# Research on Evaluation of Green Smart Building Based on Improved AHP-FCE Method

Authors: Song Xu; Yao Sun
Journal: Computational Intelligence and Neuroscience
 (2021)

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## Abstract

With the accelerated pace of urbanization, green buildings and green smart buildings gradually come into people’s vision and are highly valued by all sectors of society on the premise of meeting sustainable development strategy. Firstly, this paper selects 7 first-level index factors and 20 second-level index factors to establish the green smart building evaluation system. Secondly, this paper uses the analytic hierarchy process-fuzzy comprehensive evaluation (AHP-FCE) method to determine the weight of each secondary index. Finally, the feasibility of the evaluation system is verified by case analysis, and some suggestions on green smart building are put forward.


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## Body

## 1. Introduction

A large number of buildings will be built in the construction of new urbanization. However, buildings are one of the largest energy consumers in the world. As people pay more and more attention to issues such as energy, environment, and sustainable development, the development of green smart architecture has become a new direction that conforms to the new urbanization construction. In the “Guiding Opinions on Accelerating the Establishment and Improvement of a Green Low-Carbon Circular Development Economic System” issued by China’s State Council in February 2021, it is emphasized that green planning, green design, and green construction should be carried out in an all-round way; high-quality development and high-level protection should be promoted so as to ensure the realization of the goals of carbon peak and carbon neutrality [1]. In today’s fast-developing construction industry, to achieve the goals of building energy conservation, environmental protection, and greenness and to provide humans with a safe, comfortable, and healthy production and living environment, the construction industry needs to shift from rapid development to high-quality development. Green smart building is a new-generation building incorporating BIM, GIS, Internet of Things, cloud computing, and other technologies. It saves resources and improves energy utilization while reducing environmental pollution and resource waste and has a great effect on alleviating the current energy shortage in my country. At present, there are relatively mature evaluation standards for the evaluation of green buildings, but there are few studies on the comprehensive evaluation of green smart buildings. Combining the smart building evaluation index factors, this paper tries to build a simple and clear green smart building evaluation system based on the green building evaluation system so as to enrich the new green building evaluation standards and promote the evaluation and development of green smart buildings.


## 2. Research Status

Arkin and Paciuk pointed out that intelligent buildings are increasingly using intelligent devices, materials, and sensors. Intelligent buildings should provide environments and means for the best use of buildings. They studied some contemporary intelligent buildings based on the level of system integration [2]. Green buildings are buildings related to resource efficiency, life cycle effects, and building performance; smart buildings with integrated building technology systems as the core are buildings related to building and operational efficiency, as well as enhanced management and occupant functions. Sinopoli has studied the commonalities between the two [3]. Runde and Fay pointed out that building automation requires a large number of smart devices, and modern building automation systems are composed of as many as thousands of components with many attributes and dependencies [4]. Robichaud and Anantatmula’s research shows that by adding a team of professionals to the project, they can promote the completion of green building projects better and faster [5]. Chen and Huang suggested the establishment of an environmental health information management platform to provide residential users with a comfortable and healthy indoor environment [6]. Balta-Ozkan et al. defined an intelligent building as a residence equipped with a communication network, linking sensors, household appliances, and devices that can be remotely monitored, accessed, or controlled to provide services that respond to the needs of its residents. They studied the similarities and differences in the technical and economic driving factors and obstacles to the development of the smart home market in three European countries characterized by different policies and socioeconomic backgrounds [7]. Shaikh et al. conducted a comprehensive and important research on the most advanced intelligent control system for energy and comfort management of intelligent energy buildings [8]. Buckman et al. claimed in 2014 that intelligence can be used interchangeably with smart, and there is no obvious difference between the two [9]. Attoue et al. proposed the concept of smart buildings to use smart technology to reduce energy consumption and improve comfort and user satisfaction [10]. Research by To et al. found that building users tend to focus more on intelligent security systems, followed by intelligent and responsive fresh air supply, elevators, and escalators [11]. Ding and Fan pointed out that most green buildings certified by rating tools are mainly evaluated based on their design and construction. The life cycle of green buildings goes beyond these initial stages, and their full benefits become more apparent during the operation phase of the building [12]. Zhao et al. reviewed and analyzed 2,980 articles published from 2000 to 2016; the results show that green building research is concentrated in the fields of engineering, environmental science, ecology, and construction technology [13]. Apanaviciene et al. research and define the characteristics that smart buildings should meet in order to be compatible with the overall background of smart cities and introduce a new evaluation framework for smart buildings to integrate into smart cities [14]. Eini et al. proposed a real-time management system to control all aspects of smart buildings and proposed the system’s performance specifications, design requirements, and operational constraints [15].Long et al. [16] started from the concept of intelligent buildings and indoor ecological environment and introduced the use of passive methods such as energy-saving windows and building exterior sunshades and the use of active methods such as displacement ventilation and cold radiation ceilings to improve the indoor environment of smart buildings. After analyzing the concept and characteristics of green building and intelligent building as well as their development status at home and abroad, Yin et al. [17] put forward the harmonious and unified view of “human, building and nature” in order to achieve the purpose of saving energy and resources, harmless, pollution-free and recyclable, harmonious and sustainable development of society. Through a large number of investigations, combined with engineering construction practices, Duan [18] integrated a variety of green building evaluation systems to develop a green construction evaluation standard for construction projects. Wang and Zhou [19] studied in depth the green building evaluation system proposed by the American LEED company and the “Green Building Evaluation Standards” issued by China and combined the two standards for comparative analysis, then constructed a simple evaluation system using AHP method. Liu and Peng [20] based on the in-depth understanding of green building and real estate development, combined green building and real estate to build a green real estate development evaluation index system, adopted AHP-FCE method to establish a green real estate evaluation model, and combined with index weights put forward policy recommendations for realizing green real estate development. Xiong et al. [21] comparatively analyzed domestic and foreign green building evaluation systems, and on this basis, they built a green intelligent building evaluation system based on the 2014 version of green building evaluation standards, established a five-level evaluation standard, and determined the weights of evaluation indicators and a comprehensive evaluation model. Wang et al. [22, 23] analyzed and studied the influence of EBI, FCS, and AIOT technologies on the building automation system of modern green intelligent buildings. The application of these technologies further enhanced and improved the control level, use functions, and service efficiency of green intelligent buildings. These technologies lay the foundation for the real realization of the “green” and “intelligence” of buildings and create conditions for the further transformation of intelligent buildings into super-intelligent buildings and smart buildings.Based on academic research at home and abroad, scholars have continuously studied green buildings and intelligent buildings. The evaluation objects focused on green intelligent buildings mainly include “four savings and one environmental protection,” intelligent equipment, technology, environment, materials, and management. These evaluation systems have laid the foundation for the development of green smart buildings. Under the policy background of green economy and sustainable development, we have established a green smart building evaluation system, including safety and durability, health and comfort, convenience of life, resource conservation, environmental livability, smart, innovation and characteristic indicators and then used the analytic hierarchy process-fuzzy comprehensive evaluation (AHP-FCE) method to determine the weight of each secondary indicator and established a five-level evaluation standard.


