Research on Suitability Evaluation of Urban Engineering Construction Based on Entropy Weight Hierarchy-Cloud Model: A Case Study in Xiongan New Area, China

Abstract

The development of Xiongan New Area in Hebei Province, China, as a significant national choice, has considerable strategic significance for the integrated growth of Beijing, Tianjin, and Hebei. This paper proposes a cloud model for the suitability evaluation of the construction of Xiongan New Area based on entropy weight analysis, taking into account the geological conditions, groundwater environment, environmental geological problems, and other factors of the suitability of image city development. According to the research, the suitability evaluation findings for the project building employing the cloud model are in strong accord with those of the traditional model and have some application potential. The evaluation’s findings indicate that the project construction in Xiongan New Area is acceptable, with suitable and relatively suitable sites making up 81.4% of the total area and excellent circumstances for project development, construction, and usage. This study offers helpful direction for Xiongan New Area’s urban land-space design and serves as a useful point of comparison for studies looking at the viability of other deep Quaternary Plain region engineering buildings.

1. Introduction

Urban environmental geological issues have gradually garnered attention as China’s urbanization process has accelerated in recent years. Urban development is reliant on the geological environment, which has a direct impact on city planning and development. At the same time, urban development responds to the geological environment. Numerous engineering, geological, and environmental issues with urban development include surface deformation, groundwater contamination, the instability of the rock surrounding subsurface caves, harm to neighboring structures, and the degradation of the ecological environment. Therefore, it is crucial to use the geological environment in urban design and construction in a scientifically sound manner in order to change it and make it compatible with the geological environment [1]. The development and construction of Xiongan New Area as a new ecological metropolis will inevitably face constraints from engineering geology and environmental geology. The suitability study of urban construction can mitigate or even prevent various geological problems caused by engineering construction. It can also facilitate and maintain the coordination between the urban environment and development to the greatest extent possible, based on a comprehensive understanding of the engineering geology and environmental geological conditions in the new area [2,3,4,5,6,7].

Although there is currently no scientifically unified understanding of the application of engineering construction suitability evaluation methods among academics at home and abroad, the mathematical models and analytical theories of various widely used methods can be roughly categorized into five main categories. Through the use of the spatial data superposition analysis method in geographic information systems (GIS), the artificial neural network method, and the analytic hierarchy process, Sterling [8] developed an assessment system to evaluate the suitability of engineering construction in Minneapolis, Minnesota based on topography, engineering geological circumstances, hydrogeological conditions, and other indicators. He then utilized a complete index model for evaluation purposes. Professor Mario Mejia-Navarro [9,10] devised a geological disaster risk assessment system for the Glenwood Springs area on a GIS platform. The system evaluated the region’s geological disaster risk and provided a framework for regional urban planning and construction. Based on the fuzzy comprehensive assessment approach, Gan Xin and coworkers [11] conducted a zoning evaluation study on the acceptability of site engineering construction of various building kinds in a plain area. A waste treatment plant in Israel’s Kurdistan Province is used by Mozafar [12] as the research object. He employs the analytic hierarchy approach to systematically analyze and assess the site suitability of the plant. German academic Youssef Ahmed and others [13] included elements like topography, geological conditions, and environmental geological issues into their analytic hierarchy approach to thoroughly assess the viability of future urban development regions. Liu Hanqiang et al. [14] conducted a systematic and comprehensive evaluation of the suitability of the composite foundation of construction land in their study area through in-depth analysis and research on the engineering geological conditions of the construction land in a certain city. With the aid of the MapGIS spatial analysis function and the unit multi-factor grading weighted index method, Wang Wentao [15] and others investigated the suitability of urban construction land in the Yellow River alluvial plain. They used the geological environment and other elements to evaluate the suitability of construction land development in the plain area.

Due to differences in their mathematical models and analytical logic, each of these traditional methods has its own advantages and limitations (Table 1). However, the factors affecting the suitability of engineering construction are often complex, fuzzy, and random. Despite this complexity, most of these methods still rely on qualitative analysis and subjective evaluation to determine factor weights or membership functions. The evaluation of the adequacy of an engineering construction must consider its inherent imprecision and unpredictability. Academician Lee Deyi [16] made the cloud model his own towards the end of the 1990s. This model, which is based on fuzzy set theory and probability theory, fulfills the natural conversion between quantitative language values and quantitative values through consistently describing the randomness and fuzziness between uncertain linguistic values and exact values. It can explain uncertain issues and has greater universality than traditional fuzzy membership functions [17].

Little research has been done so far on the applicability of cloud-based urban engineering construction. Based on this, this paper uses Xiongan New Area as an example, attempts to apply the cloud model to the suitability evaluation of urban engineering construction in a plain area, resolves the uneven subjective and objective weights of conventional evaluation models, reflects some fuzziness and randomness, provides a new idea for the suitability evaluation of urban engineering construction, and serves as a foundation for Xiongan New Area’s overall planning.

2. Materials and Methods

The cloud model is utilized for the appropriateness evaluation of urban engineering construction, which establishes a grade standard for suitability evaluation using the cloud model. The digital features of the second-level index cloud are generated through utilizing the reverse cloud generator, and then obtaining the digital feat. Firstly, the suitability evaluation system for engineering construction is established through identifying single influencing factors. Then, the index weight is determined through a combination of the analytic hierarchy process and entropy weight method. Subsequently, the complete cloud map is generated using a forward cloud generator and compared with a standard cloud map to obtain the results of the suitability evaluation. The overall method flow is shown in Figure 1.

