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As an important product characteristic, maintainability is recognized as a highly significant factor in the economic success of engineering systems and products. Based on virtual reality technology, this paper aims to create an intuitive, immersive and interactive environment for product maintenance. In order to analyze and evaluate the product maintainability in a virtual maintenance environment, fuzzy comprehensive evaluation is used. At the early design stage, maintainability influencing factors are analyzed and the whole maintainability evaluation of the product is given by using fuzzy comprehensive evaluation method in virtual maintenance environment.

The paper provides a fuzzy comprehensive evaluation method for product maintainability evaluation in virtual environment.

Fuzzy comprehensive evaluation is used to evaluate product maintainability in virtual environment, and the application of virtual maintainability system is expanded.

According to maintainability requirement, the maintainability index set is built in this paper, and fuzzy comprehensive evaluation method is used to evaluate product maintainability in virtual maintenance environment at stage of early design.

The purpose of this paper is to use artificial intelligence to evaluate the risks of urban power network planning.

A fuzzy Bayesian least squares support vector machine (LS_SVM) model is established in this paper, which can learn the risk information of urban power network planning through artificial intelligence and acquire expert knowledge for its risk evaluation. With the advantage of possessing learning analog simulation precision and speed, the proposed model can be effectively applied in conducting a risk evaluation of an urban network planning system. First, fuzzy theory is applied to quantify qualitative risk factors of the planning to determine the fuzzy comprehensive evaluation value of the risk factors. Then, Bayesian evidence framework is utilized in LS_SVM model parameter optimization to automatically adjust the LS_SVM regularization parameters and nuclear parameters to obtain the best parameter values. Based on this, a risk comprehensive evaluation of urban network planning based on artificial intelligence is established.

The fuzzy Bayesian LS_SVM model established in this paper is an effective artificial intelligence method for risk comprehensive evaluation in urban network planning through empirical study.

The paper breaks new ground in using artificial intelligence to evaluate urban power network planning risks.

The purpose of this paper is to propose a method for assessing the lean construction management performance (LCMP) of engineering projects using the analytic network process-fuzzy comprehensive evaluation (ANP-FCE) model.

Literature review and questionnaire surveys were used to achieve an evaluation index system for LCMP. The data needed to calculate the weights of the indices were derived from questionnaire surveys. The ANP and the Super Decisions (SD) software were used to calculate the weights of the indices and verify the validity of the weights. The FCE was adopted to carry out a comprehensive evaluation of LCMP, and the validity of the evaluation results was verified by applying the validity degree of maximum membership principle. The applicability of the method for evaluating LCMP was validated by empirical research.

The proposed method for assessing the LCMP using the ANP-FCE model is validated to be feasible. Decision makers can easily identify the strengths and weaknesses of lean construction (LC) management of the evaluated project from the evaluation results.

Some subjectivity may exist in the assessment process due to questionnaire surveys, and only one case has been studied to validate the applicability of the method. Therefore, researchers are encouraged to increase the number of LC experts and cases over the world to make the proposed method more standard.

The research is expected to propose an assessment method of LCMP for construction enterprises, provide a reference to develop assessment standards for LCMP for building associations or governments and help decision makers know the improving path of LC management.

This research contributes to the literature by summarizing the commonly used lean management tools for quality, cost, time, safety and organization in practice, and proposing a novel approach for assessing the LCMP of engineering projects. The study is useful for researchers, project managers and decision makers engaged in LC.

Mega construction projects (MCPs), characterized by their vast scale, numerous stakeholders and complex management, often face significant uncertainties and challenges. While existing research has explored the complexity of MCPs, it predominantly focuses on qualitative analysis and lacks systematic quantitative measurement methods. Therefore, this study aims to construct a complexity measurement model for MCPs using fuzzy comprehensive evaluation and grey relational analysis.

This study first constructs a complexity measurement framework through a systematic literature review, covering six dimensions of technical complexity, organizational complexity, goal complexity, environmental complexity, cultural complexity and information complexity and comprising 30 influencing factors. Secondly, a fuzzy evaluation matrix for complexity is constructed using a generalized bell-shaped membership function to effectively handle the fuzziness and uncertainty in the assessment. Subsequently, grey relational analysis is used to calculate the relational degree of each complexity factor, identifying their weights in the overall complexity. Finally, the weighted comprehensive evaluation results of project complexity are derived by combining the fuzzy evaluation results with the grey relational degrees.

