# Evaluation and Analysis of High-Quality Development of New Urbanization Based on Intelligent Computing

Authors: Haoran Cheng
Journal: Mathematical Problems in Engineering
 (2022)

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## Abstract

Urbanization construction is an important part of China’s economic development. New urbanization is a new development direction proposed by China in order to adapt to social development. China’s urbanization construction must be changed. The construction of new urbanization is not only committed to expanding the scale of cities and towns but also promotes the industrial upgrading of cities and towns and improves the efficiency of urban production to meet the needs of economic growth. Under China’s high-quality economic development model, various problems of ecological environment pollution and low productivity have emerged. New urbanization has become an effective strategy to promote high-quality economic development. The research results of this paper show that (1) the level of coordinated development among urbanization systems is low, and the population agglomeration and industrial economic development, urban land resource utilization, urban public welfare development, and urban ecological environment development are not coordinated during the process of population urbanization, it is necessary to strengthen the development capacity of the economy, space, society, and green urbanization, and only the coordinated development of various systems can promote the high-quality development of urbanization. (2) From 2006 to 2017, the urbanization development coefficient of the five northwestern provinces and regions has increased year by year, and the high-quality development level of urbanization has gradually increased. Except for the urbanization system development coefficient of urbanization from 2016 to 2017, which was higher than 0.3 and was in a relatively imbalanced stage, the coefficients of the other provinces were all lower than 0.2 in each year, which was in a highly imbalanced stage. (3) The loss value of the intelligent computing development evaluation model proposed in the article is the lowest among the detection models. When the number of iterations is 20, the final loss value of the article is 0.1. With the increase in the number of iterations, the accuracy rate is basically in a stable growth state, when the number of iterations is 20, and the accuracy rate reaches a peak value of 99%, which is close to 100%. The experimental results can also show that the performance of the intelligent computing development evaluation model structure is better than the evaluation of high-quality urbanization development.


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## Body

## 1. Introduction

As a strong driving force for high-quality development, urbanization is not only an important driving force for population agglomeration within urban space but also an important support for industrial agglomeration and technological innovation. In the process of urbanization construction, policy dividends have opened up prerequisites for industrial agglomeration. At this stage, my country’s urbanization construction is still in a critical period of improving quality. The article shows that the problem of low quality of urbanization in my country is becoming increasingly prominent and proposes that the high-quality development of urbanization should be promoted by improving total factor productivity, strengthening urban quality construction, building characteristic small towns, and cultivating new types of farmers [1]. The article puts forward the current development status of my country’s urbanization and gives relevant suggestions [2]. Based on the panel data of 30 provinces in China from 2004 to 2018, this paper constructs an evaluation system for the rapid development of townships [3]. Using the GIS technology and the coordination degree model, the spatial pattern of urbanization quality and resource utilization coordination in 288 cities above the prefecture level in China is analyzed, and the potential reasons are being discussed [4]. Based on the new perspective of “urbanization quality improvement,” this paper summarizes the connotation of urbanization quality in developed areas by analyzing the experience and practice of village renovation in the Southwest Village of Zengcheng County [5]. This paper describes the great significance of the government’s strong support for township construction [6]. Based on the analysis of relevant literature at home and abroad, the article gives a brand-new goal for the development direction of my country’s towns and villages [7]. According to the relationship between urbanization development and industrialization development since my country’s reform and opening up, this paper makes a quantitative analysis of I/U and N/U [8]. This paper calculates the development index of new urbanization and industrial structure in Shandong Province and establishes a coupling coordination degree model of new urbanization and industrial structure [9]. The article analyzes the overall trend of agglomeration in the economic pattern of Northeast China and shows that the development characteristics of Northeast China are different, and the role of urban agglomerations needs to be strengthened [10]. This paper analyzes the economic development status of cities and towns in the five northwestern provinces over the past five years and makes a simple forecast for the future economic development [11]. The article explains the necessity and importance of township construction for national economic development [12]. The article illustrates that promoting high-quality development is an inherent requirement of new urbanization and an objective requirement of rural revitalization [13]. Based on the Guangxi research, this paper believes that private enterprises should adhere to the new development concept, firmly grasp, and make good use of five opportunities, namely, high-end industry, population urbanization, green development, social informatization, economic globalization, and exploring the new era of enterprise high A new path for quality development [14]. By analyzing the development path of urbanization, this paper considers the agglomeration efficiency and the fairness of urban and rural spaces in a thoughtful manner [15].