2.1. Entropy Weight Hierarchy Combination Weight

2.1.1. Entropy Weight Method Weight Calculation

A material system’s degree of disorder can be quantified according to its entropy, which objectively measures the amount of information contained in known data without subjective bias. This method is based on a solid mathematical foundation and involves several stages for calculating weight using the entropy weight method.

• (1). Setting up the initial data matrix

  An original data matrix is created, presuming an evaluation index system has n evaluation indexes and m evaluated items:

  (1)$A={\left(a_{ij}\right)}_{m\times n}=\left[\begin{array}{ccc}{a}_{11}& \cdots & a_{in}\\ ⋮& \ddots & ⋮\\ a_{m1}& \cdots & a_{mn}\end{array}\right]$

• (2). The original data is dimensionlessly processed:

  (2)$r_{ij}=\frac{a_{ij}-min\left\{a_{ij}\right\}}{max\left\{a_{ij}\right\}-min\left\{a_{ij}\right\}}$

  After dimensionless processing, $S={\left(s_{ij}\right)}_{m\times n}$. Then, S is normalized:

  (3)$s_{ij}^{\prime }=\frac{s_{ij}}{\sum _j{\sum }_i{s}_{ij}}$

• (3). Calculate the characteristic proportion f_ij of the characteristic object of the i-th evaluation object under the j-th index:

  (4)$f_{ij}=\frac{s_{ij}^{\prime }}{\sum _{i=1}^m{s}_{ij}^{\prime }}$

• (4). Calculate the entropy value Hj of the j-th index:

  (5)$H_j=k\sum _{i=1}^m{f}_{ij}ln{f}_{ij}$

  Among them, $k=\frac{1}{ln\left(m\right)}$.

• (5). Introduce the difference coefficient a_j and calculate the difference coefficient of the j-th index:

  (6)$a_j=1-H_j, \mathrm{j} = (1, 2, \dots , \mathrm{n})$

• (6). Determine the entropy weight of the j-th index, that is, the weight of the j-th index:

  (7)$x_j=\frac{a_j}{{\sum }_{j=1}^n{a}_j}, x_j\in \left[\mathrm{0,1}\right], \sum _{j=1}^n{x}_i=1$

• (7). Calculate the weight of each index.

  (8)$W=\left(\begin{array}{c}{w}_1\\ ⋮\\ w_m\end{array}\right)=S·X=\left(\begin{array}{ccc}{s}_{11}& \cdots & s_{1n}\\ ⋮& \ddots & ⋮\\ s_{m1}& \cdots & s_{mn}\end{array}\right)\left(\begin{array}{c}{x}_1\\ ⋮\\ x_n\end{array}\right).$

2.1.2. Weight Calculation of Analytic Hierarchy Process

The complete evaluation technique known as the analytic hierarchy process, developed by Saaty in the 1970s, combines qualitative and quantitative methodologies. It is frequently employed to find solutions to intricate issues with many goals. The basic idea is that after thoroughly examining the problem’s nature and the overall goal that must be achieved, the problem is broken down into its component parts. The parts are then grouped and combined into a multi-level structural hierarchy model based on how closely they are related to one another and how much of a member they are. Finally, the weight of the decision-making scheme in relation to the overall goal is determined. The calculation stages will not be repeated in this study because the analytic hierarchy process is frequently utilized in the suitability assessment of engineering projects.

2.1.3. Combination Weight Calculation

The entropy weight method uses objective weighing, whereas the analytical hierarchy process uses subjective weighting. Both processes obtain the weight first, then mix it with the assessed object’s original index data to produce the evaluation result. Based on the strengths of the two ways, the entropy weight–analytic hierarchy process weights and fuses the weights from the two methods to produce the combined weight.

The precise procedure is as follows:

Assume that the analytical hierarchy procedure gave the following weights to n evaluation indicators:

(9)$W_1={\left[w_1,w_2,\dots ,w_n\right]}^T$

The following weights were given to n evaluation indicators using the entropy weight method:

(10)$W_2={\left[w_1^{\prime },w_2^{\prime },\dots ,w_n^{\prime }\right]}^T$

The i-th assessment indicator’s total weight is:

(11)$W=\frac{W_{1i}{W}_{2i}}{\sum _{i=1}^n{W}_{1i}{W}_{2i}}$

2.2. Cloud Model

2.2.1. Cloud Model Definition

The cloud model is a mathematical way to express the mutual conversion between qualitative and quantitative information, reflecting the randomness and ambiguity of things. It is defined as follows: Let X be a set of exact values, X = {x}. X is called the universe of discourse, C is a qualitative concept on the set of X, and x is a random realization of the qualitative concept C. The membership degree $\mathsf{\mu }\left(\mathrm{x}\right)$ of x to C~[0, 1] and is a random number with a stable tendency. If $\mathrm{x}~\mathrm{N}\left({\mathrm{E}}_{\mathrm{x}},{\mathrm{E}}_{\mathrm{n}}^{\prime 2}\right)$, where ${\mathrm{E}}_{\mathrm{n}}^{\prime }~\mathrm{N}\left({\mathrm{E}}_{\mathrm{n}},{\mathrm{H}}_{\mathrm{e}}^2\right)$, and the degree of membership of C satisfies $\mathsf{\mu }\left(\mathrm{x}\right)=\mathrm{e}\mathrm{x}\mathrm{p}\left\{-{\left(\mathrm{x}-{\mathrm{E}}_{\mathrm{n}}\right)}^2/\left(2{\mathrm{E}}_{\mathrm{n}}^{\prime 2}\right)\right\}$, then the distribution of x on the universe X is called a cloud or a normal cloud. Each x is called a cloud drop $\left(\mathrm{x},\mathsf{\mu }\left(\mathrm{x}\right)\right)$.

