Comprehensive evaluation of urban livability

Abstract

This article is based on the comprehensive evaluation of urban livability. This article selects the indicators to measure the urban livability, and uses the factor analysis method to reasonably screen the indicators, and establishes an improved BP neural network evaluation model to obtain the livability of different cities in Shaanxi Province. Monte Carlo simulation is used to analyze the impact of different indicators on urban livability. Then this article comprehensively considers the uncertain factors, establishes a predictive model of stochastic differential equations, and establishes a dynamic evaluation model to reassess the livability of cities.