基于多Agent技术的服装合体性智能评价系统

针对服装网络营销过程中合体性评价个性化服务缺乏的问题,基于层次分析法(AHP)、模糊集合理论和人工心理理论提出了服装合体性智能评价模型,并阐述了模型各部分实现过程.同时,提出了基于多Agent技术的服装合体性智能评价系统实现框架,详细叙述了系统中各Agent的角色职能以及系统操作流程.该系统能较好地改善在线服装购物环境和为顾客提供实用的购物决策参考,具有一定的通用性和广泛的应用前景.     

AHP-Based Optimal Selection of Garment Sizes for Online Shopping

Garment online shopping has been accepted by more and more consumers in recent years. In online shopping, a buyer only chooses the garment size judged by his own experience without trying-on, so the selected garment may not be the fittest one for the buyer due to the variety of body＇s figures. Thus, we propose a method of optimal selection of garment sizes for online shopping based on Analytic Hierarchy Process （AHP）. The hierarchical structure model for optimal selection of garment sizes is structured and the fittest garment for a buyer is found by calculating the matching degrees between individual＇s measurements and the corresponding key-part values of ready-to-wear clothing sizes. In order to demonstrate its feasibility, we provide an example of selecting the fittest sizes of men＇s bottom. The result shows that the proposed method is useful in online clothing sales application.