In the above, $\mathsf{\mu }\left(\mathrm{x}\right)$ is the degree of membership, x is the original variable, ${\mathrm{E}}_{\mathrm{x}}$ is the expectation of x, ${\mathrm{E}}_{\mathrm{n}}$ is the entropy, and H_e is the hyper-entropy.

Expectation, entropy, and hyper-entropy H_e (Figure 2) are used to explain the numerical features of the cloud. The point that best embodies a qualitative concept is expectation, which also serves as the universe’s focal point. Entropy is used to reflect the likelihood and ambiguity of qualitative concepts; the higher the entropy, the wider the range of qualitative concepts that can be accepted. Hyper-entropy He is the entropy of entropy, which symbolizes the thickness of the cloud. The degree of membership dispersion increases as the cloud drop thickness increases. The value is often based on empirical data; there is no precise guideline for choosing hyper-entropy.

2.2.2. Cloud Model Generator

The cloud model implements the reciprocal conversion between qualitative and the quantitative values using a cloud generator. The forward cloud generator (CG) and reverse cloud generator (CG-1) are two categories of cloud generator.

The forward cloud generator, which creates cloud droplets from the cloud digital feature (${\mathrm{E}}_{\mathrm{x}},{\mathrm{E}}_{\mathrm{n}}$, H_e), is a conversion model that translates the qualitative notion to the quantitative value (Figure 3).

Figure 4 shows a conversion model called the reverse cloud generator that may transform a given quantity of precise data into a qualitative idea symbolized by the digital feature (${\mathrm{E}}_{\mathrm{x}},{\mathrm{E}}_{\mathrm{n}}$, H_e). It realizes the quantitative value to the qualitative concept.

2.2.3. Constructing the Comprehensive Evaluation Cloud of Suitability

We first split the assessment area into t evaluation units, choose the comment set based on each secondary index system in Table 2, and then obtain the evaluation matrix in order to build a thorough evaluation cloud. The cloud generator calculates the secondary index cloud feature digital matrix, which is then combined with the secondary index weight matrix to produce the corresponding first-level evaluation index cloud feature digital matrix. The combined first-level evaluation index cloud feature digital matrix and weight matrix then produce the comprehensive cloud digital feature of the t-th evaluation. The suitability level of the t-th unit is then determined via comparing the complete cloud map of the t-th unit’s suitability that is produced by the forward cloud generator (CG) with the standard assessment cloud map. Mapping software (https://www.esri.com/en-us/arcgis/products/mapping/overview, accessed on 2 August 2023) is used to create the complete suitability assessment zoning map of Xiongan New Area after repeating this procedure to collect the suitability evaluation grades of all t units.

(12)${\mathrm{C}}_{\mathrm{t}}={\left(\begin{array}{c}{\mathrm{W}}_1\\ ⋮\\ {\mathrm{W}}_{\mathrm{t}}\end{array}\right)}^{\mathrm{T}}\left(\begin{array}{ccc}{\mathrm{E}}_{\mathrm{x}1}& {\mathrm{E}}_{\mathrm{n}1}& {\mathrm{H}}_{\mathrm{e}1}\\ ⋮& ⋮& ⋮\\ {\mathrm{E}}_{\mathrm{x}\mathrm{t}}& {\mathrm{E}}_{\mathrm{n}\mathrm{t}}& {\mathrm{H}}_{\mathrm{e}\mathrm{t}}\end{array}\right)=\left({\mathrm{E}}_{\mathrm{x}\mathrm{t}}^{*}, E_{nt}^{*}, {\mathrm{H}}_{\mathrm{e}\mathrm{t}}^{*}\right)$

(13)${\mathrm{E}}_{\mathrm{x}\mathrm{t}}^{*}=\frac{{\mathrm{E}}_{\mathrm{x}1}{\mathrm{E}}_{\mathrm{n}1}{\mathrm{W}}_1+\cdots +{\mathrm{E}}_{\mathrm{x}\mathrm{t}}{\mathrm{E}}_{\mathrm{n}\mathrm{t}}{\mathrm{W}}_{\mathrm{t}}}{{\mathrm{E}}_{\mathrm{n}1}{\mathrm{W}}_1+\cdots +{\mathrm{E}}_{\mathrm{n}\mathrm{t}}{\mathrm{W}}_{\mathrm{t}}}$

(14)$E_{nt}^{*}={\mathrm{E}}_{\mathrm{n}1}{\mathrm{W}}_1+\cdots +{\mathrm{E}}_{\mathrm{n}\mathrm{t}}{\mathrm{W}}_{\mathrm{t}}$

(15)${\mathrm{H}}_{\mathrm{e}\mathrm{t}}^{*}=\frac{{\mathrm{H}}_{\mathrm{e}1}{\mathrm{E}}_{\mathrm{n}1}{\mathrm{W}}_1+\cdots +{\mathrm{H}}_{\mathrm{e}\mathrm{t}}{\mathrm{E}}_{\mathrm{n}\mathrm{t}}{\mathrm{W}}_{\mathrm{t}}}{{\mathrm{E}}_{\mathrm{n}1}{\mathrm{W}}_1+\cdots +{\mathrm{E}}_{\mathrm{n}\mathrm{t}}{\mathrm{W}}_{\mathrm{t}}}$

Among them, C_t is the comprehensive suitability cloud digital feature, for which ${\mathrm{E}}_{\mathrm{x}\mathrm{t}}^{*},{ E}_{nt}^{*}, {\mathrm{H}}_{\mathrm{e}\mathrm{t}}^{*}$ is the expectation, entropy, and super entropy of the higher-level index of the t-th unit, and W_t is the weight of the t-th index.