## 2. Construction of Development Evaluation Model

### 2.1. Research Purpose and Significance

With the continuous deepening of the urbanization process, the shortcomings of the traditional urbanization model have become prominent, the ecological environment has been seriously damaged, the development of cities and rural areas is not coordinated, and the construction of urban infrastructure is not perfect. This kind of large-scale urbanization construction is not in line with the current development concept of our country, and it also leads to the problem of spatial disequilibrium in the quality of urbanization in different regions. These problems need to find new solutions. Throughout the construction process of my country’s urbanization, urbanization is based on large-scale population space migration. Today, my country is seeking to transform from “seeking wealth” to “strengthening the country”, and the concept of guiding urbanization construction is no longer the best way. Development” and “rapid development” are “how to better seek new development”. The current is in the new period of the “14th Five-Year Plan”, and it is also the historical meeting period of the first two-hundred-year “great goals of struggle”, and at this critical period, perfecting the new-type urbanization development strategy has great practical significance for my country to realize socialist modernization and cope with the complex international situation. Rural areas have also achieved balanced development.


### 2.2. Construction of the Indicator System

Combined with the characteristics of the current era of increasing double circulation, the article constructs a development evaluation system, as shown in Table1 [16].Table 1
Indicators of high-quality urban development.
First-level indicatorSecondary indicatorsThree-level indicatorHigh-quality urbanization development systemPopulation of townThe resident population ratio of the town (%)Urban population density (person/Km2)Proportion of employment in the secondary industry (%)Proportion of employment in the tertiary industry (%)Economic urbanizationProvincial per capita GDP/national per capita GDPValue of nonagricultural industries/number of business people in nonagricultural industriesNonfixed output value/fixed output valuePopulation urbanization rate as a percentage of nonagricultural industry structureThe ratio of population urbanization rate to GDP growth rateThe ratio of total import and export to GDP (%)FDI to GDP ratio (%)OFDI to GDP ratio (%)Fiscal deficit ratio (%)Inflation rate (%)Spatial urbanizationRatio of construction area to total area (%)Per capita built-up area (m2/person)Ratio of urban construction land to total area (%)Per capita road area (m2/person)Completed building area (10000m2)Social urbanizationPer capita social consumptionUrban registered unemployment rateIncome ratio of urban and rural residentsHuman capitalRatio of urban and rural Engel coefficientsRatio of personnel in urban and rural health institutionsNumber of patents grantedR&D input intensityScience and technology fiscal expenditureSocial security investment levelGreen urbanizationGreen coverageDaily treatment capacity of urban sewage (10,000 cubic meters)Domestic garbage removal volume (10,000 tons)Forestry investment/GDPIndustrial pollution investment/secondary GDPPer capita park green space (square meters)CO2 emissions per capita


## 2.1. Research Purpose and Significance

With the continuous deepening of the urbanization process, the shortcomings of the traditional urbanization model have become prominent, the ecological environment has been seriously damaged, the development of cities and rural areas is not coordinated, and the construction of urban infrastructure is not perfect. This kind of large-scale urbanization construction is not in line with the current development concept of our country, and it also leads to the problem of spatial disequilibrium in the quality of urbanization in different regions. These problems need to find new solutions. Throughout the construction process of my country’s urbanization, urbanization is based on large-scale population space migration. Today, my country is seeking to transform from “seeking wealth” to “strengthening the country”, and the concept of guiding urbanization construction is no longer the best way. Development” and “rapid development” are “how to better seek new development”. The current is in the new period of the “14th Five-Year Plan”, and it is also the historical meeting period of the first two-hundred-year “great goals of struggle”, and at this critical period, perfecting the new-type urbanization development strategy has great practical significance for my country to realize socialist modernization and cope with the complex international situation. Rural areas have also achieved balanced development.


