Landscape Ecological Construction and Spatial Pattern Optimization Design Based on Genetic Algorithm Optimization Neural Network

Abstract

With the development of computer visual information processing technology, designers use visual image processing methods to analyze and extract the features of landscape ecological space environment, establish visual reconstruction models of landscape ecological construction and spatial pattern optimization design images, and improve their ability to identify and reconstruct the artistic features of landscape ecological space environment. In this paper, a landscape ecological construction and spatial pattern optimization design scheme based on NN and GA is put forward. In the process of image visual reconstruction of landscape ecological construction and spatial pattern optimization design, urban ecological landscape information fusion perception and block area template matching are carried out to realize urban ecological landscape design. Finally, simulation test and analysis are carried out. The results show that the accuracy of this algorithm is high, which is 9.34% higher than that of traditional GA. This method can effectively reduce the iteration times and running time of the algorithm and improve the efficiency of landscape space optimization design. Carrying out the research on ecological planning and design with landscape ecological protection and restoration as the core has important practical guiding significance for guiding all localities to construct landscape ecological security pattern and promote green urbanization.