实现物联网自适应模糊神经网络模型赋能服务，支持时尚零售

Proceedings of the 4th International Conference on Machine Learning and Soft Computing Pub Date : 2020-01-17 DOI:10.1145/3380688.3380692

C. Chan, H. Lau, Youqing Fan

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引用次数: 2

摘要

时尚行业在一个快速发展和动态的环境中运作，这要求时装设计师不断对市场趋势做出反应。本研究探讨物联网(IoT)在时尚零售中的应用潜力。顾客在店内的行为可能反映了他们隐藏的偏好。这项研究是基于使用物联网作为数据收集工具的框架来捕捉顾客在店内的行为。人工智能(AI)，如模糊逻辑和自适应神经模糊推理系统(ANFIS)被用来分析客户的购买意图，仿真将被用来说明模型[1]。本研究表明，物联网可以获取客户行为所需的数据，并使用AI分析偏好。它可以在店内使用，帮助销售人员更快、更准确地响应顾客的需求。分析后得到的数据可用于供应链规划。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Implementing IoT-Adaptive Fuzzy Neural Network Model Enabling Service for Supporting Fashion Retail

The fashion industry operates in a fast moving and dynamic environment which requires fashion designers to respond to market trends continuously. This study investigates potential for application of Internet of Things (IoT) in fashion retail. Customer in-store behaviors may reflect their hidden preferences. This study is based on use of IoT as a framework of data collection tools to capture customer behaviors in-store. Artificial intelligence (AI) such Fuzzy logic and Adaptive Neuro-Fuzzy Inference System (ANFIS) are used to analyze customer purchasing intentions and simulation will be used to illustrate the model [1]. This study shows that IoT can obtain the required data of customer behaviors and use AI to analyze the preferences. It can be used in-store to help salespersons to respond to customer needs faster and accurately. The data obtained after analyzing can be used in supply chain planning.

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Proceedings of the 4th International Conference on Machine Learning and Soft Computing

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