Visualization and Interaction Model of Outdoor Landscape Design Based on Virtual Reality Technology using Optimized Sparse Spectra Graph Convolutional Neural Network

Abstract

The artistic thought of traditional garden landscape design has significant effect on garden art, architectural theory, gardening theory are also inextricably linked. In modern gardens, traditional architecture lacks applicability to construction of garden painting environment. In this Manuscript, Visualization and Interaction Model of Outdoor Landscape Design Based on Virtual Reality Technology using Optimized Sparse Spectra is Graph Convolutional Neural Network is proposed (VIM-OLD-VRT-SSGCNN).Initially the data is collected fromArcbazer.com data. Afterwards sparse spectra graph convolutional neural network (SSGCNN) is used to design the Outdoor Landscape. In Generally, SSGCNN doesn’t expose some adoption of optimization systems for calculating optimal parameters for exactly design the Outdoor Landscape. Hence, Piranha Foraging optimization Algorithm (PFOA) is proposed to optimize SSGCNN which precisely design Outdoor Landscape. Finally Visualization and Interaction Model of Outdoor Landscape Designed. The proposed VIM-OLD-VRT-SSGCNN method is implemented python and performance metrics likes accuracy, precision, F1-score, sensitivity, specificity, computational time, RoC are evaluated. The performance of VIM-OLD-VRT-SSGCNN method provides 18.31%, 20.72%, 21.67% greater accuracy, 17.83%, 18.42%, 20.38% greater precision and 21.75%, 22.36%, 23.59% greater computational time while compared with existing techniques like Utilizing Deep Learning to Generate Font with Backyards in Landscape Architecture(UDL-GFB-LA), Urban Landscape Design Depend on Data Fusion with Computer Virtual Reality Technology (ULD-DF-CVRT),perception of urban sounds cape and landscape utilizing different visual environment reproduction techniques in virtual reality (PUSL-DVER-VR) respectively.