## 3. Modeling Steps of Improved Analytic Hierarchy Process-Fuzzy Comprehensive Evaluation (AHP-FCE) Method

### 3.1. Establish a Set of Evaluation Indicators

We need to build a judging evaluation index system for the goal. Generally speaking, the fuzzy comprehensive discriminant model includes three levels of indicators, namely, the target level, the criterion level, and the plan level factor set. The evaluation objectU is a collection of evaluation indicators, which is hierarchical. The first-level indicators can be established as Ui, i=1,2,3,⋯,n, so the index system is(1)U=U1,U2,⋯,Un.The secondary indicators can be established asUij, so(2)Ui=Ui1,Ui2,⋯,UiNi,i=1,2,⋯,n,Ni is the number of secondary indicators included in Ui.


### 3.2. Establish Evaluation Grade

(3)V=V1,V2,⋯,VK,where Vj(j=1,2,⋯,K) is the classification of different grades.


### 3.3. Construct Fuzzy Relation Matrix

#### 3.3.1. Construct Judgment MatrixU∗

(4)U∗=u11u12⋯u1nu21u22⋯u2n⋮⋮⋱⋮un1un2⋯unn,where uij=0,theifactorUiis  not as  important  as thejfactorUj,1,theifactorUiand  thejfactorUjareequally  important,2,theifactorUiis  more  important  then thejfactorUj,.For the fuzzy relation matrix, also known as the membership matrix, it is necessary to establish not only the comment set, but also the membership set of grade factors. In this way, after quantitative analysis, the specific position of each factor that may affect the evaluation object in the grade can be determined so as to form the fuzzy relation matrixP:(5)PUki,j=pijk,k=1,2,⋯,n,i=1,2,⋯,Nk,j=1,2,⋯,K,where pijk=vijk/M, where vijk is the number of experts who believe that Uki is affiliated to Vj among all experts. M is the total number of experts.


### 3.4. Calculate Weight Using Improved AHP Method

AHP analytic hierarchy process is a multiobjective decision analysis method that combines qualitative and quantitative analysis methods. The improved analytic hierarchy process in this article is based on the traditional analytic hierarchy process, draws lessons from the methods in Ba’s academic achievements [24], and makes changes in the strategy of constructing the judgment matrix. The previous nine-scale method is replaced by a more concise three-scale method, which makes it easier for experts to understand. Judging and scoring is more intuitive. The improved AHP method improves the accuracy of judgment, and the consistency check step can be omitted after using the optimal transfer matrix, which reduces the computational workload [25, 26].Then, we solve the elementhij in the judgment matrix H:(6)hij=ri−rjkm−1rmax−rmin+1,ri≥rj,rj−rikm−1rmax−rmin+1−1ri<rj,,where ri=∑j=1nuij,rmax=maxri, km=rmax/rmin.LetE=eijn×n, where(7)qij=loghij,dij=1n∑k=1nqik−qjk,eij=10dij.CalculateMi, the product of each row element of matrix E constructed above, then calculate its nth root. The result is as follows:(8)Wi=Min=Πeijn.Normalize the vectorW to get Wi′: Wi′=wi/∑i=1nwi; finally, we can get the weight vector W of n elements:(9)W=W1,W2,⋯,Wn.


## 3.1. Establish a Set of Evaluation Indicators

We need to build a judging evaluation index system for the goal. Generally speaking, the fuzzy comprehensive discriminant model includes three levels of indicators, namely, the target level, the criterion level, and the plan level factor set. The evaluation objectU is a collection of evaluation indicators, which is hierarchical. The first-level indicators can be established as Ui, i=1,2,3,⋯,n, so the index system is(1)U=U1,U2,⋯,Un.The secondary indicators can be established asUij, so(2)Ui=Ui1,Ui2,⋯,UiNi,i=1,2,⋯,n,Ni is the number of secondary indicators included in Ui.


## 3.2. Establish Evaluation Grade

(3)V=V1,V2,⋯,VK,where Vj(j=1,2,⋯,K) is the classification of different grades.


