Fuzzy Comprehensive Evaluation Research Articles

The Comparison and Selection of a Warm Mix Agent for Asphalt Based on Fuzzy Hierarchical Analysis

Warm mix asphalt pavements can effectively reduce construction energy consumption and control environmental pollution compared to conventional asphalt pavements. However, there is no clear test standard for the evaluation of warm mix agents. The selection of a warm mix agent is easily influenced by subjective factors. Moreover, it is difficult to consider quantitative and qualitative factors such as technical indexes and the economy. A fuzzy hierarchical comprehensive evaluation model of warm mix agents is proposed based on fuzzy hierarchical analysis. Four types of indexes, namely, material properties, technical indexes, economy, and construction difficulty, were selected to construct the hierarchical structure of the target, guideline, and indicator layers. The influence weights of all factors were determined by the judgment matrix, and an affiliation judgment matrix was established at the same time. Finally, the comprehensive score of the warm mix agent modification effect was calculated. Three warm mix agents were selected for market research and indoor testing. And the evaluation model was applied to process the data. The calculation results show that the technical indicators have the greatest influence, with a weight proportion of 0.493; WM-2 had the best comprehensive evaluation, with a comprehensive score of 0.96, and its optimal mixing amount was 0.3%. The calculation results further verified the effectiveness of the fuzzy hierarchical comprehensive evaluation model of warm mix agents. Compared with the existing methods, the fuzzy-hierarchical-integrated evaluation model of warm mix agents has a more comprehensive evaluation scope, lower subjective factor bias, and more flexible application scenarios. It provides a more rigorous and convenient idea for the development and evaluation of different warm mix agents. In conclusion, the model has greater application value and popularization value.

The Effect of Environmental Awareness on the Management of Higher Education

Higher education management is an important way to cultivate college students' awareness and behavior of ecological environment protection. The survey results show that at present, college students mainly rely on theoretical courses and lectures to receive ecological civilization education, but they lack practical links, which is different from the goal of ecological civilization education. Therefore, this paper comprehensively considers the weight of eco-environmental protection consciousness to higher education management and their relationship by using fuzzy comprehensive evaluation analysis method, which provides scientific basis for relevant decision-making. On the whole, fuzzy comprehensive evaluation analysis method can help to deeply understand the relationship between different factors and provide strong support for promoting eco-environmental protection in higher education management.

Intelligent visual analysis of accident behavior and mechanism inherent in ship collision accident data

The analysis of ship collision accident data plays a crucial role in ensuring maritime transportation safety. This paper proposes an intelligent visual analysis-based method focusing on the co-occurrence patterns, collision risk, similarity analysis, and classification of ship collision data. Based on data from 1573 maritime accidents that occurred globally between 2010 and 2023, this paper first designs co-occurrence patterns to identify regularities between accident attributes. Second, a fusion model combining fuzzy comprehensive evaluation and logistic regression is developed to calculate ship collision risk, and the model is applied to reconstruct and visually analyze the collision process. Third, the similarity between two collision accidents is analyzed based on Sentence-BERT algorithm, and a heterogeneous graph neural network model is constructed for accident classification. Finally, all the analysis contents are integrated into the visual analysis system of the ship collision accident data to illustrate the accident behavior and mechanism inherent in ship collision accident data. The rich content within the visualization system provides trainee crew members with a more comprehensive understanding of accidents and serves as a reference for maritime management agencies to analyze similar and related accidents, derive lessons learned, identify high-risk areas, and formulate targeted risk management strategies.

A Fuzzy Gold Mineral Prediction Model Integrating with Knowledge-Driven and Data-Driven: A Case Study of the Hatu Region in Xinjiang, China

