Research on modern urban environment design based on gradient descent method in machine algorithm

Abstract

With the rapid development of the times, the process of urban modernization is accelerating. How to build a city with a beautiful city appearance and a beautiful environment is the focus of modern design. Gradient Descent (GD) is a commonly used method for solving unconstrained optimization problems, and has a wide range of applications in the fields of optimization, statistics, and machine learning. With the support of computer technology, this paper puts forward the research of modern urban environment design based on gradient descent method. By simulating the residents’ understanding of urban spatial morphology and the synthesis of cognitive schemas, a person’s accumulated and organized subjective consciousness is defined in advance. Through the analysis of the relevant parameters, and then select the relevant factors in the urban environment, finally determine the theoretical model suitable for the construction of the modern urban environment, and then evaluate and test it.