## 3.3. Construct Fuzzy Relation Matrix

### 3.3.1. Construct Judgment MatrixU∗

(4)U∗=u11u12⋯u1nu21u22⋯u2n⋮⋮⋱⋮un1un2⋯unn,where uij=0,theifactorUiis  not as  important  as thejfactorUj,1,theifactorUiand  thejfactorUjareequally  important,2,theifactorUiis  more  important  then thejfactorUj,.For the fuzzy relation matrix, also known as the membership matrix, it is necessary to establish not only the comment set, but also the membership set of grade factors. In this way, after quantitative analysis, the specific position of each factor that may affect the evaluation object in the grade can be determined so as to form the fuzzy relation matrixP:(5)PUki,j=pijk,k=1,2,⋯,n,i=1,2,⋯,Nk,j=1,2,⋯,K,where pijk=vijk/M, where vijk is the number of experts who believe that Uki is affiliated to Vj among all experts. M is the total number of experts.


## 3.3.1. Construct Judgment MatrixU∗

(4)U∗=u11u12⋯u1nu21u22⋯u2n⋮⋮⋱⋮un1un2⋯unn,where uij=0,theifactorUiis  not as  important  as thejfactorUj,1,theifactorUiand  thejfactorUjareequally  important,2,theifactorUiis  more  important  then thejfactorUj,.For the fuzzy relation matrix, also known as the membership matrix, it is necessary to establish not only the comment set, but also the membership set of grade factors. In this way, after quantitative analysis, the specific position of each factor that may affect the evaluation object in the grade can be determined so as to form the fuzzy relation matrixP:(5)PUki,j=pijk,k=1,2,⋯,n,i=1,2,⋯,Nk,j=1,2,⋯,K,where pijk=vijk/M, where vijk is the number of experts who believe that Uki is affiliated to Vj among all experts. M is the total number of experts.


## 3.4. Calculate Weight Using Improved AHP Method

AHP analytic hierarchy process is a multiobjective decision analysis method that combines qualitative and quantitative analysis methods. The improved analytic hierarchy process in this article is based on the traditional analytic hierarchy process, draws lessons from the methods in Ba’s academic achievements [24], and makes changes in the strategy of constructing the judgment matrix. The previous nine-scale method is replaced by a more concise three-scale method, which makes it easier for experts to understand. Judging and scoring is more intuitive. The improved AHP method improves the accuracy of judgment, and the consistency check step can be omitted after using the optimal transfer matrix, which reduces the computational workload [25, 26].Then, we solve the elementhij in the judgment matrix H:(6)hij=ri−rjkm−1rmax−rmin+1,ri≥rj,rj−rikm−1rmax−rmin+1−1ri<rj,,where ri=∑j=1nuij,rmax=maxri, km=rmax/rmin.LetE=eijn×n, where(7)qij=loghij,dij=1n∑k=1nqik−qjk,eij=10dij.CalculateMi, the product of each row element of matrix E constructed above, then calculate its nth root. The result is as follows:(8)Wi=Min=Πeijn.Normalize the vectorW to get Wi′: Wi′=wi/∑i=1nwi; finally, we can get the weight vector W of n elements:(9)W=W1,W2,⋯,Wn.


