Open AccessHuman activity recognition based on extreme learning machine in smart home
Author(s) -
Shangfeng Chen,
Hongqing Fang,
Zhijian Liu
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1437/1/012076
Subject(s) - extreme learning machine , activity recognition , computer science , artificial intelligence , mode (computer interface) , pattern recognition (psychology) , machine learning , home automation , affect (linguistics) , speech recognition , human–computer interaction , artificial neural network , psychology , communication , telecommunications
This paper applies extreme learning machine (ELM)to human activity recognition in smart home, evaluates the human activity recognition model established by ELM. Experimental results show that the accuracy of activity recognition of ELM model is related to the number of hidden layer units. Too many/few hidden layer units can affect the performance of the ELM mode, apparently.