3. Engineering Example

3.1. Single-Factor Analysis

3.1.1. Foundation Soil Conditions

With the exception of Beiwangkou Town near Baiyangdian Duancun Town–Tongkou Town, Xiong County, the foundation soil conditions in Xiongan New Area are generally good, the soil mass is relatively uniform [18], there is only a small range of soft soil developed (Figure 5a), and the thickness is small (generally no more than 2 m). The stratum has a limited bearing capacity (95–115 kPa) in the 0–5 m depth range, making it unsuitable as the natural foundation–bearing layer for multi-story buildings. In most other places, the stratum below 100 m has a bearing capability of more than 120 kPa. It is appropriate for all types of engineering construction after treatment and may satisfy the criteria of pile foundation or pile end–bearing layer of multi-story structures (Figure 5b–f). The compressibility of soil in most areas of the new area is in the medium–low compression zone, and the soil is in the medium–high compression zone in the depth range of 0–5 m east of the first line of Zhanggang Township–Xiong County–Zhaobeikou Township–Yucun Township and west of the first line of Zhaili Township–Anzhou Township–Laohetou Township, as well as in the depth range of 30–50 m east of the first line of Nangzhang Township, southwest of Xiaoli Township, and Qiaogang Township–Zhugezhuang Township–Xiongzhou Township–Xinglonggong Township. The maximum weighted average compressive modulus is 27.17 MPa and 16.37 MPa, respectively (Figure 5g–k).

3.1.2. Hydrogeological Conditions

Only the surrounding region of Baiyangdian District has a shallow groundwater level below 5 m in most of Xiongan New Area (Figure 5l). The construction components of a foundation or pile foundation will corrode due to groundwater and soil, which will reduce the material’s strength and influence the stability of engineering structures. The Liuli Zhuang Town–Tongkou Town region is where most of the places with moderate to severe groundwater corrosion are found. The main ions affecting groundwater erosion are SO₄^2- and Cl^-, and their concentrations range from 1290 to 4345 mg/L and 33 to 1727 mg/L, respectively (Figure 5m). The moderate and severe soil erosion areas are primarily located near the Baiyangdian area, which is impacted by evaporation and concentration and where salt is enriched, forming a salt accumulation zone (Figure 5n).

3.1.3. Environmental Geological Problems

According to Xie et al. [19], the yearly land subsidence rate of Xiongan New Area ranges from 0 to 90 mm. As of 2020, the area of the new district with an annual settlement rate greater than 50 mm accounts for about 12% of the total area of the new district. The new district is primarily located in Nanzhang Town, Luzhuang Township, Longhua Township, Laohetou Township, some areas of Anzhou Town, the junction of Santai Town and Xiaoli Town, the junction of Pingwang Township in Rongcheng County and Zhugezhuang Township in Xi. Urban subterranean pipes or piling foundations may be damaged by land subsidence, which might seriously jeopardize the security of project development and operation. The Xiongan New Area’s central and southern regions are particularly susceptible to sand liquefaction, which is primarily dispersed 20 m below the surface. A tiny portion of Mozhou, Liuli Village, Anxin County, and other regions are dominated by medium–severe liquefaction, whereas the Anxin–Zhaobeikou area and the Anzhou–Qijianfang area in the south are dominated by minor liquefaction (Figure 5q).

3.1.4. Dynamic Geological Action

The stability of the site is unaffected by any of the six developed faults in and around the Xiongan New Area, all of which are non-new active fault zones (Figure 5r). Earthquakes have extremely low magnitudes and frequency; their seismic fortification intensity is VIII degrees.

3.2. Index System and Weight Determination

This time, a number of second-level evaluation indicators are chosen underneath the first-level indicators to construct the evaluation index system. The foundation soil conditions, hydrogeological conditions, environmental geological problems, site stability, and underground space availability resources are chosen as the first-level evaluation indicators this time. This article divides the suitability of the environment and engineering construction and utilization in the new area into four grades, from poor suitability (a) to suitability (b), and analyzes the distribution characteristics of hydrogeological conditions, engineering geological conditions, and environmental geological problems in the study area and their impact on the development and utilization of above-ground and underground engineering in Xiongan New Area. Referring to pertinent data [2,20] and experts’ recommendations that empirical values establish grading standards, there are two ways to determine the extent to which various types of geological environmental impact factors will have an impact on project construction. Table 2 displays the quantitative grading standards for the evaluation factors.

In this study, the subjective and objective integrated weighing approach and the entropy weight–analytic hierarchy process are used, which can effectively eliminate the drawbacks of employing the two methods independently. Through questionnaire surveys, in-person discussions, and other methods for weight evaluation and index assignment, as well as through the pertinent calculations to obtain the judgment matrix and the consistency test of the results, this evaluation arranges three groups of engineering construction suitability evaluation consultants, with each group consisting of ten people who are experienced engineering geology scholars. The evaluation index is weighted using the entropy approach. Five relevant experts from the consulting group create the initial matrix based on the scores of each index, and then the appropriate weighting computation is done. A calculation is made to determine the aggregate weight of each indicator, which displays how much of an impact each index has on the suitability of a project’s construction (Table 3).