As mineral resources become increasingly scarce, the search for potential ore deposits presents a significant challenge in geological exploration. Subjective factors often constrain traditional knowledge-driven approaches, while purely data-driven methods may overlook the geological significance of data relationships, potentially compromising the accuracy and reliability of predictions. To address these issues, this study proposes a novel mineral prediction model that integrates fuzzy comprehensive evaluation with both knowledge-driven and data-driven approaches (FCEKDD), resulting in an optimized comprehensive mineral prediction model based on multi-source geoscience data. This model establishes comprehensive exploration indicators based on expert knowledge and quantitatively assesses these indicators through fuzzy evaluation methods to evaluate mineralization potential, thereby delineating exploration targets within the study area. Ultimately, a three-layer predictive framework is constructed using the C-A fractal method. Experimental results indicate that 57.1% of known mineral points are within the primary prediction zone, thus demonstrating the model’s high predictive accuracy. Comparisons with a random forest model reveal that the FCEKDD model has advantages in addressing geoscience data uncertainty and interpreting geological phenomena. This research validates the reliability and applicability of the proposed model in mineral exploration mapping, providing an effective solution for future mineral resource exploration.

Safety Risk Assessment Method of In-Service Stage Suspension Equipment Based on Grey Fuzzy Comprehensive Evaluation

Performance safety is one of the important goals for the high-quality development of modern performance services. The in-service stage suspension equipment that has been put into use is one of the most frequently used and most closely related stage machinery in performances, and there are often significant safety hazards during its use. In response to the current lack of safety risk assessment methods and incomplete assessment techniques for in-service stage suspension equipment, this paper proposes a safety risk assessment method for in-service stage suspension equipment based on grey fuzzy comprehensive evaluation, with professional theaters as the target scenario. This method first identifies risk factors based on Failure Mode and Effects Analysis (FMEA), then uses the grey relational analysis (GRA) method for risk factor analysis, and finally adopts the fuzzy comprehensive evaluation (FCE) method to achieve safety risk level assessment. By constructing and analyzing an evaluation model for professional theater stage suspension equipment, the safety risk levels and corresponding safety risk factor rankings of performance accidents such as electric shock, falling, and failure can be obtained, and measures to reduce risks can be provided based on the most important risk factors. The research results show that more attention should be paid to the influence of human factors in the safety assessment and detection of in-service stage suspension systems. The research in this article is of great significance for improving the safe use of in-service stage suspension equipment, enhancing the level of performance safety management, and improving the quality of performance equipment services, laying the foundation for the formation of relevant regulatory systems and standards.

A Three-Level Service Quality Index System for Wind Turbine Groups Based on Fuzzy Comprehensive Evaluation

A Three-Level Service Quality Index System for Wind Turbine Groups Based on Fuzzy Comprehensive Evaluation

How to Evaluate the Operating Performance of Mid-Deep Geothermal Heat Pump Systems (MD-GHPs): A Study on a Multistage Evaluation Index System

Mid-deep geothermal heat pump systems (MD-GHPs) use mid-deep borehole heat exchangers (MDBHEs) to extract heat from the geothermal energy at a depth of 2–3 km, and have been used for space heating in China over the last decade. This paper proposes a comprehensive and multilevel evaluation-index system to analyze and evaluate the energy performance of MD-GHPs. The multilevel evaluation index system consists of a target layer, a criterion layer, and an index layer, where the criterion layer is subdivided into six aspects and the index layer includes 26 specific indices, reflecting the geothermal resources, heat transfer performance of the MDBHEs, energy efficiency of the heat pump systems, building space heating demand, grid dynamic response capability, and energy-saving and economic benefits. Then, based on both expert survey results and case study data, the entropy weight method and the analytic hierarchy process are integrated to determine indicator weight coefficients among the multilevel evaluation indices, comprehensively considering both subjective and objective analyses. Furthermore, a fuzzy comprehensive evaluation model is conducted to integrate these weighted indices into a multi-criteria evaluation of MD-GHP performance. Finally, the proposed method was applied to evaluate the practical performance of four projects, returning scores of 61.56, 58.33, 72.73, and 78.41. These evaluations enable an overall assessment of the energy performance of MD-GHPs, reflecting the technical weaknesses and offering optimization guidance for system design and operation.

