Fuzzy Comprehensive Evaluation Model Research Articles

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.

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.

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.

Fuzzy Comprehensive Evaluation based NLOS Identification for UWB Indoor Positioning

Abstract. Ultra-wideband (UWB) positioning technology stands out from many indoor positioning technologies with its advantages of high precision. However, non-line-of-sight (NLOS) propagate leads to heavy range error and reduces position accuracy, this paper proposes a NLOS identification method based on channel impulse response (CIR), which includes three stages. Firstly, CIR based feature selection is carried out, which includes correlation analysis of calculated features. Secondly, fuzzy comprehensive evaluation model is introduced to NLOS identification. Finally, time of arrival (TOA) based location estimation is realized after NLOS ranging error mitigation. Simulation results show that the average identification rate of NLOS can exceed 86%, and the average positioning error can be reduced by about 0.5m.

Dual Method for Comprehensive Evaluation of Sustainable Water Resources’ Utilization Capacity in Huangshui River in Yellow River Basin, China

The evaluation of sustainable water resources’ utilization capacity in the Huangshui Basin is essential for effective management and development in the water-scarce regions of northwest China. This research provides valuable insights into the basin’s potential capacity for sustainable water resource use by developing a comprehensive evaluation index that addresses the following three critical aspects: climate factors, water resource systems, and socio-economic conditions. The evaluation is conducted using a dual method, as follows: the fuzzy comprehensive evaluation model and the ELECTRE III evaluation method. The results indicate that the Huangshui Basin’s water resources, as a whole, exhibit a medium sustainable utilization capacity. Climatic factors and socio-economic characteristics are the main factors affecting the sustainable utilization of water resources in the Huangshui Basin. Remarkably, both methods yield consistent results, indicating that the overall sustainable utilization capacity of the Huangshui Basin’s water resources is medium. Climatic factors and socio-economic characteristics are identified as the primary aspects influencing the sustainable utilization of water resources in the basin. Based on these findings, recommendations such as enhancing the introduction of external water resources, improving water resources’ management, and implementing comprehensive remediation efforts can help to elevate the level of sustainable water use. This research not only contributes to a deeper understanding of the basin’s water resources’ dynamics, but also serves as an important reference for informed decision making regarding sustainable utilization in the Huangshui Basin.

Multi-Objective Route Planning Model for Ocean-Going Ships Based on Bidirectional A-Star Algorithm Considering Meteorological Risk and IMO Guidelines

In this study, a new route planning model is proposed to help ocean-going ships avoid dangerous weather conditions and ensure safe ship navigation. First, we integrate ocean-going ship vulnerability into the study of the influence of meteorological and oceanic factors on navigational risk. A multi-layer fuzzy comprehensive evaluation model for weather risk assessment is established. A multi-objective nonlinear route planning model is then constructed by comprehensively considering the challenges of fuel consumption, risk, and time during ship navigation. The International Maritime Organization (IMO) guidelines are highlighted as constraints in the calculations, and wind, wave, and calm water resistance to ships in the latest ITTC method is added to the fuel consumption and sailing time in the objective function. Finally, considering the large amount of data required for ocean voyages, the bidirectional A* algorithm is applied to solve the model and reduce the planning time. Furthermore, our model is applied to the case of an accident reported in the Singapore Maritime Investigation Report, and the results show that the model-planned route is very close to the original planned route using the Towing Manual, with an average fit of 98.22%, and the overall meteorological risk of the model-planned route is 11.19% smaller than the original route; our model can therefore be used to plan a safer route for the vessel. In addition, the importance of risk assessments and the IMO guidelines as well as the efficiency of the bidirectional A* algorithm were analyzed and discussed. The results show that the model effectively lowers the meteorological risk, is more efficient than the traditional route planning algorithm, and is 86.82% faster than the Dijkstra algorithm and 49.16% faster than the A* algorithm.

Comfort evaluation of carrier-based aircraft missile handling operation based on fuzzy analytic hierarchy process

The analysis and evaluation of missile handling operation are crucial for ensuring safety and reliability during these processes. This paper proposes a novel assessment method for missile handling motions based on the Fuzzy Analytic Hierarchy Process (FAHP). The methodology comprises several stages: Initially, an analysis of missile handling motions is conducted. Subsequently, joint evaluation indicators influencing operational comfort are selected. Following this, membership functions and a comprehensive evaluation matrix are constructed. Finally, a fuzzy comprehensive evaluation model for the comfort level of carrier-based aircraft ammunition handling operations is established. A typical case study of carrier-based aircraft missile handling operation is presented to illustrate the fuzzy comprehensive evaluation process. The evaluation results are then compared with those obtained from the Rapid Upper Limb Assessment (RULA) and Ovako Working Posture Analysis System (OWAS) models. Comparative analysis indicates that the results derived from the fuzzy comprehensive evaluation model demonstrate high reliability.