## 2.2. Construction of the Indicator System

Combined with the characteristics of the current era of increasing double circulation, the article constructs a development evaluation system, as shown in Table1 [16].Table 1
Indicators of high-quality urban development.
First-level indicatorSecondary indicatorsThree-level indicatorHigh-quality urbanization development systemPopulation of townThe resident population ratio of the town (%)Urban population density (person/Km2)Proportion of employment in the secondary industry (%)Proportion of employment in the tertiary industry (%)Economic urbanizationProvincial per capita GDP/national per capita GDPValue of nonagricultural industries/number of business people in nonagricultural industriesNonfixed output value/fixed output valuePopulation urbanization rate as a percentage of nonagricultural industry structureThe ratio of population urbanization rate to GDP growth rateThe ratio of total import and export to GDP (%)FDI to GDP ratio (%)OFDI to GDP ratio (%)Fiscal deficit ratio (%)Inflation rate (%)Spatial urbanizationRatio of construction area to total area (%)Per capita built-up area (m2/person)Ratio of urban construction land to total area (%)Per capita road area (m2/person)Completed building area (10000m2)Social urbanizationPer capita social consumptionUrban registered unemployment rateIncome ratio of urban and rural residentsHuman capitalRatio of urban and rural Engel coefficientsRatio of personnel in urban and rural health institutionsNumber of patents grantedR&D input intensityScience and technology fiscal expenditureSocial security investment levelGreen urbanizationGreen coverageDaily treatment capacity of urban sewage (10,000 cubic meters)Domestic garbage removal volume (10,000 tons)Forestry investment/GDPIndustrial pollution investment/secondary GDPPer capita park green space (square meters)CO2 emissions per capita


## 3. Evaluation and Analysis of High-Quality Urban Development

### 3.1. Calculation and Evaluation of Urbanization Efficiency

In order to test the effect of new urbanization on high-quality industrial development, the following model is constructed [17].(1)IDQit=β0+β1urbit+β2Zit+ui+vi+εit,where i is the individual or each province, t is the year, IDQit is the comprehensive level of high-quality industrial development, urbit is the comprehensive level of new urbanization, Zit is the control variable, and ui is the individual fixed effect, which is used to control changes over time. The individual heterogeneity of vit is the time dummy variable, and εit is the random disturbance term.Test the effect of new urbanization on high-quality industrial development:(2)IDQit=α0+α1urbit+α2zit+ui+vi+εit.The regression results of the new urbanization on the intermediary variable [18]are as follows:(3)Mit=β0+β1urbit+β2Zit+ui+vi+εit,IDQit=γ0+γ1urbit+γ2Mit+γ3zit+ui+vi+εit.Considering the multiple correlations of resource element structure transformation in the process of urbanization, the mainstream spatial panel model can be set as SAR and SEM types.(4)Urbanit=α+ρ∑j=1nWijUrbanit+γRstruit+δXit+εit,Urbanit=α+γRstruit+δXit+εit.Build a dynamic space panel model:(5)Urbanit=βUrbanit−1+ρ∑j=1nWijUrbanit+γRstruit+δXit+εit,εit=λ∑j=1nWijεit+μit.Ratio of service sector to industrial output is as follows:(6)RstruBij=∑j=1nvijtvitInlpijtlpjt.


### 3.2. Variables and Data Description

Based on the two dimensions of time and cross section, the panel data containingm evaluation indicators in n regions in T years are split, so that there is one cross-sectional data every year [19].(7)XT=xijn×m.The T-year cross-sectional data are sorted by time and region to form anT×m global evaluation matrix [20].(8)X=X1,X2,⋯,XTnT×m=xijnT×m.For positive indicators,(9)xij=xij−minxij/imaxxij/i−minxij/i×99+1,1≤i≤nT,1≤j≤m.For negative indicators,(10)xij=maxxij/i−xijmaxxij/i−minxij/i×99+1,1≤i≤nT,1≤j≤m.Calculate the information entropy of thej-th index [21]:(11)ej=−1lnnT×∑i=1nTfij×lnfij,1≤i≤nT,1≤j≤m.Calculate the information entropy redundancy of thej-th indicator [22]:(12)gj=1−ej.Indicator weight calculation [23]:(13)ωj=gj∑j=1mgj.Calculate the high-quality development level of the economy [24]:(14)Fi=∑i=1mωj×xij.Urban high-quality development index[25]:(15)hstruc=∑j=15Wjθj.


