang, JS .
DECISION SUPPORT SYSTEMS, 2000, 28 (04) :305-317
[10]   Knowledge acquisition and representation for expert systems in the field of financial analysis [J].
Matsatsinis, NF ;
Doumpos, M ;
Zopounidis, C .
EXPERT SYSTEMS WITH APPLICATIONS, 1997, 12 (02) :247-262