## 4. Green Smart Building Evaluation Index System Based on Improved AHP-FCE Method

To build a more systematic and comprehensive evaluation system for green smart building projects, it is necessary to select the first and second indicators and the corresponding scoring rules, and the indicators should be relatively independent so as to avoid the appearance of redundant and miscellaneous indicators. At the same time, in order to facilitate the understanding of calculations and applications, the construction of the index system should also be simple and easy to implement. Following the principles of systemicity, dynamics, and relative independence, combined with China’s latest “Green Building Evaluation Standard” (GB/T50378-2019) and the group standard “Smart Building Evaluation Standard” issued by China Building Energy Conservation Association in 2021, we have built an evaluation index system for green smart buildings in Table1.Table 1
Green smart building evaluation system.
Target layerFirst-level indicatorsSecondary indicatorsJudging rulesGreen smart building evaluationUSafety and durabilityU1SafetyU11Reasonably improve the seismic performance of buildingsPersonnel safety protection measuresProducts or accessories with safety functionsAntislip measures for indoor and outdoor floorsPeople and vehicles are divided and the traffic system is sufficiently illuminatedDurabilityU12Improve building adaptabilityImprove the durability of building componentsImprove the durability of building structure materialsReasonable use of decoration building materialsHealth and comfortU2Indoor air qualityU21Control the concentration of major indoor air pollutantsDecoration building materials meet national standardsWater qualityU22Direct drinking water, landscape water, and other water quality meet national standardsWater storage facilities such as pools meet sanitary requirementsPermanent identification of water supply and drainage pipeline equipmentAcoustic environment and light environmentU23Optimize the indoor acoustic environment of the main roomThe main room divider has good sound performanceMake full use of natural lightIndoor hot and humid environmentU24Good indoor hot and humid environmentImprove natural ventilation effectImprove indoor thermal comfortConvenience of lifeU3Mobility and barrier-freeU31The site has convenient transportationPublic areas meet all-age design requirementsService facilitiesU32Provide convenient public servicesOpen urban green spaces, squares, and other venuesReasonably set up fitness venues and spacesProperty managementU33Formulate energy-saving, water-saving, and material-saving greening plansThe average daily water consumption of the building meets the national standardRegularly evaluate the building operation effectEstablish a green education publicity and practice mechanismSave resourcesU4Land saving and land useU41Economical and intensive use of landReasonable development and utilization of underground spaceReasonable parking designEnergy-saving and energy utilizationU42Optimizing the thermal performance of building envelopeEnergy efficiency of heating and air conditioning system is better than national standardReduce energy consumption of heating and air conditioning systemsAdopt energy-saving equipment and energy-saving measuresTake measures to reduce building energy consumptionReasonable use of renewable resourcesWater-saving and water resources utilizationU43Use higher-efficiency sanitary appliancesUse water-saving equipment for irrigation and cooling waterComprehensive utilization of rainwater to make landscape waterUse nontraditional water sourcesWood-saving and green building materialsU44Integrated design and construction of civil engineering and decorationReasonable selection of building structure materials and componentsIndustrialized interior parts are selected for building decorationUse recyclable and reusable materialsChoose green building materialsLivable environmentU5Site ecology and landscapeU51Reasonable layout of buildings and landscapesPlanning surface and roof stormwater runoffReasonably set up green landReasonably arrange outdoor smoking areasSet up green rainwater infrastructureOutdoor physical environmentU52The environmental noise inside the venue is better than the national standardBuilding and lighting design to avoid light pollutionComfortable and natural ventilationReduce heat island strengthSmartU6Smart securityU61Equipped with public safety smart warning functionVideo surveillance with detection functionSet up an emergency response systemComputer room engineering and its own protective measures specificationEffective display of video security monitoring systemFire and security have linkage function and work normallyThe security system has the ability to prevent damageThe security system uses a dedicated transmission networkSmart architecture and platformU62Support the deployment of IoT application servicesThe platform can centrally monitor and manage each subsystemThe platform follows the principle of modular constructionThe platform supports secondary developmentRealize equipment life cycle monitoring and managementWith the docking function of smart building operation and maintenance platformThe platform can intelligently analyze dataSpecific applications such as data sharingSmart operationU63Has a smart parking management systemHas a smart property management systemRealize smart home with IoT technologyWith personnel positioning indoor navigation serviceComplete information query and release systemWireless network coverage on demandAccess to smart platform for main electrical building equipmentWith office automation systemHas a building energy metering management platformSet up an automatic remote metering systemSet up air quality monitoring and release systemSet up an online monitoring system for water quality and water supply and drainageInnovation and characteristicsU7Improvement and innovationU71Further reduce the energy consumption of heating and air conditioning systemsArchitectural style design and inheritance of architectural cultureIncrease the green capacity of the siteReasonable selection of abandoned sitesStructural system and building components meet requirementsApply BIM technologyReduce carbon emission intensity per unit areaGreen construction and managementUse of insurance products for potential defects in construction project qualityCharacteristicsU72Obtain the green building logoMeet the requirements of the national gridSet equipment monitoring health indexMeet the individual needs of different acquaintancesApply big data artificial intelligence and other technologiesRemarks: Innovation and characteristics are the corresponding improvement ofU1–U6 index factors.


## 5. Empirical Analysis

Xiang'an Zhengrong Mansion is located at the intersection of Shamei Road and Xiang'an South Road. It was built by XM Zhengpeng Real Estate Co., Ltd. The total construction area of the project is 114,307.13 square meters, covering an area of 27,595.52 square meters, the greening rate is 30%, and the plot ratio is 2.8. The planned properties include commercial streets, landscape gardens, and basketball courts. The project is surrounded by Xiangshan Park and Shamei Park. The environment is beautiful, and it is close to the subway entrance and exit, making travel very convenient.


### 5.1. Building Evaluation System Based on Improved AHP-FCE Model

Next, we use the improved AHP-FCE method to comprehensively evaluate the green wisdom project level of Xiang'an Zhengrong Mansion in combination with the 7 primary index factors and 20 secondary index factors listed in Table1.


### 5.2. Construction of Judgment Matrix and Single-Layer Weight Calculation

According to the green smart building evaluation index system established in Table1, the hierarchical structure is constructed by combining the interrelationships between the indicators. Experts from the green smart building and real estate industries are invited to compare and score each factor. A judgment matrix is constructed, and the corresponding weights are calculated. The results are as follows:(10)U∗=1220202012010200100022221212012010222212120000001.Calculate according to the steps of the improved fuzzy comprehensive evaluation method, and get the weights of each criterion layer (first-level indicators):(11)WU=WU1,WU2,WU3,WU4,WU5,WU6,WU7,=0.1481,0.0607,0.0253,0.3451,0.0607,0.3451,0.0151.Using the same method and principle, construct the judgment matrix of the index layer (secondary indicators) against the criterion layer:Safety and durability indicatorsU1=U11,U12, U1∗=1201.Health and comfort indicatorsU2=U21,U22,U23,U24, U2∗=1200010022102221.Convenience of life indicatorsU3=U31,U32,U33,U3∗=100212201.Save resources indicatorsU4=U41,U42,U43,U44, U4∗=1000212220122001.Livable environment indicatorsU5=U51,U52, U5∗=1201.Smart indicatorsU6=U61,U62,U63, U6∗=100210221.Innovation and characteristics indicatorsU7=U71,U72, U7∗=1111.Calculate according to the improved method, and get the weight of each indicators layer (secondary indicators):Safety and durability index weightWU1=0.7500,0.2500.Health and comfort index weightWU2=0.1178,0.0550,0.2634,0.5638.Convenience of life index weightWU3=0.1047,0.6370,0.2583.Save resources index weightWU4=0.0550,0.5638,0.2634,0.1178.Livable environment index weightWU5=0.7500,0.2500.Smart index weightWU6=0.1047,0.2583,0.6370.Innovation and characteristics index weightWU7=0.5000,0.5000.


