Search Results (32)

The complex interdependencies among numerous safety risk factors influencing oil tanker loading/unloading operations constitute a focal point in academic research. To enhance safety management in oil port operations, this study conducts a risk analysis of oil tanker berthing and cargo transfer safety. Initially, safety risk factors are identified based on the Wu-li Shi-li Ren-li (WSR) systems methodology. Subsequently, a hybrid weighting approach integrating the Fuzzy Analytic Hierarchy Process (FAHP), G2 method, and modified CRITIC technique is employed to calculate indicator weights. These weights are then synthesised into a combined weight (GVW) using cooperative game theory and variable weight theory. Further, by integrating grey theory with the cloud model (GCM), a risk assessment is performed using Tianjin Port as a case study. Results indicate that the higher-risk indicators for Tianjin Port include vessel traffic density, safety of berthing/unberthing operations, safety of cargo transfer operations, safety of pipeline transfer operations, psychological resilience, proficiency of pilots and captains, and emergency management capability. The overall comprehensive risk evaluation value for Tianjin Port is 0.403, corresponding to a “Moderate Risk” level. Comparative experiments demonstrate that the results generated by this model align with those obtained through Fuzzy Comprehensive Evaluation Methods. However, the proposed GVW-GCM framework provides a more objective and accurate reflection of safety risks during tanker operations. Based on the computational outcomes, targeted recommendations for risk mitigation are presented. The integrated weighting model—incorporating game theory and variable weight concepts—coupled with the grey cloud methodology, establishes an interpretable and reusable analytical framework for the safety assessment of oil port operations under diverse port conditions. This approach provides critical decision support for constructing comprehensive management systems governing oil tanker loading/unloading operations. Full article

With the increasing diversification of modern home textile design (HTD), the integration of traditional cultural elements has become an important trend. This study investigates the impact of symmetry in traditional patterns on the optimization of home textile product design and examines its role in consumer acceptance. First, the affinity diagram method was employed to collect core affective vocabularies. Based on a selection of home textile products incorporating traditional patterns available in the market, a questionnaire was developed to solicit consumers’ evaluations of these affective descriptors. Principal component analysis (PCA) was conducted to extract key perceptual dimensions, with particular emphasis on the influence of pattern symmetry on consumer perception. Subsequently, the Fuzzy Analytic Hierarchy Process (FAHP) was applied to determine the relative weights of the affective terms. Incorporating expert input, five representative traditional patterns from the Homespun Fabric of Jiangnan (HFoJ) were selected and reinterpreted with a focus on symmetrical design. Through the Quality Function Deployment (QFD) method, the effective vocabularies were mapped to the redesigned patterns, leading to the identification of the scheme that most effectively embodied the symmetrical principle for integration into HTD. Finally, the Grey Relation Analysis (GRA) was used to conduct a comprehensive evaluation of multiple design alternatives. The optimal design was selected and subsequently validated through consumer feedback to assess its market feasibility. This study contributes a symmetric approach to the application of symmetry in traditional pattern design, offering both traditional insights and practical guidance for the modernization and innovative transformation of cultural elements in HTD. Full article

This study introduces the GWO-FNN model, an improvement of the fuzzy neural network (FNN) architecture that aims to balance high performance with improved interpretability in artificial intelligence (AI) systems. The model leverages the Grey Wolf Optimizer (GWO) to fine-tune the consequents of fuzzy rules and uses mutual information (MI) to initialize the weights of the input layer, resulting in greater classification accuracy and model transparency. A distinctive aspect of GWO-FNN is its capacity to transform logical neurons in the hidden layer into comprehensible fuzzy rules, thereby elucidating the reasoning behind its outputs. The model’s performance and interpretability were rigorously evaluated through statistical methods, interpretability benchmarks, and real-world dataset testing. These evaluations demonstrate the model’s strong capability to extract and clearly express intricate patterns within the data. By combining advanced fuzzy rule mechanisms with a comprehensive interpretability framework, GWO-FNN contributes a meaningful advancement to interpretable AI approaches. Full article

