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模糊控制和神经网络预测在智能管家系统中的应用研究
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Abstract:
智能家居主要以智能感知终端对电器设备或用户的行为习惯进行数据采集，结合物联技术将各项数据上传至云端。为了提供便捷的交互方式和多指标控制策略，本文研究了模糊控制算法和神经网络预测算法在智能管家系统中的应用。采用模糊控制算法对环境内的多项参数进行模糊融合，并且利用用户的日常活动数据来预测用户未来的活动行为，通过MATLAB仿真验证，模糊结果符合实际应用场景，神经网络预测得到的行为时间点与实际用户时间误差保持在3%以下。同时通过云平台和语音识别装置实现了人机交互，提高智能管家系统操作的便捷性，实现家居的智能化管理。
With the development of the Internet of Things (IoT) technology, intelligent sensing terminals equipped in smart homes can achieve the collection of electrical equipment or user behaviour and upload the collected data to the cloud. In this paper, fuzzy control algorithm and neural network prediction algorithm are applied to the smart housekeeping system to provide convenient interaction and precise control strategy. The fuzzy control algorithm can blur a large number of parameters of the indoor environment. Based on the results of the fuzzy control algorithm and the actual activities of the user, the neural network prediction algorithm is used to predict the future performance of the user. A case study through MATLAB software shows that the fuzzy results satisfy the application in real scenarios. The error between the time point of the behaviour predicted by the neural network and the actual user can be less than 3%. Therefore, the device with cloud platform and voice recognition function achieves human-computer interaction and intelligent management of the house. In addition, the ease of operation of the intelligent housekeeping system is greatly improved.
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