# The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm

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## Abstract

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^{2}. Meanwhile, the increases in urban construction land area in different years are different. The empirical results show that the population composition of the Yangtze River Economic Belt and the urban construction area between 2005 and 2019 show a trend of increasing annually; at the same time, urban sprawl development shows a staged characteristic. It is of great significance to apply deep learning fusion neural network algorithm in the construction of the urban sprawl measurement system, which provides a quantitative basis for the in-depth analysis and discussion of urban sprawl.

## 1. Introduction

## 2. Materials and Methods

#### 2.1. Theories of Urban Sprawl Regulation

#### 2.2. BPNN Algorithm Based on Deep Learning

#### 2.3. Smart Growth Model Based on Deep Learning Fusion BPNN Algorithm

#### 2.4. Construction of Urban Sprawl Measurement System

## 3. Results

#### 3.1. Evaluation of the Smart Growth Model

#### 3.2. Results of Urban Sprawl Measurement Based on Quantitative Growth Measurement

^{2}from 2014 to 2019. At the same time, from a general perspective, the increase in urban construction land in different years is different. The increase in urban construction land area is not very uniform. Among them, the increase was the largest in 2014, and the total urban construction land area in various regions has reached 1761.34 km

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#### 3.3. Empirical Analysis of Urban Sprawl Measurement

## 4. Discussion

## 5. Conclusions

## Author Contributions

## Funding

## Conflicts of Interest

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## Share and Cite

**MDPI and ACS Style**

Huang, H.; Wu, X.; Cheng, X.
The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm. *Int. J. Environ. Res. Public Health* **2020**, *17*, 4194.
https://doi.org/10.3390/ijerph17124194

**AMA Style**

Huang H, Wu X, Cheng X.
The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm. *International Journal of Environmental Research and Public Health*. 2020; 17(12):4194.
https://doi.org/10.3390/ijerph17124194

**Chicago/Turabian Style**

Huang, Huafang, Xiaomao Wu, and Xianfu Cheng.
2020. "The Analysis of the Urban Sprawl Measurement System of the Yangtze River Economic Belt, Based on Deep Learning and Neural Network Algorithm" *International Journal of Environmental Research and Public Health* 17, no. 12: 4194.
https://doi.org/10.3390/ijerph17124194