### 5.3. Calculation of the Composite Weight of Each Layer Element to the Target Layer

Through the above calculation and evaluation results, the weight of each indicator for comprehensive evaluation of green smart building project is obtained, as shown in Table2.Table 2
Weights of comprehensive evaluation indicators of green smart building project.
Target layerFirst-level indicatorsFirst-level weightSecondary indicatorsSecondary weightWeightsUUiWiUijWjWij = Wi∗WjGreen smart building evaluation systemUSafety and durabilityU10.1481SafetyU110.75000.1111DurabilityU120.25000.0370Health and comfortU20.0607Indoor air qualityU210.11780.0072Water qualityU220.05500.0033Acoustic environment and light environmentU230.26340.0160Indoor hot and humid environmentU240.56380.0342Convenience of lifeU30.0253Mobility and barrier-freeU310.10470.0026Service facilitiesU320.63700.0161Property managementU330.25830.0065Save resourcesU40.3451Land saving and land useU410.05500.0190Energy-saving and energy utilizationU420.56380.1946Water-saving and water resources utilizationU430.26340.0909Wood-saving and green building materialsU440.11780.0407Livable environmentU50.0607Site ecology and landscapeU510.75000.0455Outdoor physical environmentU520.25000.0152SmartU60.3451Smart securityU610.10470.0361Smart architecture and platformU620.25830.0891Smart operationU630.63700.2198Innovation and characteristicsU70.0151Improvement and innovationU710.50000.0076CharacteristicsU720.50000.0076The weight distribution of indicators in Table1 is shown in Figures 1 and 2. The main indicators that affect the evaluation of green smart buildings are save resources (U4, weight is 0.3451) and smart (U6, weight is 0.3451), followed by safety and durability (U1, weight is 0.1481). The main indicator that affects safety and durability (U1) is safety (U11, weight is 0.7500); the main indicator that affects health and comfort (U2) is indoor hot and humid environment (U24, weight is 0.5638); the main indicator that affects convenience of life (U3) is service facilities (U32, weight is 0.6370); the main indicator that affects save resources (U4) is energy-saving and energy utilization (U42, weight is 0.5638); the main indicator that affects livable environment (U5) is site ecology and landscape (U51, weight is 0.7500); the main indicator that affects smart (U6) is smart operation (U63, weight is 0.6370); the main indicators that affect innovation and characteristics (U7) are improvement and innovation (U71, weight is 0.5000) and characteristics (U72, weight is 0.5000).Figure 1
The weighting diagram of the criterion layer indicators.Figure 2
The weighting diagram of scheme layer indicators. (a) Weights ofU11 – U12. (b) Weights of U21 – U24. (c) Weights of U31 – U33. (d) Weights of U41 – U44. (e) Weights of U51 – U52. (f) Weights of U61 – U63. (g) Weights of U71 – U72.
(a)(b)(c)(d)(e)(f)(g)The overall ranking of indicator weights is shown in Figure3. Among all the impact indicators, the most important is smart operation (U63), followed by energy-saving and energy utilization (U42), followed by safety (U11), water-saving and water resources utilization (U43), and smart architecture and platform (U62).Figure 3
Comparison of weights of indicators.


### 5.4. Determine the Set of Evaluation Criteria

The evaluation standard set of green and smart building projects selects the five-star evaluation system in the “Smart Building Evaluation Standards,” which are one-star, two-star, three-star, four-star, and five-star. UseV to denote the set of evaluation criteria; then they are as follows:(12)V=V1,V2,V3,V4,V5,=one−star, two−star, three−star, four−star, five−star,=0∼20,20∼50,50∼70,70∼90,90∼100.


### 5.5. Fuzzy Comprehensive Evaluation of Criterion Level

According to the actual situation of the project, this paper consulted a 10-member expert group composed of experts in the construction, environmental protection, and real estate industries by collecting relevant information and using questionnaire surveys and collected the expert group’s review opinions on green and smart building projects. The fuzzy evaluation matrix is as follows:Safety and durability index matrix:(13)PU1=0.20.40.20.10.10.20.50.20.10.Health and comfort index matrix:(14)PU2=0.10.60.10.10.10.30.40.3000.40.60000.20.50.300.Convenience of life index matrix:(15)PU3=0.40.50.1000.10.50.4000.30.40.300.  Save resources index matrix:(16)PU4=0.10.50.20.10.10.10.60.20.100.30.40.3000.20.60.200.Livable environment index matrix:(17)PU5=0.10.50.30.100.20.60.200.Smart index matrix:(18)PU6=0.20.50.10.200.40.40.2000.20.60.200.Innovation and characteristics index matrix:(19)PU7=0.50.50000.30.60.100.According to the steps of the improved AHP method, the calculated weight vectorW of each evaluation index is established, the fuzzy evaluation matrix is established, and the comprehensive evaluation vector of the criterion layer (first-level indexes) is calculated according to the formula Y=W×P.Comprehensive evaluation vector of safety and durability index:(20)YU1=WU1×PU1=0.7500,0.2500×0.20.40.20.10.10.20.50.20.10=0.2000,0.4250,0.2000,0.1000,0.0750.Comprehensive evaluation vector of health and comfort index:(21)YU2=WU2×PU2=0.1178,0.0550,0.2634,0.5638×0.10.60.10.10.10.30.40.3000.40.60000.20.50.300=0.2464,0.5326,0.1974,0.0118,0.0118.Comprehensive evaluation vector of convenience of life index:(22)YU3=WU3×PU3=0.1047,0.6370,0.2583×0.40.50.1000.10.50.4000.30.40.300=0.1831,0.4742,0.3428,0.0000,0.0000.Comprehensive evaluation vector of save resources index:(23)YU4=WU4×PU4=0.0550,0.5638,0.2634,0.1178×0.10.50.20.10.10.10.60.20.100.30.40.3000.20.60.200=0.1645,0.5418,0.2263,0.0619,0.0055.Comprehensive evaluation vector of livable environment index:(24)YU5=WU5×PU5=0.7500,0.2500×0.10.50.30.100.20.60.200=0.1250,0.5250,0.2750,0.0750,0.0000.Comprehensive evaluation vector of smart index:(25)YU6=WU6×PU6=0.1047,0.2583,0.6370×0.20.50.10.200.40.40.2000.20.60.200=0.2517,0.5379,0.1895,0.0209,0.0000.Comprehensive evaluation vector of innovation and characteristics index:(26)YU7=WU7×PU7=0.5000,0.5000×0.50.50000.30.60.100=0.4000,0.5500,0.0500,0.0000,0.0000.