3.3. Evaluation Cloud Construction

3.3.1. Standard Evaluation Cloud Construction

We initially develop a common assessment cloud before performing engineering, geological environment, and construction suitability evaluation. In accordance with the Xiongan New Area’s established engineering, geological, and construction suitability evaluation system (Table 2), the new area’s suitability evaluation grades are separated into four categories: suitable, more suitable, generally appropriate, and poorly suitable. The equivalent value range is set to [0, 100], with [0, 25) denoting the area that is most suitable, [25, 50) the area that is more suitable, [50, 75) the area that is generally suitable, and [75, 100] the area that is least suitable. Higher scores indicate a worse fit, whereas lower scores indicate greater suitability. The standard evaluation cloud model is then produced using the cloud model’s inverse cloud generator (Figure 6). To ascertain the level of construction suitability for the project, the final results of the construction suitability evaluation are compared and examined. Table 4 displays the numerical properties of the derived standard cloud model.

3.3.2. Comprehensive Evaluation Cloud Construction

According to the construction suitability evaluation system in Table 2, Formulas (13)–(15) are used to determine the numerical characteristic values of each evaluation index (Table 5 and Table 6). Since there is no exact guidance method for the selection of super entropy, this time, after consulting a large number of relevant materials, the value of super entropy He is set to 0.5. When generating random cloud drops, considering the computer operation ability and accuracy needs, the calculation is repeated 5000 times, that is, each normal cloud model generates 5000 cloud drops. The normal cloud model is generated for the selected 12 s level evaluation indicators (Figure 7) and 4 first level evaluation indicators (Figure 8) according to the four evaluation levels.

The whole area of Xiongan New Area is divided into 100 × 150 evaluation units. The construction suitability cloud model is used to evaluate them. The digital characteristics of each respective evaluation unit are obtained and compared with the digital characteristics of the standard cloud. The engineering, geological environment, and construction suitability grid of Xiongan New Area is obtained (Figure 9).

3.4. Results and Analysis

A partition diagram illustrating the applicability of cloud theory to building of the Xiongan New Area is shown in Figure 10. The chart shows that the majority of the above-ground regions in Xiongan New Area are appropriate and more suitable places for engineering building, with the suitable area accounting for 417.50 km², or 23.6% of the total area. This area has an excellent engineering geological environment that is suited for all types of engineering development and building, as well as general seismic fortification. 1022.89 km², or 57.8% of the total, is the area that is more appropriate. This region has better engineering geological conditions that are better suited for different engineering development and construction. Measures for liquefiable strata should be taken in accordance with standard seismic fortification. Only 8.9% of the available space, or 157.74 km², is generally appropriate. It is mostly dispersed in the areas around Baiyangdian. Flooding is the main possibility. In addition, there are issues with sand liquefaction and land subsidence. To lessen or eliminate the risks of flooding, land subsidence, and sand liquefaction, appropriate precautions must be taken. Finally, 171.87 km²—or 9.7% of the total area—is considered to be unsuitable. It is primarily found in the north of Xiong County, in the western parts of the towns of Duancun, Longhua, and Luzhuang. The area has substantial liquefaction of sandy soil and a ground settlement rate of more than 50 mm per year.

This research also utilizes the average comprehensive index approach as a comparison reference to confirm the viability of the cloud model in the appropriateness evaluation of engineering construction (Figure 11). According to the results of the average comprehensive index method’s suitability evaluation, the suitable area is 818.65 km², or 46.3% of the total area; the more suitable area is 673.87 km², or 38.1%; the generally suitable area is 163.18 km², or 9.2%; and the area of poor suitability is 114.30 km², or 6.4%. Comparing the two methods reveals that while the assessment outcomes of the two approaches are somewhat dissimilar, the overall outcomes are rather comparable (Table 7). The main distinction is that the comprehensive index method overemphasizes the importance of a single factor’s maximum value in the evaluation process and ignores the weight of the evaluation index, whereas the cloud model overcomes these drawbacks and more accurately quantifies the weight of all evaluation factors’ effects on the suitability of engineering construction. It is clear that the cloud model may provide a more accurate and thorough reflection of the evaluation outcomes.

4. Conclusions

• (1). We created a thorough evaluation mechanism for the viability of project construction in Xiongan New Area. Eight second-level evaluation indices of foundation bearing capacity at different depths, soil compressibility, groundwater depth, water and soil corrosivity, and land stability are screened out after the engineering geological conditions and environmental geological conditions affecting the urban construction of the new district are taken into consideration.

• (2). A thorough assessment of the appropriateness of engineering construction in Xiongan New Area was carried out. The suitability assessment grade standard was developed using a cloud model to assess the appropriateness of Xiongan New Area, and the index weight was determined using the analytical hierarchy process and the entropy weight technique. This study’s findings indicate that Xiongan New Area’s engineering construction conditions are generally good, that the suitable and more suitable areas make up more than 80% of the new area’s total area, and that both the generally suitable area and the poorly suitable area have significant environmental geological problems like land subsidence, sand liquefaction, and flood inundation.

• (3). Comparisons were made between the outcomes of the cloud model’s evaluation and those of the conventional suitability evaluation model. Despite some discrepancies between the two, the general conclusions are the same, proving the viability and efficacy of the cloud model in the evaluation of engineering construction’s appropriateness.

• (4). The conceptual model of the evaluation index system must be established before the evaluation method based on cloud theory can be implemented. Through the cloud generator, this method realizes the organic combination of uncertainty and ambiguity among the multi-factor indicators of the suitability evaluation of urban engineering construction in comparison to the conventional assessment technique. The assessment index system is a crucial element in engineering practice that influences site selection for engineering projects as well as disaster prevention and mitigation. The choice of assessment indices in this work is mostly based on the most recent technical requirements of engineering and geological exploration. The consideration is not thorough enough, and the actual problems outside the framework are less complicated. It must be reinforced in a follow-up study to increase the research findings’ maturity and applicability.