High Quality Development of Ecotourism Along the Middle and Lower Reaches of the Yellow River Based on Big Data

The Yellow River basin is an important economic zone and an important ecological barrier in China. The ecological environment protection of the Yellow River basin is an important direction for the development of ecotourism. Promoting the ecological protection and high-quality development of the Yellow River basin through ecotourism can realise the rational utilisation of ecological resources development and environmental protection functions. This paper takes wetland scenic spots as the main research object, and under the guidance of high-quality development theory, environmental education theory, education evaluation and other related theories, conducts field research on the current situation of eco-tourism environmental education in wetland scenic spots in the Yellow River basin. Based on the expert opinions and literature analysis, the evaluation index system of ecotourism environment of wetland scenic spots in the Yellow River basin is constructed. The Yellow River estuary and sand lake ecotourism scenic spots are selected as the case sites, and the entropy weight fuzzy comprehensive evaluation method is used for comprehensive evaluation, and the reasons for the evaluation results are analysed. This model has laid a theoretical foundation for the research on the high-quality development of ecotourism along the middle and lower reaches of the Yellow River in the context of big data.

Understanding Impacts of Neighbourhood Micro-Renewal Through a Lens of Place Value: A Case Study of Wuhan, China

Neighbourhood micro-renewal (NMIR) plays a critical role in the renewal landscape of urban China. However, an oversight in post-occupancy evaluation (POE) impedes the comprehensive understanding of NMIR’s impact and post-implementation efficacy. This research addresses this gap by leveraging the lens of place value to examine NMIR’s outcomes. Using Wuhan, China, as a case study, 10 Delphi consultations and 28 interviews were conducted among five stakeholder groups: local government, planning professionals, academics, community workers, and residents. Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE) were combined to identify and rank potential indicators. A total of 6 primary and 22 secondary indicators were identified. The indicators were derived from four key policy areas—health, society, economy, and environment—highlighting the relationship among NMIR initiatives, their contribution to place quality, and alignment with policy goals. AHP and FCE results reveal substantial enhancements in environmental quality, residential properties, and public infrastructure. Nevertheless, the analysis exposes varied satisfaction levels and divergences in the perceived relevance of indicators among the government, professionals, and the residents, particularly concerning social cohesion. These disparities underscore the layered impacts of NMIR. This research recommends integrating resident feedback with expert insights to enhance place quality in NMIR projects by balancing physical upgrades with social considerations. It also advocates for a continuous, adaptable post-occupancy evaluation system to monitor and support place value over time. This system should be flexible and context-specific, allowing NMIR initiatives to adapt to diverse urban settings globally, thus supporting long-term sustainability and thriving urban communities.

Measuring complexity in mega construction projects: fuzzy comprehensive evaluation and grey relational analysis

PurposeMega 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.Design/methodology/approachThis 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.FindingsTo 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.Originality/valueThis 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.

A Comparative Analysis of the Sustainable Development of Urban Agriculture in Chengdu and Singapore

With the deepening global concern for sustainable development, urban agriculture has received more and more attention as an important combination of urban development and ecological environmental protection. This paper provides a comprehensive evaluation and comparison of two areas, Chengdu and Singapore, in terms of their capacity for sustainable development of urban agriculture through an empirical analysis method. To make a multidimensional evaluation index system, the study uses the hierarchical analysis method (AHP) and the fuzzy comprehensive evaluation method. The index covers important areas like the level of agricultural development, the intensity of applied inputs, the rate of energy use, the rate of resource utilization, and the level of agricultural factors. The results show that Chengdu performs significantly in terms of resource utilization rate and agricultural factor level, while Singapore performs better in terms of energy utilization rate. The study provides targeted recommendations, including strengthening scientific and technological innovation, policy support, and ecological and environmental protection, with the aim of providing references and lessons for the sustainable development of urban agriculture in the two places and other areas around the world.

The Study of Risk Assessment Method for Ship Berthing Based on the “Human-Ship-Environment” Synergy

Berthing is one of the most dangerous phases in the process of ship navigation, and its risk assessment is crucial for both ship safety and port scheduling. To effectively enhance the safety and reliability of the berthing process, a berthing risk assessment method based on the synergy of “human-ship-environment” has been established. First, the impact of the human, ship, and environmental factors on berthing risk was analyzed, and a risk assessment index system for ship berthing was constructed. Then, the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation (FCE) methods were employed for a comprehensive risk assessment. AHP was used to determine the weight of each factor reasonably, while FCE was applied for the evaluation of the berthing risk. Finally, the proposed method was applied to evaluate the berthing operations of two ships, namely the KCS ship type and the S-175 large passenger ship type, at the Qingdao Intelligent Ship Testing Field, China. The experiment’s results indicate that the evaluation results of the method proposed here have good consistency with the expert survey method.