### 5.6. Fuzzy Comprehensive Evaluation of Target Layer

Using the relevant calculation rules of the fuzzy comprehensive evaluation, and according to the calculation results of the fuzzy comprehensive evaluation of the criterion layer (first-level indexes), construct the target layer fuzzy evaluation matrix of this project; then, the target layer fuzzy evaluation matrix is(27)PU=0.20000.42500.20000.10000.07500.24640.53260.19740.01180.01180.18310.47420.34280.00000.00000.16450.54180.22630.06190.00550.12500.52500.27500.07500.00000.25170.53790.18950.02090.00000.40000.55000.05000.00000.0000.According to formulaY=W×P, the comprehensive evaluation vector of the target layer is(28)YU=WU×PU=0.1481,0.0607,0.0253,0.3451,0.0607,0.3451,0.0151×0.20000.42500.20000.10000.07500.24640.53260.19740.01180.01180.18310.47420.34280.00000.00000.16450.54180.22630.06190.00550.12500.52500.27500.07500.00000.25170.53790.18950.02090.00000.40000.55000.05000.00000.0000=0.2064,0.5200,0.2112,0.0487,0.0137.According to the principle of the maximum degree of membership, the comprehensive evaluation level of the green smart building project can be determined. The maximum comprehensive evaluation value of the green intelligent building project in this case is0.5200, which belongs to the two−star level of the set of evaluation criteria. Then, we use the formula S=Y×GT to calculate the comprehensive evaluation value of the green smart building project and obtain the quantified comprehensive evaluation result, where the value of the quantified evaluation standard set G is the median value of the corresponding value in the evaluation standard set V. So, the quantified comprehensive score S is(29)S=YU×GT=0.2064,0.5200,0.2112,0.0487,0.0137×10,35,60,80,95T=38.1330.


### 5.7. Analysis of Evaluation Results

Through the above calculations, it is shown that the project developed by XM Zhengpeng Real Estate Co., Ltd., is a two-star building. According to the quantified comprehensive evaluation calculation result, the comprehensive score of the overall evaluation of the project is corresponding to the two-star level. If you score according to the judging rules rules in Table1, you can get consistent results. However, the judging rules’ scoring method needs to determine the weight or value of the rules, which also increases the workload of the experts for scoring. The improved AHP-FCE method can reduce the corresponding workload and improve work efficiency.


## 5.1. Building Evaluation System Based on Improved AHP-FCE Model

Next, we use the improved AHP-FCE method to comprehensively evaluate the green wisdom project level of Xiang'an Zhengrong Mansion in combination with the 7 primary index factors and 20 secondary index factors listed in Table1.


## 5.2. Construction of Judgment Matrix and Single-Layer Weight Calculation

According to the green smart building evaluation index system established in Table1, the hierarchical structure is constructed by combining the interrelationships between the indicators. Experts from the green smart building and real estate industries are invited to compare and score each factor. A judgment matrix is constructed, and the corresponding weights are calculated. The results are as follows:(10)U∗=1220202012010200100022221212012010222212120000001.Calculate according to the steps of the improved fuzzy comprehensive evaluation method, and get the weights of each criterion layer (first-level indicators):(11)WU=WU1,WU2,WU3,WU4,WU5,WU6,WU7,=0.1481,0.0607,0.0253,0.3451,0.0607,0.3451,0.0151.Using the same method and principle, construct the judgment matrix of the index layer (secondary indicators) against the criterion layer:Safety and durability indicatorsU1=U11,U12, U1∗=1201.Health and comfort indicatorsU2=U21,U22,U23,U24, U2∗=1200010022102221.Convenience of life indicatorsU3=U31,U32,U33,U3∗=100212201.Save resources indicatorsU4=U41,U42,U43,U44, U4∗=1000212220122001.Livable environment indicatorsU5=U51,U52, U5∗=1201.Smart indicatorsU6=U61,U62,U63, U6∗=100210221.Innovation and characteristics indicatorsU7=U71,U72, U7∗=1111.Calculate according to the improved method, and get the weight of each indicators layer (secondary indicators):Safety and durability index weightWU1=0.7500,0.2500.Health and comfort index weightWU2=0.1178,0.0550,0.2634,0.5638.Convenience of life index weightWU3=0.1047,0.6370,0.2583.Save resources index weightWU4=0.0550,0.5638,0.2634,0.1178.Livable environment index weightWU5=0.7500,0.2500.Smart index weightWU6=0.1047,0.2583,0.6370.Innovation and characteristics index weightWU7=0.5000,0.5000.


