基于神经网络的智能家居模式识别方法研究
首发时间:2013-08-28
摘要:为提高智能家居体系架构的智能程度,研究在智能家居的环境下,长期采集用户在日常生活中产生的数据,并将数据与神经网络算法相结合。在原有智能家居系统的基础上,将大量的采集数据预处理,结合物联网和模式识别相关理论知识,基于双层ART1型神经网络算法,将数据的反复训练,形成一套成熟、稳定、可靠的反映不同用户生活习惯的智能家居模式集,将智能家居系统设计成一个闭环的、智能化的生态系统。研究提出的智能家居模式识别方法,便于提取用户行为的兴趣偏好,可以为智能家居理论研究提供理论素材和技术导向,为智能家居产业和相关物联网行业提供一套模式识别和智能化管理的解决方案。
关键词: 物联网 智能家居 数据挖掘 用户行为 模式识别 ART神经网络
For information in English, please click here
Research on the Method of Smart Home Pattern Recognition Based on Neural Network Algorithm
Abstract:In order to promote the intelligence degree of smart home system, this paper designed a method by building a system-collecting data produced in users' daily life and introducing double layers ART1 Neural Network Algorithm (NNA) for data processing. This system preprocesses collected data to get significant data sets. Double layers ART1 NNA algorithm helps the system extract users' interests and preferences in large data sets and transform it into a mature and stable pattern, which reflecting different users' life model. Thus, with this system, smart home system can be intelligent and closed-loop ecosystem. The method provides theoretical material and technical guidance for smart home theory research, also, providing a set of solutions to pattern recognition and intelligent management for smart home industry and related Internet of things industry.
Keywords: Internet of things smart home data mining user behavior pattern recognition ART Neural Network Algorithm
基金:
论文图表:
引用
No.****
同行评议
共计0人参与
勘误表
基于神经网络的智能家居模式识别方法研究
评论
全部评论