Exploring Asymmetric Gender-Based Satisfaction of Delivery Riders in Real-Time Crowdsourcing Logistics Platforms

This study investigates gender-based differences in the satisfaction ranking of riders on real-time crowdsourcing logistics platforms, using online reviews from the Ele.me platform. Quantitative methods, including the frequency ratio-based Analytic Hierarchy Process (AHP), probabilistic linguistic term sets (PLTS), and fuzzy comprehensive evaluation (FCE), were applied to analyze satisfaction differences between men and women riders. The findings reveal an asymmetric pattern in satisfaction preferences: women riders place more emphasis on perceived value, while men riders prioritize service perceived quality. Although both groups rank platform image, product perceived quality, and rider expectations similarly, the importance of these factors varies significantly, indicating an underlying asymmetry in their expectations and values. Women riders express higher satisfaction with platform image, rider expectations, service perceived quality, and product perceived quality, with rider expectations showing the largest difference. Additionally, the multi-criteria decision-making methods used in this study offer insights for optimizing service performance in real-time crowdsourcing logistics platforms, particularly in handling uncertainty and enhancing system adaptability through fuzzy sets. These findings provide a basis for developing gender-specific strategies aimed at enhancing rider satisfaction, minimizing turnover, and improving platform adaptability—contributing to a more inclusive and sustainable logistics supply chain.

Dynamic fuzzy comprehensive evaluation of wet friction components performance degradation based on G1-CRITIC

High power density wet friction components are crucial in heavy equipment transmission systems, directly influencing equipment reliability. This paper proposes a fuzzy comprehensive evaluation method with combined weighting, which dynamically divides the performance degradation of wet friction components into three stages. It constructs a multi-indicator, multi-level evaluation system, in which the performance degradation data is obtained from the wet clutch accelerated life test. Additionally, we utilize the combined weighting method to dynamically allocate weights for evaluation indicators at different stages and introduce the trapezoidal distribution membership function. The accuracy of the fuzzy comprehensive evaluation model is then verified by using two prediction models as a comparison method. The results indicate that the model achieves an average relative error of 14.79% and a correlation coefficient R2 of 0.9580, indicating higher usability and accuracy than the prediction models. Furthermore, the evaluation indicator weights are more sensitive to pressure variations.

RETRACTION: Supply Chain Risk Management of Badminton Supplies Company Using Decision Tree Model Assisted by Fuzzy Comprehensive Evaluation

Retraction: D. Zhang, Y. Tang, and X. Yan, “,” Expert Systems 41, no. (2024): . https://doi.org/10.1111/exsy.13275. The above article, published online on 05 March 2023, in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor‐in‐Chief, David Camacho; and John Wiley & Sons Ltd. The article was submitted as part of a guest‐edited special issue. Following publication, it has come to the attention of the journal that this article was accepted solely on the basis of a compromised peer review process. The editors have therefore decided to retract the article. The authors did not respond to the notice of retraction.

Design of Digital Economy Industry Investment Decision Support System Based on Fuzzy Comprehensive Evaluation Method

Design of Digital Economy Industry Investment Decision Support System Based on Fuzzy Comprehensive Evaluation Method

Snow Resource Reutilization: Design of Snow Collection and Compression Equipment Based on Functional Analysis Method

