Application of Neural Network Model Based on Multispecies Evolutionary Genetic Algorithm to Planning and Design of Diverse Plant Landscape

Abstract

In order to explore the feasibility of applying neural network model to landscape planning, based on the multispecies evolutionary genetic algorithm, a neural network model is proposed in this paper for the system design of diverse plant landscape planning. From the perspective of plant species diversity, this paper discusses landscape planning based on a neural network model. This landscape plan involves more than 180 plant species, mainly shrubs, fungi, and so on. The application of multispecies evolutionary genetic algorithm to landscape planning and design and the application of gene level coding and multispecies parallel evolution strategy to the evolutionary design of neural network have guiding significance for plant landscape planning and design. Compared with the traditional neural network modeling method and genetic algorithm, the proposed method has the advantages of wide network structure search space and simple algorithm calculation and design, independent of specific application background, and has strong application and promotion value. This method makes the model performance evaluation index more comprehensive and accurate and the model solution more reasonable. At the same time, combined with the specific status and corresponding changes of various plants in each season, this paper designs a targeted plan to rationally plan the specific spatial layout of the plant landscape and the combination of different types of plant landscapes, so as to effectively improve the quality of the landscape.