## 3.1. Calculation and Evaluation of Urbanization Efficiency

In order to test the effect of new urbanization on high-quality industrial development, the following model is constructed [17].(1)IDQit=β0+β1urbit+β2Zit+ui+vi+εit,where i is the individual or each province, t is the year, IDQit is the comprehensive level of high-quality industrial development, urbit is the comprehensive level of new urbanization, Zit is the control variable, and ui is the individual fixed effect, which is used to control changes over time. The individual heterogeneity of vit is the time dummy variable, and εit is the random disturbance term.Test the effect of new urbanization on high-quality industrial development:(2)IDQit=α0+α1urbit+α2zit+ui+vi+εit.The regression results of the new urbanization on the intermediary variable [18]are as follows:(3)Mit=β0+β1urbit+β2Zit+ui+vi+εit,IDQit=γ0+γ1urbit+γ2Mit+γ3zit+ui+vi+εit.Considering the multiple correlations of resource element structure transformation in the process of urbanization, the mainstream spatial panel model can be set as SAR and SEM types.(4)Urbanit=α+ρ∑j=1nWijUrbanit+γRstruit+δXit+εit,Urbanit=α+γRstruit+δXit+εit.Build a dynamic space panel model:(5)Urbanit=βUrbanit−1+ρ∑j=1nWijUrbanit+γRstruit+δXit+εit,εit=λ∑j=1nWijεit+μit.Ratio of service sector to industrial output is as follows:(6)RstruBij=∑j=1nvijtvitInlpijtlpjt.


## 3.2. Variables and Data Description

Based on the two dimensions of time and cross section, the panel data containingm evaluation indicators in n regions in T years are split, so that there is one cross-sectional data every year [19].(7)XT=xijn×m.The T-year cross-sectional data are sorted by time and region to form anT×m global evaluation matrix [20].(8)X=X1,X2,⋯,XTnT×m=xijnT×m.For positive indicators,(9)xij=xij−minxij/imaxxij/i−minxij/i×99+1,1≤i≤nT,1≤j≤m.For negative indicators,(10)xij=maxxij/i−xijmaxxij/i−minxij/i×99+1,1≤i≤nT,1≤j≤m.Calculate the information entropy of thej-th index [21]:(11)ej=−1lnnT×∑i=1nTfij×lnfij,1≤i≤nT,1≤j≤m.Calculate the information entropy redundancy of thej-th indicator [22]:(12)gj=1−ej.Indicator weight calculation [23]:(13)ωj=gj∑j=1mgj.Calculate the high-quality development level of the economy [24]:(14)Fi=∑i=1mωj×xij.Urban high-quality development index[25]:(15)hstruc=∑j=15Wjθj.


## 4. Simulation Experiments

### 4.1. Spatial and Temporal Analysis of Development

In order to understand the changing trend of the coordinated development of the urbanization system, the experiment selected five different towns in five different provinces in the northwest region and recorded the changes in their development coefficients in recent years. The experimental results show that from 2006 to 2017, the urbanization development coefficient of the five northwestern provinces and regions has increased year by year, and the high-quality development level of urbanization has gradually increased. In terms of provinces and regions, the development coefficient of urban one ranks first among the five provinces and regions in the northwest. The development coefficient of town one was 0.240 in 2006 and has been on an upward trend since then, reaching 0.320 in 2017. Urban 2 was 0.191 in 2006, showing an upward trend in fluctuations. In 2017, it was 0.240, ranking fourth. Urban 3 was 0.163 in 2006 and has been on an upward trend, reaching 0.210 in 2017, ranking last among the five northwestern provinces. In 2006, the urban area 4 was 0.240, showing a fluctuating upward trend, and it reached 0.260 in 2017, ranking second. The development coefficient of town five in 2006 was 0.220, showing an upward trend, and it reached 0.250 in 2017, ranking third. The statistics of the urbanization development coefficient are shown in Figure1.Figure 1
Regional urbanization development coefficient of the five northwestern provinces.As shown in Figure1, although the urban development coefficient of the five northwestern provinces is on the rise, the level of development schedule is low. Except for the urban development coordination degree in 2016–2017, which was higher than 0.3, which was in a relatively imbalanced stage, the urbanization development coordination degree of other provinces in each year was lower than 0.2, which was in a highly imbalanced stage. The Northwest is in a stage of serious imbalance as a whole, indicating that the quality of urbanization in the Northwest is low. The level of coordinated development among urbanization systems is low, and there is an inconsistency between population agglomeration and industrial economic development, urban land resource utilization, urban public welfare development, and urban ecological environment development. In the process of population urbanization, people constantly emphasize economy, space, society, and green. The development capacity of urbanization is very important for the rapid development of cities and towns. Only by achieving stable and coordinated development among various regions, we can correctly achieve the goal of high-quality development of urban construction.As shown in Figure2, from the perspective of the urban economic development coefficient, the overall value is between 0.2 and 0.4, which is in a relatively high imbalance stage. The coefficients of Urban 1, Urban 2, and Urban 5 and 3 provinces are relatively stable and are also in a relatively high imbalance stage. The coefficients of Urban 3 and Urban 4 fluctuate and decrease and tend to be stable. This is related to the weak economic foundation of the five northwestern provinces and regions. The key to the quality of urbanization development lies in economic development. As the basic guarantee for urban development, the economy is a necessary factor to determine whether the high-quality urban development is successful. From the industrial development of the northwest provinces, we can see that except for the urban four and two industries in the northwest provinces, the growth rate of the four and two industries is positive and has a downward trend. This reflects the unstable foundation of high-quality development of urbanization and inhibits the high-quality development of urbanization.Figure 2
Urban economic development coefficient.As shown in Figure3, from the perspective of the urban spatialization development coefficient, the development coefficient of the northwest provinces shows a gradual upward trend, evolving from a high imbalance to a moderate coordination. The coefficients of Town 1 and Town 4 are in a moderate coordination stage in each year. The coefficients of Town 5 and Town 2 have evolved from high imbalance to moderate coordination. Although the coefficient of Town 3 is on the rise, it has been in a relatively high imbalance stage. Judging from the gradual increase in the development coefficient of population and spatial urbanization in Northwest China, the level of urban spatial development has gradually met the needs of population urbanization, but the degree of coordinated development still needs to be improved. Because the northwest is located in an ecologically fragile area, especially in the second, third, and fifth cities, the urban spatial development is greatly affected by natural factors, and it is more necessary to make scientific planning in terms of land resource utilization to improve the level of spatial urbanization.Figure 3
Urban spatialization development coefficient.