To validate the model’s effectiveness, the 2020 Xi’an Silk Road International Conference Center construction project is used as a case study. The results indicate that the overall complexity level of the project is moderate, with goal complexity being the highest, followed by organizational complexity, environmental complexity, technical complexity, cultural complexity and informational complexity. The empirical analysis demonstrates that the model can accurately reflect the variations across different dimensions of MCP complexity and can be effectively applied in real-world projects.

This study systematically integrates research on MCPs complexity, establishing a multidimensional complexity measurement framework that addresses the limitations of previous studies focusing on partial dimensions. Moreover, the proposed quantitative measurement model combines fuzzy comprehensive evaluation and grey relational analysis, enhancing the accuracy and objectivity of complexity measurement while minimizing subjective bias. Lastly, the model has broad applicability and can be used in MCPs across different countries and regions, providing a scientific and effective basis for identifying and managing MCP complexity.

The purpose of this paper is to establish an evaluation index system to select the reverse‐logistics servicer of electronic products, based on characteristics of electronic products' recycling and reuse.

First of all, according to the characteristics of electronic products' recycling and reuse, an evaluation index system is designed to select its reverse‐logistics servicer, then the index weights are determined by factor analysis method based on abundant investigation. Finally, the fuzzy comprehensive evaluation method is used to evaluate and select a reverse‐logistics servicer of electronic products.

The results are convincing: an evaluation index system is developed according to the characteristics of electronic products' recycling and reuse, and then the index weights are determined by factor analysis method.

The method exposed in the paper can be used to evaluate and select a reverse‐logistics servicer of electronic products.

The paper succeeds in realising both designing of an evaluation index system according to characteristics of electronic products' recycling and reuse, and in determining the index weights by the factor analysis method based on abundant investigation.

The purpose of this paper is to propose a new assessment methodology for the African Peer Review Mechanism (APRM) using fuzzy comprehensive evaluation method (FCEM) and the Delphi technique. The proposed approach by its design simplifies the review processes and also quantifies the outcome of the assessment result for easier interpretation and benchmarking among member countries. The proposed hybrid method demonstrates how the subjective APRM thematic areas and their objectives can be efficiently tracked country by country while addressing the key identified challenges.

Using a numerical example, a demonstration of how the APRM assessment could be carried is shown using the FCEM and the Delphi method. The APRM's own thematic areas are used as the evaluation factors and the weights are assigned using Delphi technique. A novel remark set is constructed to linguistically describe the performance of a country against each or all of the thematic areas. Then in line with the maximum membership degree principle, the position of the maximum number would correspond to its respective remark element to indicate the level of performance.

The result shows a hybrid method of FCEM and Delphi used to determine whether a member country has “achieved”, “on track”, “very likely to be achieved”, “possible if some changes are made” or “off-track” on the four focus areas of the APRM. The method provides a well-organized way of tracking progress of member countries. It is also an ideal method of tracking progress of individual thematic areas and objectives. Moreover, the simplicity of the proposed method, the preciseness of the final result it generates and the clear interpretation of the result makes it a stronger alternative to the current approach for assessing member countries.

The APRM is a respected body with the backing of the heads of state in Africa. As most African countries become conscious of the pressure to meet international standards as far as governance performance is concerned, this proposed assessment methodology if adopted would go a long way in improving performance evaluation on the continent.

The proposed methodology is unique in its simplicity and its ability to evaluate any of the APRM thematic areas independent of the others. This means an overall performance can be tracked as well as that of individual evaluation factors.

This paper improves the evaluation index system of green building operation effect and establishes the evaluation model of green building operation effect. It is expected to promote energy saving and emission reduction and provide a more scientific evaluation method for green building operation effect evaluation.

First, 20 key evaluation indexes are selected to establish the operation effective evaluation index system. Then, the combined weight method is proposed to determine the weight of each evaluation index. Next, the gray clustering-fuzzy comprehensive evaluation method is used to construct the green building operation effective evaluation model. Finally, the feasibility and validity of the selected model were verified by taking Shenzhen Bay One green building in Shenzhen as an example.

