Optimal Design of Green Building Landscape Space Environment Based on Niche Genetic Algorithm

In view of the limitations of traditional image recognition algorithms in the optimal design of green building landscape space environment, a landscape space environment optimization design scheme based on niche genetic algorithm was proposed. Firstly, the influencing factors were accurately located through the adaptive degree theory, and the indicators were reasonably divided to reduce the interference, and the niche genetic algorithm was used to construct the optimal design scheme of landscape spatial environment. Experimental results show that under certain evaluation criteria, the proposed scheme is superior to the traditional image recognition algorithm in terms of the accuracy of landscape space environment optimization design and the processing time of influencing factors, and has obvious advantages. Landscape space environment optimization design plays an extremely important role in the green building landscape, which can accurately predict and optimize the growth characteristics and product generation of the green building landscape. However, traditional image recognition algorithms have certain limitations in solving space environment simulation problems, especially when dealing with complex problems. In this paper, this paper proposes an optimal design scheme of landscape spatial environment based on niche genetic algorithm to better solve this problem. In this scheme, the influencing factors were accurately located through the adaptive degree theory, so as to determine the division of indicators, and the niche genetic algorithm was used to construct the scheme. Experimental results show that under certain evaluation criteria, the accuracy and speed of the scheme is significantly improved for different problems, and it has better performance. Therefore, the simulation scheme based on niche genetic algorithm can better solve the limitations of traditional image recognition algorithms and improve the simulation accuracy and efficiency in the optimal design of green building landscape spatial environment.