### 4.2. Analysis of Empirical Results

In order to explore the impact of new urbanization on high-quality industrial development, the experiment uses a fixed-effect model for regression analysis. By comparing the impact of traditional urbanization and new urbanization on the quality of industrial development, we can find out the important factors that affect the high-quality development of cities and towns. The experimental results are shown in Figures4 and 5.Figure 4
Descriptive statistics result from graph.Figure 5
Statistics of regression results.According to the data in Tables2 and 3, in the stage of traditional urbanization, the results show that the coefficient of influence of traditional urbanization on high-quality industrial development is 0.315, and it can significantly promote development at the level of 1%. Traditional urbanization focuses on the expansion of population and space. To a certain extent, population aggregation and spatial expansion are conducive to the expansion of industrial scale and the improvement of efficiency and to improve the overall development quality of cities and towns. In the new-type urbanization stage, the influence coefficient of new-type urbanization on the high-quality industrial development is much higher than that of traditional urbanization, and at the level of 1%, its promotion effect is much greater than that of traditional urbanization. As far as control variables are concerned, the influence coefficient of government support on high-quality industrial development is not at a significant level in the traditional urbanization stage, indicating that government support has little impact on high-quality industrial development at this stage, while the influence coefficient in the new-type urbanization stage is small and more significant. Under the environmental rules, the difference between the coefficients of traditional towns and new-type urbanization is relatively small, indicating that environmental rules have little influence on the construction of new-type urbanization, and the influence of the talent environment and technological innovation on traditional and new-type towns is within the control range.Table 2
Descriptive statistics.
VariableSample sizeMeanStandard deviationMinMaxIndustrial high-quality development level3600.39550.09880.17800.6941New urbanization level3600.33870.13260.16550.7702Governmental support3600.25230.11120.19980.7582Talent environment3600.26420.12570.09890.2221Environmental rules3600.16140.12030.21600.0110Technological innovation3600.12490.13270.14020.2287Industrial agglomeration3600.19870.23480.39641.6003Table 3
Benchmark regression results and instrumental variable regression.
VariableTraditional urbanizationNew urbanizationInstrumental variableUrbanization level2.721.942.26Governmental support2.012.973.16Environmental rules1.591.791.01Talent environment2.622.312.41Technological innovation1.631.592.01


