基于新型模糊CMAC神经网络的Agent外贸协商模型  

Agent-based trade negotiation model based on a novel fuzzy CMAC

作　　者：曹晶[1] 张良均 郑巍[1] 许鸿 

机构地区：[1]广东技术师范学院,广东广州510630 [2]广州万友软件有限公司,广东广州510665

出　　处：《合肥工业大学学报（自然科学版）》2006年第11期1420-1424,共5页Journal of Hefei University of Technology：Natural Science

摘　　要：文章提出了一个由外销商训练的基于一种新型模糊小脑神经网络的Agent外贸协商模型。由于模糊小脑神经网络训练快速性,所以客户在输入了购买信息之后,可以及时获得相关评价,使客户最终能以协商的方式与Agent达成协议,提高了工作效率,仿真试验也证明了其评价的正确性。In this paper,the agent-based trade negotiation model trained by the salesman is presented. The model is based on a novel fuzzy cerebellar model articulation controller called FuCMAC. For its advantage of fast convergence,when information on purchasing is input by clients, the model can provide some related assessments for clients. So clients and the agent-based trade negotiation model can reach an agreement by negotiation, thus promoting the working efficiency. Simulation results demonstrate the correctness of the model.

关 键 词：小脑神经网络 模糊小脑神经网络 Agent协商模型 电子商务 

分 类 号：TP113[自动化与计算机技术—控制理论与控制工程]