This study systematically evaluates ten historical cultural symbols in the brand image design of Xuzhou City based on Grey System Theory and Fuzzy Evaluation Method, revealing their significance and distinctions within city branding. First, Grey System Theory is applied to rank these symbols, establishing their prioritization in the brand design process. Subsequently, Fuzzy Evaluation Method is employed to perform a comprehensive analysis of each symbol across five dimensions: visual appeal, cultural heritage, brand recognizability, public acceptance, and sustainability. The Analytical Hierarchy Process (AHP) is used to set weights for each dimension, ensuring a scientific and reasonable evaluation. Results indicate that Xuzhou’s ancient city wall and the culture of Xiang Yu excel in visual appeal and sustainability, while symbols like Pengzu culture show relatively lower public acceptance. Targeted recommendations are proposed based on these findings. This study provides a quantitative basis for Xuzhou’s city brand design and suggests a greater emphasis on the sustainability and adaptability of cultural symbols in future city branding efforts. Full article

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. Full article

Current design decision-making methods ignore the fuzzy relationship between Kansei images, and the use of constant weights reduces the accuracy of cognitive evaluation results. To solve these problems, this paper proposes a grey decision-making method for product form driven by the fuzzy relationship between Kansei images. First, according to the initial weight of the Kansei images, variable weight theory is used to determine the Kansei image variable weights of the samples, and the variable weight comprehensive evaluation results for each sample are obtained. Then, based on the correlation and angle of the Kansei images, a cobweb diagram is drawn to represent the fuzzy relationship between the Kansei images of each sample. Combined with the cobweb grey target decision-making model (CGTDM) for multiple Kansei images, decision coefficients are calculated. The decision coefficients are compared and ranked to determine the relatively optimal design reference sample. Finally, the constructed model is compared with the CGTDM for multiple Kansei images and TOPSIS. The results show that the difference coefficient of the proposed method is the largest, and it can reflect the decision-making thinking of the designers and improve the discrimination among the decision-making results to a certain extent. Full article

To effectively enhance the adaptability of earthquake rescue robots in dynamic environments and complex tasks, there is an urgent need for a comprehensive evaluation method that encompasses establishing an evaluation index system, testing performance indexes, and conducting performance evaluation. Firstly, four main criterion and twenty-three sub-criterion indexes are established by conducting a comprehensive review of existing assessment measures for rescue robots across diverse domains. These indexes are validated through test modules developed by the National Earthquake Response Support Service to obtain corresponding values for each criterion. Moreover, a method for establishing the index system is proposed based on the fuzzy clustering analysis and grey correlation analysis methods. This method effectively addresses issues related to excessive subjectivity, redundancy, and ambiguous stratification of indexes. Subsequently, the DEMATEL is employed to scrutinize the interrelationships and causal connections among each index within the established index system, leading to the identification of input and output indexes based on the analysis outcomes. Finally, as an empirical example, three earthquake rescue robots are comprehensively evaluated and ranked using the super efficiency DEA model. Alongside analyzing results regarding input redundancy and output deficiency, targeted improvement suggestions are provided for each earthquake rescue robot. Additionally, comparison analysis with the entropy weight method and VIKOR method verifies the effectiveness of our proposed method. Full article

In recent years, the frequent occurrence of public health emergencies has affected people’s daily lives. In response, this paper evaluates the risk of logistics terminal distribution and puts forward the corresponding countermeasures. Firstly, this paper summarizes relevant literature and analyzes the characteristics of public health emergencies and logistics terminal distribution. This paper constructs the risk index system of logistics terminal distribution under public health emergencies for the first time. Secondly, this paper conducts a questionnaire survey on a domestic e-commerce enterprise. In this paper, the intuitionistic fuzzy entropy weight method is applied to the obtained data to determine the weight of risk index. Finally, this paper adopts the grey fuzzy comprehensive evaluation method to evaluate the risk index of logistics terminal distribution under public health emergencies. This paper takes the impact of public health emergencies into account for the risk of logistics terminal distribution for the first time. Some suggestions are provided for preventing the logistics terminal distribution from stagnation and paralysis when public health emergencies occur. This paper supplements the existing research in this field. Full article