• (5). This research was conducted for the Xiongan New Area’s general planning, and as such, its evaluation accuracy does not satisfy the standards of regulatory detailed planning. The following phase is conducting a “targeted” project construction suitability review in accordance with the particular planning framework, taking into account the requirements of various project construction layouts, and undertaking various kinds of projects.

Author Contributions

Conceptualization, Y.-H.G. and B.H.; methodology, Y.-H.G.; software, Y.-H.G.; validation, B.H.; investigation, Y.-H.G., B.H. and S.J.; resources, B.H.; data curation, Y.-H.G. and B.H.; writing—original draft preparation, Y.-H.G.; writing—review and editing, B.H., J.-J.M. and H.-W.L.; visualization, Y.-H.G.; supervision, B.H. and H.-W.L.; project administration, B.H. and H.-W.L.; funding acquisition, B.H. All authors have read and agreed to the published version of the manuscript.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Thanks to Jiang Wanjun for his guidance and suggestions on this article.

Conflicts of Interest

The authors declare that they have no conflict of interest regarding the publication of this paper.

Footnotes

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Figures and Tables

Figure 1. Flow chart of cloud model method for suitability evaluation of engineering construction.

Figure 2. Digital characteristics of the cloud model.

Figure 3. Forward cloud generator.

Figure 4. Backward cloud generator.

Figure 5. Evaluation results of single-factor analysis. (a) Soft soil distribution map in Xiongan New Area; (b) zoning map of 0–5 m foundation bearing capacity in Xiongan New Area; (c) zoning map of 5–10 m foundation bearing capacity in Xiongan New Area; (d) zoning map of 10–15 m foundation bearing capacity in Xiongan New Area; (e) zoning map of 15–30 m foundation bearing capacity in Xiongan New Area; (f) zoning map of 30–50 m foundation bearing capacity in Xiongan New Area; (g) 0–5 m compressibility zoning diagram of soil in Xiongan New Area; (h) 5–10 m compressibility zoning diagram of soil in Xiongan New Area; (i) 10–15 m compressibility zoning diagram of soil in Xiongan New Area; (j) 15–30 m compressibility zoning diagram of soil in Xiongan New Area; (k) 30–50 m compressibility zoning diagram of soil in Xiongan New Area; (l) classification chart of shallow groundwater depth in Xiongan New Area; (m) zoning map of soil corrosion in Xiongan New Area; (n) zoning map of groundwater corrosion in Xiongan New Area; (o) gradation map of land subsidence rate in Xiongan New Area (2016); (p) zoning map of flood inundation potential in Xiongan New Area; (q) classification chart of the sand liquefaction in Xiongan New Area; (r) hidden fault structure distribution map in Xiongan New Area.

Figure 5. Evaluation results of single-factor analysis. (a) Soft soil distribution map in Xiongan New Area; (b) zoning map of 0–5 m foundation bearing capacity in Xiongan New Area; (c) zoning map of 5–10 m foundation bearing capacity in Xiongan New Area; (d) zoning map of 10–15 m foundation bearing capacity in Xiongan New Area; (e) zoning map of 15–30 m foundation bearing capacity in Xiongan New Area; (f) zoning map of 30–50 m foundation bearing capacity in Xiongan New Area; (g) 0–5 m compressibility zoning diagram of soil in Xiongan New Area; (h) 5–10 m compressibility zoning diagram of soil in Xiongan New Area; (i) 10–15 m compressibility zoning diagram of soil in Xiongan New Area; (j) 15–30 m compressibility zoning diagram of soil in Xiongan New Area; (k) 30–50 m compressibility zoning diagram of soil in Xiongan New Area; (l) classification chart of shallow groundwater depth in Xiongan New Area; (m) zoning map of soil corrosion in Xiongan New Area; (n) zoning map of groundwater corrosion in Xiongan New Area; (o) gradation map of land subsidence rate in Xiongan New Area (2016); (p) zoning map of flood inundation potential in Xiongan New Area; (q) classification chart of the sand liquefaction in Xiongan New Area; (r) hidden fault structure distribution map in Xiongan New Area.

Figure 5. Evaluation results of single-factor analysis. (a) Soft soil distribution map in Xiongan New Area; (b) zoning map of 0–5 m foundation bearing capacity in Xiongan New Area; (c) zoning map of 5–10 m foundation bearing capacity in Xiongan New Area; (d) zoning map of 10–15 m foundation bearing capacity in Xiongan New Area; (e) zoning map of 15–30 m foundation bearing capacity in Xiongan New Area; (f) zoning map of 30–50 m foundation bearing capacity in Xiongan New Area; (g) 0–5 m compressibility zoning diagram of soil in Xiongan New Area; (h) 5–10 m compressibility zoning diagram of soil in Xiongan New Area; (i) 10–15 m compressibility zoning diagram of soil in Xiongan New Area; (j) 15–30 m compressibility zoning diagram of soil in Xiongan New Area; (k) 30–50 m compressibility zoning diagram of soil in Xiongan New Area; (l) classification chart of shallow groundwater depth in Xiongan New Area; (m) zoning map of soil corrosion in Xiongan New Area; (n) zoning map of groundwater corrosion in Xiongan New Area; (o) gradation map of land subsidence rate in Xiongan New Area (2016); (p) zoning map of flood inundation potential in Xiongan New Area; (q) classification chart of the sand liquefaction in Xiongan New Area; (r) hidden fault structure distribution map in Xiongan New Area.

