Influence and Effectiveness Analysis of Urban Community Planning on Children's Play Environment Based on Artificial Intelligence

Abstract

With the development of the times, the progress of science and technology, and the growing needs of people, more and more urban community planning chooses artificial intelligence to replace the traditional urban community planning, at the same time, it also brings new influences and changes to children's play environment. Firstly, GA, BP, and GA-BP algorithms are explained, and IGA-BP algorithm is proposed. Secondly, the planning and allocation schemes of different communities in children's environment are planned, and genetic algorithm and BP neural network are used to plan and apply children's play environment in urban communities. Finally, the experiment compares and predicts the optimal path of the above three algorithms, and the results show that IGA-BP algorithm can wait for the optimal path. Then, GA-BP and IGA-BP algorithms were used to compare the heat of children's community and other related indicators. IGA-BP algorithm has obvious advantages in heat prediction, absolute error, and relative error.