### 4.3. Model Validation

In order to verify the performance of the model, the experiment was compared with the other two models, and the evaluation results of urban development were analyzed. The loss value and exact value are set under the model. Among them, the experimental set is a set of samples set aside during the model training process, which can be used to adjust the hyperparameters of the model and to initially evaluate the ability of the model, and the test set is used to evaluate the generalization ability of the final model, but it cannot be used as the basis for algorithm-related selections such as parameter tuning and feature selection. In order to make the model run better, each model is set for 20 iterations. The model test loss value is shown in Figure6.Figure 6
Model loss value test.According to the experimental results in Figure6, it can be known that the loss value of the intelligent computing development evaluation model proposed in the article is the smallest value in the test model. When the number of iterations is 20, the final loss value of the article is 0.1. The final loss value of the development evaluation model is 0.3, the final loss value of the grey relational development evaluation model is 0.48, the loss value of the intelligent computing development evaluation model decreases slowly with the increase of the number of iterations, showing a relatively stable state, and the other two models have a more tortuous decline. Therefore, in terms of loss value, the model proposed in this paper has a lower loss value and higher robustness. The correct rate curves of the three different models are shown in Figure 7.Figure 7
Model accuracy test.According to the data in the figure, we can know that the correct rate of the intelligent computing development evaluation model proposed in the article is the one with the largest value in the test model. With the increase in the number of iterations, the correct rate is basically in a steady growth state. When the number of iterations is 20, the accuracy rate peaks at 99%, which is close to 100%. The accuracy rate of the grey relational development evaluation model is the lowest among the three models. When the number of iterations is 20, the accuracy rate reaches 78%. The accuracy rate of the AHP development evaluation model is 92%, which is between the two models. Due to the limited data set and the number of experiments, the two indicators cannot accurately compare the performance of the model. Therefore, the article also introduces theF1 indicator, which can better reflect the specific performance of the model on different test sets. Based on the above model verification results, the performance of the three models is compared and analyzed, and the results are shown in Table 4.Table 4
Model test comparison results.
Model categoryCorrect rate (%)F1Loss valueIntelligent computing development evaluation model96.230.88430.0647Analytic hierarchy process development evaluation model90.250.74060.1945Grey relational development assessment model86.230.64520.2453As shown in the data in Table4, we can know that the performance of the intelligent computing development evaluation model structure is better than the other two models in terms of accuracy, F1, and loss value. Therefore, it can be shown that the intelligent computing development evaluation model structure is very important for urbanization. The quality development assessment performed better than the other two models.


## 4.1. Spatial and Temporal Analysis of Development

In order to understand the changing trend of the coordinated development of the urbanization system, the experiment selected five different towns in five different provinces in the northwest region and recorded the changes in their development coefficients in recent years. The experimental results show that from 2006 to 2017, the urbanization development coefficient of the five northwestern provinces and regions has increased year by year, and the high-quality development level of urbanization has gradually increased. In terms of provinces and regions, the development coefficient of urban one ranks first among the five provinces and regions in the northwest. The development coefficient of town one was 0.240 in 2006 and has been on an upward trend since then, reaching 0.320 in 2017. Urban 2 was 0.191 in 2006, showing an upward trend in fluctuations. In 2017, it was 0.240, ranking fourth. Urban 3 was 0.163 in 2006 and has been on an upward trend, reaching 0.210 in 2017, ranking last among the five northwestern provinces. In 2006, the urban area 4 was 0.240, showing a fluctuating upward trend, and it reached 0.260 in 2017, ranking second. The development coefficient of town five in 2006 was 0.220, showing an upward trend, and it reached 0.250 in 2017, ranking third. The statistics of the urbanization development coefficient are shown in Figure1.Figure 1
Regional urbanization development coefficient of the five northwestern provinces.As shown in Figure1, although the urban development coefficient of the five northwestern provinces is on the rise, the level of development schedule is low. Except for the urban development coordination degree in 2016–2017, which was higher than 0.3, which was in a relatively imbalanced stage, the urbanization development coordination degree of other provinces in each year was lower than 0.2, which was in a highly imbalanced stage. The Northwest is in a stage of serious imbalance as a whole, indicating that the quality of urbanization in the Northwest is low. The level of coordinated development among urbanization systems is low, and there is an inconsistency between population agglomeration and industrial economic development, urban land resource utilization, urban public welfare development, and urban ecological environment development. In the process of population urbanization, people constantly emphasize economy, space, society, and green. The development capacity of urbanization is very important for the rapid development of cities and towns. Only by achieving stable and coordinated development among various regions, we can correctly achieve the goal of high-quality development of urban construction.As shown in Figure2, from the perspective of the urban economic development coefficient, the overall value is between 0.2 and 0.4, which is in a relatively high imbalance stage. The coefficients of Urban 1, Urban 2, and Urban 5 and 3 provinces are relatively stable and are also in a relatively high imbalance stage. The coefficients of Urban 3 and Urban 4 fluctuate and decrease and tend to be stable. This is related to the weak economic foundation of the five northwestern provinces and regions. The key to the quality of urbanization development lies in economic development. As the basic guarantee for urban development, the economy is a necessary factor to determine whether the high-quality urban development is successful. From the industrial development of the northwest provinces, we can see that except for the urban four and two industries in the northwest provinces, the growth rate of the four and two industries is positive and has a downward trend. This reflects the unstable foundation of high-quality development of urbanization and inhibits the high-quality development of urbanization.Figure 2
Urban economic development coefficient.As shown in Figure3, from the perspective of the urban spatialization development coefficient, the development coefficient of the northwest provinces shows a gradual upward trend, evolving from a high imbalance to a moderate coordination. The coefficients of Town 1 and Town 4 are in a moderate coordination stage in each year. The coefficients of Town 5 and Town 2 have evolved from high imbalance to moderate coordination. Although the coefficient of Town 3 is on the rise, it has been in a relatively high imbalance stage. Judging from the gradual increase in the development coefficient of population and spatial urbanization in Northwest China, the level of urban spatial development has gradually met the needs of population urbanization, but the degree of coordinated development still needs to be improved. Because the northwest is located in an ecologically fragile area, especially in the second, third, and fifth cities, the urban spatial development is greatly affected by natural factors, and it is more necessary to make scientific planning in terms of land resource utilization to improve the level of spatial urbanization.Figure 3
Urban spatialization development coefficient.