(1) Background: At present, physiological stress detection technology is a critical means for precisely evaluating the comprehensive health status of live fish. However, the commonly used biochemical tests are invasive and time-consuming and cannot simultaneously monitor and dynamically evaluate multiple stress levels in fish and accurately classify their health levels. The purpose of this study is to deploy wearable bioelectrical impedance analysis (WBIA) sensors on fish skin to construct a deep learning-based stress dynamic evaluation model for precisely estimating their accurate health status. (2) Methods: The correlation of fish (turbot) muscle nutrients and their stress indicators are calculated using grey relation analysis (GRA) for allocating the weight of the stress factors. Next, WBIA features are sieved using the maximum information coefficient (MIC) in stress trend evaluation modeling, which is closely related to the key stress factors. Afterward, a convolutional neural network (CNN) is utilized to obtain the features of the WBIA signals. Then, the long short-term memory (LSTM) method learns the stress trends with residual rectification using bidirectional gated recurrent units (BiGRUs). Furthermore, the Z-shaped fuzzy function can accurately classify the fish health status by the total evaluated stress values. (3) Results: The proposed CNN-LSTM-BiGRU-based stress evaluation model shows superior accuracy compared to the other machine learning models (CNN-LSTM, CNN-GRU, LSTM, GRU, SVR, and BP) based on the MAPE, MAE, and RMSE. Moreover, the fish health classification under waterless and low-temperature conditions is thoroughly verified. High accuracy is proven by the classification validation criterion (accuracy, F1 score, precision, and recall). (4) Conclusions: the proposed health evaluation technology can precisely monitor and track the health status of live fish and provides an effective technical reference for the field of live fish vital sign detection. Full article

Aiming at comprehensively evaluating the status of a bridge monitoring system, an evaluation framework based on the improved Delphi, analytic Hierarchy process, Grey relations analysis and Fuzzy integrated evaluation (DHGF) is selected. Firstly, the evaluation indexes for the bridge monitoring system are determined by an anonymous group discussion and expert questionnaire using the improved Delphi method. Secondly, a comparison matrix of the evaluation indexes is constructed to determine the comprehensive weight via the analytic hierarchy process. Then, based on the gray relations analysis, the albino weight function is constructed, the evaluation gray class is determined, and the single-factor fuzzy evaluation matrix is obtained. Finally, the final evaluation result was obtained by the fuzzy comprehensive evaluation. The evaluation results of a real bridge monitoring system show that the evaluation level of the monitoring system was level II, and the proposed framework could better reflect the construction and operation status of the monitoring system. Full article

Bridge safety during operating periods is a primary concern worldwide, and the evaluation of bridge risks is a critical aspect of ensuring bridge safety. The most common methods used for bridge risk evaluations include fuzzy comprehensive evaluations, grey system theory, fault tree analysis, the Kent index method, and data envelopment analysis. However, these approaches are highly subjective and have uneven distributions when determining the weights of risk indicators. To improve the accuracy and feasibility of bridge risk evaluations for a given period of operation, we first establish bridge risk indicators and assign subjective weights to each indicator based on an analytic hierarchy process. Additionally, objective weights are assigned to each indicator according to an entropy weighting method. Then, the combined weights of each risk indicator are obtained by applying game theory principles. This enables the construction of a degree of membership matrix comprising these risk indicators, which is established according to an expert grading method and grey fuzzy theory. Finally, the evaluation results vector is calculated, allowing the risk level of a bridge to be assessed according to the principle of the maximum degree of membership. Overall, this study provides a more accurate and objective method for evaluating bridge risk during a given period of operation. Full article

With the rapid development of the economy in China, the scale and quantity of urban underground space development continue to grow rapidly; as such, geological safety problems in urban underground space development and utilization are a research hotspot at present. Therefore, it is important to establish a high-quality evaluation index system and method for assessing the geological safety of urban underground spaces in coastal bedrock. Taking the typical area of Qingdao as an example, this study establishes an effective system for evaluating the geological safety of urban underground space according to the geological background, hydrogeology, engineering geology, and unfavorable geological phenomena in the Hongdao Economic Zone of Qingdao. Then, the method of evaluating the geological safety of urban underground space was studied. Through a comprehensive analysis and comparison of the fuzzy comprehensive evaluation–analytic hierarchy process (FCE-AHP), the grey relation comprehensive evaluation–analytic hierarchy process (GRCE-AHP), the matter-element comprehensive evaluation–analytic hierarchy process (MECE-AHP), and the back-propagation neural network comprehensive evaluation–analytic hierarchy process (BPCE-AHP), it was determined that the back-propagation neural network comprehensive evaluation–analytic hierarchy process (BPCE-AHP) was an ideal method for evaluating the geological safety of underground space in Qingdao’s coastal bedrock area. This method was used to evaluate the geological safety of the study area, and the evaluation results were verified; this further proved the practicability and rationality of the back-propagation neural network comprehensive evaluation–analytic hierarchy process (BPCE-AHP). Full article