This paper establishes the evaluation system of green building operational effect, and evaluates green building from the angle of operational effect. Taking Shenzhen Bay One project as an example, the rationality and applicability of the model are verified.

In this paper, for the first time, relevant indexes of user experience are included in the evaluation system of green building operational effect, which makes the evaluation system more perfect. In addition, a more scientific fuzzy gray clustering method is used to evaluate the operational effect of green building, and a new evaluation model is established.

To achieve sustainability for a construction project requires the achievement of economic, environmental and social sustainability at the same time. The economic sustainability of a project should be built into the stipulated cost. The unbalanced bidding always contribute cost overrun for a construction project. The purpose of this paper is to develop a method for identifying unbalanced bidding.

The problem of identifying unbalanced bidding is a comprehensive evaluation problem. All line items and bidders in bills of quantities are evaluation factors and evaluation objects, respectively, and the engineer’s estimated prices are considered as the evaluation benchmarks. The weights of these factors are determined through integrating the entropy weight method and the analytic hierarchy model, which consider subjective and objective factors in the weighting process.

The proposed model can be used to quantitatively evaluate unbalanced bids. The identification process can be analyzed within a short period, specifically with the aid of Microsoft Excel, reducing delays in awarding contracts. The results show that the model will support owners as they efficiently and effectively identify unbalanced bids in the bid evaluation stage to mitigate the negative consequences of unbalanced bidding.

A case study is given to verify the feasibility and practicability of the proposed method, which not only assists owners in efficiently and effectively identifying unbalanced bidding, but also promotes the economic sustainability of construction projects.

The fuzzy comprehensive evaluation method is used to detect unbalanced bidding, allowing owners to be objective as they identify and reduce unbalanced bidding at the procurement stage.

In this study, a novel framework was proposed to assess the trust in e-government (e-Gov) services under an uncertain environment. The proposed framework was applied in Iranian municipality websites of e-Gov services to evaluate the readiness score of trust in e-Gov services.

A unique hybrid research methodology was proposed. In the first phase, a comprehensive set of indices were determined from an extensive literature review and finalized by employing the fuzzy Delphi method. In the second phase, interval-valued intuitionistic fuzzy set (IVIFS) -was utilized to model the problem's uncertainty with analytic called IVIFS- hierarchy process (AHP) to determine the importance of indices and indicators by assigning the weights. In the third phase, the fuzzy evaluation method (FEM) is followed for assessing the readiness score of indices in case studies.

The findings indicated that “Trust in government” is the most significant index affecting citizen's trust in e-Gov services while “Maintenance and support” has the least impact on user's intention to use e–Gov services.

The study contributes by introducing a unique research methodology that integrates three phases, including fuzzy Delphi, IVIFS AHP and fuzzy evaluation method. Moreover, the fuzzy sets theory helps to reach a more accurate result by modeling the inherent ambiguity of indicators and indices. Interval-valued intuitionistic fuzzy models the ambiguity of experts' judgments in an interval.

The study helps policy makers to monitor wider aspects of trust in e-Gov services as well as understanding their importance. The study enables policy makers to apply the framework to any potential case studies to evaluate the readiness score of indices and recognizing strengths and weakness of trust dimensions as well as recommending advice for improving the situation.

The study is one of the few to indicate significant indices of trust in e-Gov services in developing countries. The study shows the importance of indicators and indices by assigning a weight. Additionally, the framework can assess the readiness score of various case studies.

The ergonomic performance of protective clothing for earthquake disaster search and rescue team members is significant for its protective performance. The paper aims to discuss these issues.

By experimental simulations of the rescue tasks, an evaluation system for the protective clothing in both static and dynamic conditions was designed and established in this study. In static evaluation, motion capture system was used to measure the ranges of motions. The mobility was analyzed by the comprehensive evaluation method. In dynamic experiments, three types of rescue tasks were simulated for ergonomic evaluation. The results were analyzed based on the multi-levels joint evaluation method.

It was shown that the established evaluation system could meet well with the requirements of the ergonomic evaluation.

Fuzzy comprehensive evaluation method is an effective tool in ergonomic evaluation of clothing. The newly designed coverall and suit are of better ergonomic performance compared with the in-service clothing.