Figure 6. Cloud map of suitability evaluation standard for Xiongan New Area engineering construction.

Figure 7. Cloud model of second-level index of suitability evaluation of engineering construction. (a) Cloud model of 0–5 m foundation bearing capacity; (b) cloud model of 5–10 m foundation bearing capacity; (c) cloud model of 10–15 m foundation bearing capacity; (d) cloud model of 15–30 m foundation bearing capacity; (e) cloud model of 30–50 m foundation bearing capacity; (f) cloud model of soil comprehensibility; (g) cloud model of shallow groundwater depth; (h) cloud model of corrosion of soil and water; (i) cloud model of land subsidence; (j) cloud model of sand liquefaction; (k) cloud model of flood inundation potential; (l) cloud model of seismic fortification intensity.

Figure 7. Cloud model of second-level index of suitability evaluation of engineering construction. (a) Cloud model of 0–5 m foundation bearing capacity; (b) cloud model of 5–10 m foundation bearing capacity; (c) cloud model of 10–15 m foundation bearing capacity; (d) cloud model of 15–30 m foundation bearing capacity; (e) cloud model of 30–50 m foundation bearing capacity; (f) cloud model of soil comprehensibility; (g) cloud model of shallow groundwater depth; (h) cloud model of corrosion of soil and water; (i) cloud model of land subsidence; (j) cloud model of sand liquefaction; (k) cloud model of flood inundation potential; (l) cloud model of seismic fortification intensity.

Figure 7. Cloud model of second-level index of suitability evaluation of engineering construction. (a) Cloud model of 0–5 m foundation bearing capacity; (b) cloud model of 5–10 m foundation bearing capacity; (c) cloud model of 10–15 m foundation bearing capacity; (d) cloud model of 15–30 m foundation bearing capacity; (e) cloud model of 30–50 m foundation bearing capacity; (f) cloud model of soil comprehensibility; (g) cloud model of shallow groundwater depth; (h) cloud model of corrosion of soil and water; (i) cloud model of land subsidence; (j) cloud model of sand liquefaction; (k) cloud model of flood inundation potential; (l) cloud model of seismic fortification intensity.

Figure 8. Cloud model of first level index of suitability evaluation of engineering construction. (a) Foundation soil condition; (b) hydrogeology condition; (c) environmental geological problem; (d) field stabilization.

Figure 9. Grid profile of cloud model suitability for engineering construction in Xiongan New Area.

Figure 10. Cloud theory suitability zone map in Xiongan New Area.

Figure 11. Average composite index method suitability zone map in Xiongan New Area.

Table 1

Comparison of advantages and disadvantages of suitability evaluation methods.

Evaluation Methodology	Advantages	Disadvantages
Spatial data superposition analysis of GIS	The operation is simple and the portability is strong	The research of secondary development of software is insufficient, and the analysis of complex geological environment is still lacking
Artificial neural network method	Nonlinear correlation function, intelligent processing ability for wrong results; It has the ability to react quickly to different indicators	For local minimization problem, the convergence speed of the algorithm is slow; the choice of network structure is different, and there is no unified and perfect theoretical guidance
Analytic hierarchy process (AHP)	Simple application, hierarchical division system, few quantitative parameters; It is suitable for complex problems with multiple indicators	Less quantitative data, more qualitative components, and more subjective factors; when there are too many evaluation factors, the weight is difficult to determine
Fuzzy comprehensive evaluation method	The combination of qualitative and quantitative analysis of the selected index system; the evaluation accuracy is more accurate, and the evaluation result is close to the reality	The calculation is complicated and it is difficult to collect each factor quantitatively. There are subjective factors in determining the index weight
Composite index method	The method is simple, easy to understand and easy to calculate; reliable, practical, clear economic meaning	When selecting indicators, we should pay attention to select the same direction indicators; difficult to quantify accurately

Table 2

System of engineering construction suitability integrated evaluation indexes in Xiongan New Area.

First-OrderFactor	Second-OrderFactor	Evaluation Index Grading Standard
		Unsuited	Less Suitable	Relatively Suitable	Suitability
		I	II	III	IV
Foundation soil condition	0–5 m foundation bearing capacity fa	fa < 80 kPa	80 kPa ≤ fa < 100 kPa	100 kPa ≤ fa < 130 kPa	fa ≥ 130 kPa
	5–10 m foundation bearing capacity fa	fa < 100 kPa	100 kPa ≤ fa < 130 kPa	130 kPa ≤ fa < 160 kPa	fa ≥ 160 kPa
	10–15 m foundation bearing capacity fa	fa < 110 kPa	110 kPa ≤ fa < 130 kPa	130 kPa ≤ fa < 170 kPa	fa ≥ 170 kPa
	15–30 m foundation bearing capacity fa	fa < 130 kPa	130 kPa ≤ fa < 160 kPa	160 kPa ≤ fa < 200 kPa	fa ≥ 200 kPa
	30–50 m foundation bearing capacity fa	fa < 130 kPa	130 kPa ≤ fa < 160 kPa	160 kPa ≤ fa < 200 kPa	fa ≥ 200 kPa
	Soil comprehensibility	Es > 15 MPa	11 MPa ≤ Es < 15 MPa	4 MPa ≤ Es < 11 MPa	Es < 4 MPa
Hydrogeology condition	Shallow groundwater depth	<1 m	1–3 m	3–6 m	>6 m
	Corrosion of soil and water	High corrosion	Medium corrosion	Low corrosion	Micro-corrosion
Environmental geological problem	Land subsidence(rate)	>50 mm/a	30–50 mm/a		<30 mm/a
	Sand liquefaction	Severe sand liquefaction	Medium sand liquefaction	Weak sand liquefaction	No sand liquefaction
	Flood inundation potential (the flood inundation depth or land elevation is lower than the flood prevention level)	>1.0 m	0.5–1.0 m	<0.5 m	No flood or land elevation higher than fortification height
Field stabilization	Seismic fortification intensity	≥IX	VIII, VII		≤VI

Table 3

Comprehensive weight table of engineering construction suitability evaluation index.