To regulate the safety behavior of employees and improve the occupational safety level of enterprises. Based on the perspective of safety culture, this paper designed an index system based on the four dimensions of safety concept, system, behavior, and physical culture, and it explored a new quantitative assessment method of safety culture level by introducing the concept of maturity into the evaluation of safety culture using the grey fuzzy comprehensive evaluation method. Combining the characteristics of enterprise safety culture, safety culture was divided into five levels, including original level, starting level, development level, completion level, and leading level, and the maturity model of enterprise safety culture was established. Finally, taking an enterprise to be evaluated as an example, the evaluation steps and application of evaluation results were introduced. The results showed that the evaluation model of enterprise safety culture maturity constructed in this paper provides systematic measurement indexes and scientific evaluation methods for evaluating the safety culture maturity of enterprises. Full article

In the era of internet connection and IOT, data-driven decision-making has become a new trend of decision-making and shows the characteristics of multi-granularity. Because three-way decision-making considers the uncertainty of decision-making for complex problems and the cost sensitivity of classification, it is becoming an important branch of modern decision-making. In practice, decision-making problems usually have the characteristics of hybrid multi-attributes, which can be expressed in the forms of real numbers, interval numbers, fuzzy numbers, intuitionistic fuzzy numbers and interval-valued intuitionistic fuzzy numbers (IVIFNs). Since other forms can be regarded as special forms of IVIFNs, transforming all forms into IVIFNs can minimize information distortion and effectively set expert weights and attribute weights. We propose a hybrid multi-attribute three-way group decision-making method and give detailed steps. Firstly, we transform all attribute values of each expert into IVIFNs. Secondly, we determine expert weights based on interval-valued intuitionistic fuzzy entropy and cross-entropy and use interval-valued intuitionistic fuzzy weighted average operator to obtain a group comprehensive evaluation matrix. Thirdly, we determine the weights of each attribute based on interval-valued intuitionistic fuzzy entropy and use the VIKOR method improved by grey correlation analysis to determine the conditional probability. Fourthly, based on the risk loss matrix expressed by IVIFNs, we use the optimization method to determine the decision threshold and give the classification rules of the three-way decisions. Finally, an example verifies the feasibility of the hybrid multi-attribute three-way group decision-making method, which provides a systematic and standard solution for this kind of decision-making problem. Full article

Sponge cities provide broad hydrological functions to alleviate urban flooding and other water-related problems in China. Conventional impervious paving cannot meet contemporary sustainable city goals. The permeable paving technology offers primary benefits such as increasing stormwater infiltration, drainage, purification, groundwater recharge, and microclimatic amelioration. Few studies have evaluated the embracive range of benefits and the social functions holistically. This study aimed to develop a comprehensive benefit evaluation system to cover a broad range of indicators. Nineteen indicators were selected based on the literature review, field studies, and research experience. Organized in a three-tiered hierarchical structure, they were divided into environmental, economic, and social benefits. A grey intuitionistic fuzzy comprehensive evaluation model was built by combining intuitionistic fuzzy analysis with a grey comprehensive evaluation. The computational tools could determine the differential weights of indicators and benefit scores. Taking an example of a permeable pavement project in Quanzhou City, the comprehensive benefits were assessed and validated using our evaluation model. The results show that (1) the comprehensive benefits of the project met the economic feasibility criteria with advantages over conventional paving; (2) the environmental benefits were prominently expressed; (3) the social benefits were assessed and confirmed. The results verified the feasibility and applicability of the quantitative-qualitative model. The method could permit the integrated and systematic benefit assessment of permeable paving designs. It also provides guidance and reference to evaluate the performance of permeable pavements and their comprehensive range of benefits. The findings could reference choosing and refining designs, optimizing the benefits, and promoting a science-oriented development of permeable paving. Full article