Application of interactive Genetic Algorithm in landscape planning and design - Li, Boyang; Sharma, Ashutosh (Informatica, 2022)
In order to improve the design effect of garden landscape space environment and optimize the structure of garden landscape space environment, an optimization design method of garden landscape space environment based on interactive genetic algorithm was proposed. Landscape space environment design is built with image visual feature space distributed monitoring model and fuzzy pixel area feature fusion reconstruction model, and the landscape space environment design of the image by multistage decomposition and pixel gray characteristics, established landscape space environment design image visual feature reconstruction model. The method also combines block area template matching method is landscape space environment design of the image features visual reconstruction and visual space distributed detection, information fusion using similarity model reconstructs the landscape space environment design of image visual perception process of information fusion, in order to extract fuzzy characteristic landscape space environment design of the image, Finally, interactive genetic algorithm is used to realize the quality assessment of landscape art information fusion perception and visual reconstruction. The simulation results show that compared with the traditional method, the visual reconstruction quality of landscape spatial environment design image processed by this method is better, the image recognition accuracy is higher, and the output signal-to-noise ratio is improved by 14.6%. The experimental results prove that the introduction of interactive genetic algorithm in landscape planning and design can effectively solve the problems of multi-level feature decomposition and pixel feature separation in the process of landscape design, optimize the landscape spatial environment structure, and achieve good landscape spatial environment design effect.