High-latitude regions of the Earth are rich in natural snow resources; however, owing to their negative impact on daily life, they have not been effectively utilized for a long time and are instead viewed as obstacles that require substantial resources for clearance. This waste of resources contradicts the principles of sustainable development. With the rapid development of the ice and snow industry, the social and economic value of snow resources is gradually becoming apparent. Therefore, to promote sustainable social and economic development, this study explores new methods for processing snow resources to achieve their recycling and high-value transformation. This study employs the functional analysis method to analyze and solve the functions of the design system, utilizing the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation for the objective assessment and selection of schemes. The obtained relative optimal principles are utilized to guide the parameter setting and innovative design of the scheme in terms of functional structure. After the final scheme is output, its feasibility is verified through finite element simulation. Ultimately, to address the issue of snow resource clearing and recycling, this study designs a product scheme capable of collecting and compressing snow on road surfaces, proposing the use of snow in the form of standardized compressed snow blocks for large-scale snow sculpture construction and other fields. This method significantly reduces the cost of snow sculpture production, enhances efficiency, realizes the comprehensive utilization and high-value transformation of snow resources, and provides a reference for the sustainable development of the low-altitude ice and snow tourism industry.

Research on Navigation Risk Assessment of Unmanned Ship Under Complex Navigation Conditions

With the research on unmanned ships conducted by the International Maritime Organization, the European Union and China, the navigation risk of unmanned ships has become a hot topic around the world. Based on the research and development history and current situation of unmanned ships at home and abroad, focusing on the three key elements of “Unmanned Ship, shore-based control personnel, external navigation environment”, this study establishes a navigation risk index system for unmanned ships under complex navigation conditions, considering the particularity of the unmanned ship, its perception ability, environmental understanding, situation judgment, communication ability and other indicators. The analytic hierarchy process is used to solve the weight of all kinds of navigation risk factors, and a consistency test of the established index system is carried out. Through expert investigation, the fuzzy membership set of risk indexes is established, and a fuzzy comprehensive evaluation model is established to evaluate the navigation risk of unmanned ships under complex navigation conditions. To avoid the situation of single-factor information being inundated, this study adopts the method of fuzzy comprehensive evaluation from a low level to a high level, and it verifies the algorithm through cases, which proves the validity and rationality of the proposed risk assessment method.

A fuzzy comprehensive evaluation method for assessing the damage degree of cultural relics based on an improved AHP-EWM coupled weight model and a modified ridge function

Due to long-term exposure to outdoor environments, stone artifacts exhibit complex and varying degrees of disease that need to be conserved urgently in order to perpetuate their historical, artistic and scientific values. Owing to the varying degrees of damage inflicted upon cultural relics, discrepancies exist in intervention strategies and conservation materials employed. Hence, it is considerably crucial to conduct a scientific and precise assessment of the preservation status of cultural relics at an early stage for the advancement of cultural relic conservation efforts. In this research, three masonry components of the Hailongtun Fortress site were selected as study objects. A secondary fuzzy comprehensive evaluation system was established through selecting a total of 12 indicators from four aspects, namely, surface change, rock mass structure, physical properties and matrix weathering. The weight of each indicator was determined by using an improved AHP-EWM weight coupling model. The membership degree was calculated by selecting a modified ridge function. The asymmetric nearness method was employed in the final decision-making process so as to correct the error caused by the principle of maximum membership degree. The research shows that the results of the improved evaluation method are in line with the real damage degree of each masonry component, which provides a scientific and quantitative basis for determining the priority of the conservation of masonry components in the Hailongtun Fortress Site. This method is also a reference for carrying out the disease assessment and conservation of other types of cultural relics.

Evaluation and Improvement of Construction Safety for Prefabricated Buildings Under the Concept of Resilience

In the construction of prefabricated buildings, safety issues occur frequently, posing challenges to project progress and personnel safety. As a new trend in the construction industry, the complexity of the environment in prefabricated construction demands an update to traditional safety management concepts. This study introduces the concept of resilience to analyze safety issues in prefabricated construction and develops a WSR-4Rs framework for a systematic evaluation of construction safety. The study first combines the WSR (Wuli-Shili-Renli) systematic methodology with the 4R resilience theory to construct an evaluation index system for construction safety. Then, it uses the Analytic Hierarchy Process (AHP) and the entropy weight method to determine the combined weights of each index, establishing a balanced and objective weighting scheme. A fuzzy comprehensive evaluation model is then applied to assess actual project cases. Finally, an obstacle degree model is introduced to identify key indicator factors that significantly impact construction safety, and specific improvement measures are proposed based on these findings. The aim is to provide practical references and guidance for enhancing the safety management level in prefabricated construction.