## 5.3. Calculation of the Composite Weight of Each Layer Element to the Target Layer

Through the above calculation and evaluation results, the weight of each indicator for comprehensive evaluation of green smart building project is obtained, as shown in Table2.Table 2
Weights of comprehensive evaluation indicators of green smart building project.
Target layerFirst-level indicatorsFirst-level weightSecondary indicatorsSecondary weightWeightsUUiWiUijWjWij = Wi∗WjGreen smart building evaluation systemUSafety and durabilityU10.1481SafetyU110.75000.1111DurabilityU120.25000.0370Health and comfortU20.0607Indoor air qualityU210.11780.0072Water qualityU220.05500.0033Acoustic environment and light environmentU230.26340.0160Indoor hot and humid environmentU240.56380.0342Convenience of lifeU30.0253Mobility and barrier-freeU310.10470.0026Service facilitiesU320.63700.0161Property managementU330.25830.0065Save resourcesU40.3451Land saving and land useU410.05500.0190Energy-saving and energy utilizationU420.56380.1946Water-saving and water resources utilizationU430.26340.0909Wood-saving and green building materialsU440.11780.0407Livable environmentU50.0607Site ecology and landscapeU510.75000.0455Outdoor physical environmentU520.25000.0152SmartU60.3451Smart securityU610.10470.0361Smart architecture and platformU620.25830.0891Smart operationU630.63700.2198Innovation and characteristicsU70.0151Improvement and innovationU710.50000.0076CharacteristicsU720.50000.0076The weight distribution of indicators in Table1 is shown in Figures 1 and 2. The main indicators that affect the evaluation of green smart buildings are save resources (U4, weight is 0.3451) and smart (U6, weight is 0.3451), followed by safety and durability (U1, weight is 0.1481). The main indicator that affects safety and durability (U1) is safety (U11, weight is 0.7500); the main indicator that affects health and comfort (U2) is indoor hot and humid environment (U24, weight is 0.5638); the main indicator that affects convenience of life (U3) is service facilities (U32, weight is 0.6370); the main indicator that affects save resources (U4) is energy-saving and energy utilization (U42, weight is 0.5638); the main indicator that affects livable environment (U5) is site ecology and landscape (U51, weight is 0.7500); the main indicator that affects smart (U6) is smart operation (U63, weight is 0.6370); the main indicators that affect innovation and characteristics (U7) are improvement and innovation (U71, weight is 0.5000) and characteristics (U72, weight is 0.5000).Figure 1
The weighting diagram of the criterion layer indicators.Figure 2
The weighting diagram of scheme layer indicators. (a) Weights ofU11 – U12. (b) Weights of U21 – U24. (c) Weights of U31 – U33. (d) Weights of U41 – U44. (e) Weights of U51 – U52. (f) Weights of U61 – U63. (g) Weights of U71 – U72.
(a)(b)(c)(d)(e)(f)(g)The overall ranking of indicator weights is shown in Figure3. Among all the impact indicators, the most important is smart operation (U63), followed by energy-saving and energy utilization (U42), followed by safety (U11), water-saving and water resources utilization (U43), and smart architecture and platform (U62).Figure 3
Comparison of weights of indicators.


## 5.4. Determine the Set of Evaluation Criteria

The evaluation standard set of green and smart building projects selects the five-star evaluation system in the “Smart Building Evaluation Standards,” which are one-star, two-star, three-star, four-star, and five-star. UseV to denote the set of evaluation criteria; then they are as follows:(12)V=V1,V2,V3,V4,V5,=one−star, two−star, three−star, four−star, five−star,=0∼20,20∼50,50∼70,70∼90,90∼100.


## 5.5. Fuzzy Comprehensive Evaluation of Criterion Level

According to the actual situation of the project, this paper consulted a 10-member expert group composed of experts in the construction, environmental protection, and real estate industries by collecting relevant information and using questionnaire surveys and collected the expert group’s review opinions on green and smart building projects. The fuzzy evaluation matrix is as follows:Safety and durability index matrix:(13)PU1=0.20.40.20.10.10.20.50.20.10.Health and comfort index matrix:(14)PU2=0.10.60.10.10.10.30.40.3000.40.60000.20.50.300.Convenience of life index matrix:(15)PU3=0.40.50.1000.10.50.4000.30.40.300.  Save resources index matrix:(16)PU4=0.10.50.20.10.10.10.60.20.100.30.40.3000.20.60.200.Livable environment index matrix:(17)PU5=0.10.50.30.100.20.60.200.Smart index matrix:(18)PU6=0.20.50.10.200.40.40.2000.20.60.200.Innovation and characteristics index matrix:(19)PU7=0.50.50000.30.60.100.According to the steps of the improved AHP method, the calculated weight vectorW of each evaluation index is established, the fuzzy evaluation matrix is established, and the comprehensive evaluation vector of the criterion layer (first-level indexes) is calculated according to the formula Y=W×P.Comprehensive evaluation vector of safety and durability index:(20)YU1=WU1×PU1=0.7500,0.2500×0.20.40.20.10.10.20.50.20.10=0.2000,0.4250,0.2000,0.1000,0.0750.Comprehensive evaluation vector of health and comfort index:(21)YU2=WU2×PU2=0.1178,0.0550,0.2634,0.5638×0.10.60.10.10.10.30.40.3000.40.60000.20.50.300=0.2464,0.5326,0.1974,0.0118,0.0118.Comprehensive evaluation vector of convenience of life index:(22)YU3=WU3×PU3=0.1047,0.6370,0.2583×0.40.50.1000.10.50.4000.30.40.300=0.1831,0.4742,0.3428,0.0000,0.0000.Comprehensive evaluation vector of save resources index:(23)YU4=WU4×PU4=0.0550,0.5638,0.2634,0.1178×0.10.50.20.10.10.10.60.20.100.30.40.3000.20.60.200=0.1645,0.5418,0.2263,0.0619,0.0055.Comprehensive evaluation vector of livable environment index:(24)YU5=WU5×PU5=0.7500,0.2500×0.10.50.30.100.20.60.200=0.1250,0.5250,0.2750,0.0750,0.0000.Comprehensive evaluation vector of smart index:(25)YU6=WU6×PU6=0.1047,0.2583,0.6370×0.20.50.10.200.40.40.2000.20.60.200=0.2517,0.5379,0.1895,0.0209,0.0000.Comprehensive evaluation vector of innovation and characteristics index:(26)YU7=WU7×PU7=0.5000,0.5000×0.50.50000.30.60.100=0.4000,0.5500,0.0500,0.0000,0.0000.