## 4.2. Analysis of Empirical Results

In order to explore the impact of new urbanization on high-quality industrial development, the experiment uses a fixed-effect model for regression analysis. By comparing the impact of traditional urbanization and new urbanization on the quality of industrial development, we can find out the important factors that affect the high-quality development of cities and towns. The experimental results are shown in Figures4 and 5.Figure 4
Descriptive statistics result from graph.Figure 5
Statistics of regression results.According to the data in Tables2 and 3, in the stage of traditional urbanization, the results show that the coefficient of influence of traditional urbanization on high-quality industrial development is 0.315, and it can significantly promote development at the level of 1%. Traditional urbanization focuses on the expansion of population and space. To a certain extent, population aggregation and spatial expansion are conducive to the expansion of industrial scale and the improvement of efficiency and to improve the overall development quality of cities and towns. In the new-type urbanization stage, the influence coefficient of new-type urbanization on the high-quality industrial development is much higher than that of traditional urbanization, and at the level of 1%, its promotion effect is much greater than that of traditional urbanization. As far as control variables are concerned, the influence coefficient of government support on high-quality industrial development is not at a significant level in the traditional urbanization stage, indicating that government support has little impact on high-quality industrial development at this stage, while the influence coefficient in the new-type urbanization stage is small and more significant. Under the environmental rules, the difference between the coefficients of traditional towns and new-type urbanization is relatively small, indicating that environmental rules have little influence on the construction of new-type urbanization, and the influence of the talent environment and technological innovation on traditional and new-type towns is within the control range.Table 2
Descriptive statistics.
VariableSample sizeMeanStandard deviationMinMaxIndustrial high-quality development level3600.39550.09880.17800.6941New urbanization level3600.33870.13260.16550.7702Governmental support3600.25230.11120.19980.7582Talent environment3600.26420.12570.09890.2221Environmental rules3600.16140.12030.21600.0110Technological innovation3600.12490.13270.14020.2287Industrial agglomeration3600.19870.23480.39641.6003Table 3
Benchmark regression results and instrumental variable regression.
VariableTraditional urbanizationNew urbanizationInstrumental variableUrbanization level2.721.942.26Governmental support2.012.973.16Environmental rules1.591.791.01Talent environment2.622.312.41Technological innovation1.631.592.01