First-Order Factor	Weight	Second-Order Factor	Weight
Foundation soil condition	0.432	Foundation bearing capacity	0.242
		Soil comprehensibility	0.190
Hydrogeology condition	0.152	Shallow groundwater depth	0.120
		Corrosion of soil and water	0.032
Environmental geological problem	0.3	Land subsidence	0.159
		Sand liquefaction	0.113
		Flood inundation potential	0.028
Field stabilization	0.116	Seismic fortification intensity	0.116

Table 4

Engineering construction suitability classification and digital characteristics of standard cloud model.

Classification of Suitability	Degree of Suitability	Range	Digital Characteristics of Standard Cloud Model
I	Unsuited	[100, 75]	(87.5, 15.0, 0.5)
II	Less suitable	(75, 50]	(62.5, 15.0, 0.5)
III	Relatively suitable	(50, 25]	(37.5, 15.0, 0.5)
IV	Suitable	(25, 0]	(12.5, 15.0, 0.5)

Table 5

Numerical characteristics of cloud model for suitability evaluation index of engineering construction in Xiongan New Area.

Assessment Index		Suitability			Relatively Suitable			Less Suitable			Unsuited
		Ex	En	He	Ex	En	He	Ex	En	He	Ex	En	He
Foundation soil condition	0–5 m foundation bearing capacity fa	155.000	131.644	0.500	115.000	97.672	0.500	90.000	76.439	0.500	40.000	33.972	0.500
	5–10 m foundation bearing capacity fa	170.000	144.385	0.500	145.000	123.152	0.500	115.000	97.672	0.500	50.000	42.466	0.500
	10–15 m foundation bearing capacity fa	310.000	263.290	0.500	150.000	127.399	0.500	115.000	97.670	0.500	55.000	46.713	0.500
	15–30 m foundation bearing capacity fa	325.000	279.030	0.500	180.000	152.878	0.500	145.000	123.152	0.500	65.000	55.026	0.500
	30–50 m foundation bearing capacity fa	325.000	276.030	0.500	180.000	152.878	0.500	145.000	123.152	0.500	65.000	55.206	0.500
	Soil comprehensibility	2.000	1.698	0.500	7.500	6.369	0.500	13.000	11.041	0.500	17.500	14.863	0.500
Hydrogeology condition	Shallow groundwater depth	8.000	6.794	0.500	4.500	3.821	0.500	2.000	1.698	0.500	0.500	0.424	0.500
	Corrosion of soil and water	150.000	1.274	0.500	900.00	1.274	0.500	2250.0	5.095	0.500	4000.0	8.917	0.500
Environmental geological problem	Land subsidence	15.000	12.739	0.500	40.000	33.972	0.500	70.000	9.452	0.500	70.000	59.452	0.500
	Sand liquefaction	0.050	0.042	0.500	3.050	2.590	0.500	12.000	10.191	0.500	21.500	18.260	0.500
	Flood inundation potential	0.050	0.042	0.500	0.300	0.254	0.500	0.750	0.637	0.500	1.500	1.274	0.500
Field stabilization	Seismic fortification intensity	3.000	2.548	0.500	7.500	6.370	0.500	7.500	6.370	0.500	10.500	8.9180	0.500

Table 6

Construction suitability of integrated cloud digital characteristics.

Assessment Index	Suitability			Relatively Suitable			Less Suitable			Unsuited
	Ex	En	He	Ex	En	He	Ex	En	He	Ex	En	He
Foundation soil condition	293.584	56.286	0.500	156.478	33.732	0.500	120.529	27.950	0.500	50.246	14.476	0.500
Hydrogeology condition	126.300	4.892	0.500	883.500	24.919	0.500	2242.50	61.355	0.500	3998.1	108.764	0.500
Environmental geological problem	253.924	55.465	0.500	149.001	33.064	0.500	116.961	25.776	0.500	52.962	11.797	0.500
Field stabilization	3.000	2.548	0.500	7.500	6.369	0.500	7.500	6.369	0.500	10.5	8.917	0.500

Table 7

Comparison list of evaluation results of suitability of project development and construction in Xiongan New Area.

Cloud Theory				Average Composite Index Method
Zoning of Suitability	AreaKm2	Proportion%	Distribution	Zoning of Suitability	AreaKm2	Proportion%	Distribution
Unsuited	171.87	9.7	Between Beishakou, Daying and Mijiawu; Duancun west side; Longhua and luzhuang	Unsuited	114.30	6.4	East of Beishakou and Daying; Duancun west side; Longhua and Luzhuang
Less suitable	157.74	8.9	Around Baiyangdian area	Less suitable	163.18	9.2	Around Baiyangdian area; Northwest of Nanzhang
Relatively suitable	1022.89	57.8	South of Santai, Dawang, Pingwang and Mijiawu	Relatively suitable	673.87	38.1	South of Zhaili, Anxin and Zhaobeikou
suitability	417.50	23.6	Areas other than those mentioned above	suitability	818.65	46.3	Areas other than those mentioned above

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