## 5.6. Fuzzy Comprehensive Evaluation of Target Layer

Using the relevant calculation rules of the fuzzy comprehensive evaluation, and according to the calculation results of the fuzzy comprehensive evaluation of the criterion layer (first-level indexes), construct the target layer fuzzy evaluation matrix of this project; then, the target layer fuzzy evaluation matrix is(27)PU=0.20000.42500.20000.10000.07500.24640.53260.19740.01180.01180.18310.47420.34280.00000.00000.16450.54180.22630.06190.00550.12500.52500.27500.07500.00000.25170.53790.18950.02090.00000.40000.55000.05000.00000.0000.According to formulaY=W×P, the comprehensive evaluation vector of the target layer is(28)YU=WU×PU=0.1481,0.0607,0.0253,0.3451,0.0607,0.3451,0.0151×0.20000.42500.20000.10000.07500.24640.53260.19740.01180.01180.18310.47420.34280.00000.00000.16450.54180.22630.06190.00550.12500.52500.27500.07500.00000.25170.53790.18950.02090.00000.40000.55000.05000.00000.0000=0.2064,0.5200,0.2112,0.0487,0.0137.According to the principle of the maximum degree of membership, the comprehensive evaluation level of the green smart building project can be determined. The maximum comprehensive evaluation value of the green intelligent building project in this case is0.5200, which belongs to the two−star level of the set of evaluation criteria. Then, we use the formula S=Y×GT to calculate the comprehensive evaluation value of the green smart building project and obtain the quantified comprehensive evaluation result, where the value of the quantified evaluation standard set G is the median value of the corresponding value in the evaluation standard set V. So, the quantified comprehensive score S is(29)S=YU×GT=0.2064,0.5200,0.2112,0.0487,0.0137×10,35,60,80,95T=38.1330.


## 5.7. Analysis of Evaluation Results

Through the above calculations, it is shown that the project developed by XM Zhengpeng Real Estate Co., Ltd., is a two-star building. According to the quantified comprehensive evaluation calculation result, the comprehensive score of the overall evaluation of the project is corresponding to the two-star level. If you score according to the judging rules rules in Table1, you can get consistent results. However, the judging rules’ scoring method needs to determine the weight or value of the rules, which also increases the workload of the experts for scoring. The improved AHP-FCE method can reduce the corresponding workload and improve work efficiency.


## 6. Conclusions and Recommendations

From the analysis of the evaluation results, it can be seen that smart and green building sustainability have become the core of modern green buildings. The main indicators that have an impact on the development of green smart buildings include safety and durability indicators, health and comfort indicators, convenience of life indicators, save resources indicators, livable environment indicators, smart indicators, and innovation and characteristics indicators. Under the premise of these seven indicators, a fuzzy comprehensive evaluation model for green smart building projects was established, and this evaluation system was verified through corresponding cases, which further enriched the green smart building evaluation system.In order to promote the implementation of my country’s green and smart building strategy and improve the level of green economy development, the following points should be given priority: (1) Firstly, we should focus on save resources. Green smart buildings are the inevitable trend of future development. Scientific management and advanced green and clean environmental protection technologies should be used in their development so as to improve energy efficiency, reduce building energy consumption, and improve people’s quality of life. Therefore, local governments should vigorously support the development of green buildings, further increase research on the development of green building products, and promulgate relevant policies for support and subsidies in order to accelerate the upgrading of the green and smart building industry. (2) Secondly, in terms of smart, it is necessary to make full use of the Internet of Things, 5G, big data, cloud computing, artificial intelligence, and other technologies to create an economical, safe, reliable, efficient, convenient, and green ecological living environment through automatic sensing, ubiquitous connection, timely transmission, and information integration. While strengthening the utilization of green and smart building resources, qualified enterprises should be encouraged to explore and innovate more advanced management systems and smart management. (3) In terms of safety and durability, attention should be paid to the safety and durability of buildings to avoid “fragile buildings.” Starting from the full life cycle of the building, improve the seismic performance of the building and the durability of structural components, and ensure the safety of people’s lives.Green smart buildings are developing rapidly. We should constantly learn from experience and adjust the direction in the course of its development so as to explore an optimal development path. In the context of carbon peaks and carbon neutrality, leading companies in green smart buildings should adhere to the green, environmentally friendly, and healthy production concepts and strive to explore zero-carbon buildings to provide a “green model” for the development of the industry.



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*Source: 5485671-2021-11-26.xml*