Rural landscape design strategy based on deep learning model

Abstract

In order to scientifically allocate rural landscape resources, reasonably plan rural tourism space, and ensure that the local characteristics of the countryside are not homogenized when carrying out rural landscape design, this paper studies rural landscape design strategies based on deep learning models. The extreme learning machine algorithm, DBN-RBM algorithm model and the improved DBN-DELM algorithm are the main technical means to obtain research data and parameter calibration results for tourism planning and development work, and the rural planning direction and planning theme is determined through the rural landscape design pre-analysis work. The data show that the main motives of tourists’ rural experience tourism are close to nature 85.90% and leisure vacation 75%, followed by understanding culture 45.30%, novelty 30.70%, parent-child education 29.20%, health retreat 30.40%, and business meeting 5.90%. In this paper, the study of rural landscape planning and design can effectively alleviate the contradiction between people’s production and living and ecological environment and coordinate the benign development of rural and tourism elements in their respective spaces.