Deep Learning based Models for identifying Healthy Aging People

There is a correlation between the urban environment and senior health. Macau’s high population density, however, means that its small urban area will soon have to accommodate an increasingly greying population. The link between the elderly in Macau and urban space is an area that has received little attention in the previous research. This study uses Baidu Street order to assess the association among the, and the physical and mental health of the health. In this research, the Tasmanian Devil optimization (TDO) technique is used to choose the most important features for the identification process. This research proposes a novel detection model that makes use of LSTM and the Spotted Hyena Optimizer (SHO). Features are added to the LSTM network’s vector space using the Skip-gram method. The SHO technique is used to optimise the initial weight of the LSTM network in the new model. In LSTM, adjusting the weight matrix is one of the trickiest parts. An accurate output may be expected if the neurons’ weights are also correct. Based on the collective hunting strategies of spotted hyenas, the SHO technique. In this method, the hyena represents a different possible solution to the issue. The other hyenas then follow the leader hyena to the best possible solution. The findings demonstrate that the statistics accurately portray the current state of public space on the Macau Peninsula.