## 4.3. Model Validation

In order to verify the performance of the model, the experiment was compared with the other two models, and the evaluation results of urban development were analyzed. The loss value and exact value are set under the model. Among them, the experimental set is a set of samples set aside during the model training process, which can be used to adjust the hyperparameters of the model and to initially evaluate the ability of the model, and the test set is used to evaluate the generalization ability of the final model, but it cannot be used as the basis for algorithm-related selections such as parameter tuning and feature selection. In order to make the model run better, each model is set for 20 iterations. The model test loss value is shown in Figure6.Figure 6
Model loss value test.According to the experimental results in Figure6, it can be known that the loss value of the intelligent computing development evaluation model proposed in the article is the smallest value in the test model. When the number of iterations is 20, the final loss value of the article is 0.1. The final loss value of the development evaluation model is 0.3, the final loss value of the grey relational development evaluation model is 0.48, the loss value of the intelligent computing development evaluation model decreases slowly with the increase of the number of iterations, showing a relatively stable state, and the other two models have a more tortuous decline. Therefore, in terms of loss value, the model proposed in this paper has a lower loss value and higher robustness. The correct rate curves of the three different models are shown in Figure 7.Figure 7
Model accuracy test.According to the data in the figure, we can know that the correct rate of the intelligent computing development evaluation model proposed in the article is the one with the largest value in the test model. With the increase in the number of iterations, the correct rate is basically in a steady growth state. When the number of iterations is 20, the accuracy rate peaks at 99%, which is close to 100%. The accuracy rate of the grey relational development evaluation model is the lowest among the three models. When the number of iterations is 20, the accuracy rate reaches 78%. The accuracy rate of the AHP development evaluation model is 92%, which is between the two models. Due to the limited data set and the number of experiments, the two indicators cannot accurately compare the performance of the model. Therefore, the article also introduces theF1 indicator, which can better reflect the specific performance of the model on different test sets. Based on the above model verification results, the performance of the three models is compared and analyzed, and the results are shown in Table 4.Table 4
Model test comparison results.
Model categoryCorrect rate (%)F1Loss valueIntelligent computing development evaluation model96.230.88430.0647Analytic hierarchy process development evaluation model90.250.74060.1945Grey relational development assessment model86.230.64520.2453As shown in the data in Table4, we can know that the performance of the intelligent computing development evaluation model structure is better than the other two models in terms of accuracy, F1, and loss value. Therefore, it can be shown that the intelligent computing development evaluation model structure is very important for urbanization. The quality development assessment performed better than the other two models.


## 5. Conclusion

The current international environment is complex, and economic globalization has entered a period of adjustment. Under the background of the new development pattern, my country should give the correct development concept to solve the problem of high-quality development of the domestic economy. The key lies in the coordinated development of urban and rural areas. On the one hand, it is necessary to strengthen the implementation of the rural revitalization strategy, further improve the total factor productivity of agriculture, improve the level of rural revitalization, release more rural labor force, and promote the transformation efficiency of migrant workers into citizens. On the other hand, based on the construction of new urbanization, accelerate the high-quality development of urbanization and strengthen the coordinated development of urban and rural areas. Based on the panel data of five provinces and regions in Northwest China in recent years, this paper constructs an indicator system for high-quality urbanization development and concludes that my country’s new-type urbanization and industrial high-quality development levels are gradually improving, but there are regional differences between the two. This result shows that my country’s industrial development is gradually transforming into a high-quality direction, but the current level of development needs to be further improved. In the future research work, we should focus on the following aspects:(1)
Accelerating the construction of new urbanization provides an important support platform for the high-quality development of the industry. First, under the guidance of the government, accelerate the reform of the household registration system to realize the real citizenization of migrant workers and promote more rural laborers to gather in cities and towns. Second, speed up the urban infrastructure construction and expand the space for industrial agglomeration to realize the free flow of factors, so as to realize the balanced development of cities and towns and solve the problem of unbalanced labor distribution.(2)
In the process of promoting new-type urbanization, reasonably introduce industries and build industrial parks according to the factor endowments of each region. Through continuous adjustment and optimization of industrial layout and structure, resource elements can be reasonably circulated, thereby reducing industrial production costs, improving production efficiency, and promoting high-quality industrial development.(3)
In the critical period of improving the quality of new-type urbanization, through the construction of new-type urbanization, continuously lead the technological innovation of industrial enterprises, and provide strong support for promoting the high-quality development of the industry. In the information age, more emphasis is placed on the diffusion of information technology, so as to optimize resource efficiency and promote high-quality industrial development.



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*Source: 6428970-2022-06-17.xml*