Artificial Neural Network-Based Planting Arrangement of Smart City in Green Ecological Environment

The traditional urban planting arrangement is largely limited by the designer’s idea and has a high repetition rate low reference reuse rate. Therefore, scientific reasonable of environment necessary. In this work, research on arrangements in smart city carried out under green ecology environment. Firstly, analyzed based structure, characteristics, basic principles artificial neural network (ANN) model. ANN frequently applied pattern recognition, signal processing, system identification, optimization. field control, networks are used to deal with nonlinearity uncertainty control approximate identification function system. Secondly, output value calculated according error backpropagation algorithm. During period, weight adjusted Hebb criterion, relevant statistical model ANN. Finally, suggestions given. shows that steamed bun-shaped plants have largest total number cities, followed spherical bush-like plants. Planting for palm or coconut-form more frequent while wind-shaped lower frequency. terms importance arrangement, these 18 types very important ecological city. given research.