Rural Homestay Spatial Planning and Design Based on Bert BiLSTM EIC Algorithm in the Background of Digital Ecology

Abstract

There is a promising development prospect in the digital ecosystem. In this context, the spatial planning of rural homestays has also received widespread attention. The research aims to better explore the advantages and determine the development direction of rural homestays, while providing two-way demand support for consumers and managers. Therefore, this study combines bidirectional long-term and short-term memory networks, pre-trained models, and emotional information attention mechanisms in deep learning. A new emotional analysis model is proposed. Then it is applied to the spatial planning of homestays near Chengdu Normal University and Chengdu Neusoft University. The experimental results show that the accuracy, recall, and F1 values of the new emotion analysis model proposed in this research reach 94%, 93%, and 94%, respectively. In terms of consumer satisfaction with the spatial location of homestays before and after the renovation, the average score of homestays near Chengdu Normal University increases by 21% compared to before the renovation. The average score of homestays near Chengdu Neusoft University increases by 40% compared to before the renovation. In summary, the new emotional analysis model proposed in this research has certain feasibility and effectiveness in the planning of rural homestay spatial location, providing new ideas for homestay spatial location planning.