A training-free non-intrusive air conditioning load monitoring method based on fuzzy comprehensive evaluation

Air conditioner (AC) is a grid friendly load, monitoring its operating status plays a key role in evaluating user side potential for participation in demand response. With continuous innovations in AC technology, the AC operation characteristics have shown increasing complexity, which poses significant challenges for non-intrusive AC load monitoring. Furthermore, obtaining labeled training data for target scenarios is often challenging, which hinders deployment of many Non-Intrusive Load Monitoring (NILM) methods in practice. In this regard, this article proposes a training-free non-intrusive AC load monitoring method based on fuzzy comprehensive evaluation (FCE), which is very easy to deploy and has good robustness. Firstly, considering various influence factors, a FCE model is constructed based on common knowledge about AC. This model simulates the manual labeling process to locate AC operation periods. Secondly, an AC power estimation method based on weighted filtering is established, in which weighted filter is used to eliminate the non-AC load components that may overlap during AC operation periods. Specifically, an optimization model is constructed to make the cumulative power of the AC events in its working cycle approach zero, with the filter weight vector as the objective variable, in which a heuristic greedy algorithm is used to find the optimal filter weight vector. When multiple feasible solutions with similar objective function values are derived in the solving process, the probability of load events appearing in AC and non-AC operation periods are compared. The final solution is selected, taking into account the likelihood of each feasible solution corresponding to a load event sequence belonging to AC load. The testing results on the PecanStreet dataset and multiple real-world measured datasets prove the effectiveness of the proposed method in monitoring complex ACs with poor waveform consistency.

High-density sampling of soil heavy metals in the upper Bailang River basin: contamination characteristics, sources, and source-oriented health risk assessment.

Heavy metals (HMs) seriously harm soil environment and threaten crop quality and human health. The aim of the study was to investigate the characteristics, quantify the sources and assess the risks of HMs in soil of upper Bailang River Basin (UBRB). The results indicated that the soils in UBRB were at a non-polluted level and posed a low ecological risk to the environment as a whole. The main pollutants were Ni and Cr obtained by indices Pi and Igeo. Based on the consideration of toxicity, the fuzzy comprehensive evaluation model and Ei index revealed that Hg and Cd were dominating pollutants and ecological risk factors of soil in UBRB. The positive matrix factorization model ascertained five potential sources of soil HMs, namely, plastic processing, energy activities, parent material, transportation and agriculture mixed source and industrial manufacturing, with contribution rates of 17%, 7%, 15%, 29% and 32%, respectively. Natural source primarily determined the non-carcinogenic risk for all populations, accounting for about 43% of the total risk. Industrial manufacturing mainly determined the carcinogenic risk, accounting for about 45%. For adults, the risk was acceptable for most of the sample points. For children, potential non-carcinogenic risks were present in 13.19% of the sample sites, which were mainly located in the west, and unacceptable carcinogenic risks were present in 57.21% of the sample sites, which were mainly concentrated in the western and central parts.

Suitability Evaluation of Urban Underground Space Development: A Case Study of Qingdao City

Urban underground space, as an underutilized land resource, holds tremendous potential and value. Efficient and rational development and utilization of this resource are key to addressing current urban challenges. This study takes the main urban area of Qingdao City as an example and establishes a comprehensive evaluation system for the suitability of urban underground space development at different depth levels through the integration of geological, hydrological, and urban planning factors. By utilizing the Analytic Hierarchy Process to assign weights to evaluation criteria within the system, both a multi-objective linear weighting function model and a fuzzy comprehensive evaluation model are employed to assess the suitability of underground space development. The results delineate the distribution of underground space development suitability within the study area. Comparative analysis of the two models reveals that the fuzzy comprehensive evaluation model offers a more detailed and comprehensive reflection of the complexity and diversity of underground space development, providing forward-looking and insightful evaluation results for urban planning and development. The evaluation indicates that certain streets within the main urban area of Qingdao exhibit excellent prospects for underground space development.

The Power of Influencers: How Does Influencer Marketing Shape Consumers’ Purchase Intentions?

In the current digital wave, social media is not only a hub for information exchange but also a shaper of new business marketing models, as is especially evident in the trend towards light and healthy eating. The influence of the influencer economy on consumer purchasing decisions is increasingly pronounced. This paper systematically investigates the impact of influencer marketing on consumer purchase intentions in social media utilizing the Consumer Attitude Theory. Through a sample survey of 654 consumers and empirical analysis using the fuzzy comprehensive evaluation model, the results show that the influencers’ credibility and professionalism and consumers’ satisfaction with live-streaming sales by influencers have a significant positive impact on enhancing consumers’ purchase intentions. To enhance consumers’ purchase intentions, this study suggests that influencers should transparently disclose their collaborations with brands, showcase the positive experiences of other users, and use relevant research and data to support their product recommendations in order to enhance their credibility. Simultaneously, influencers need to strengthen product knowledge, improve professional image and reputation, and meet consumer needs through personalized recommendations and carefully designed live-streaming content to promote brand-value enhancement.

Research on the Composting Technology of Cattle and Sheep Manure Based on Intelligent and Efficient Composting Equipment and the Evaluation Standard of Decomposition Degree

The Inner Mongolia Autonomous Region is a crucial area in China with a significant advantage in animal husbandry, particularly in cattle and sheep farming. However, the disposal of the large quantities of manure produced during farming has severely impacted the industry’s healthy development. Proper treatment of the manure can convert it into organic fertilizer beneficial to farmland; otherwise, it will cause substantial environmental pollution. This study focuses on existing composting equipment and addresses the issues of cattle and sheep manure mixture ratios and compost maturity evaluation. Through experiments on the mixture of cattle and sheep manure, the optimal ratio for converting cattle and sheep manure into organic fertilizer was determined. Additionally, a fuzzy mathematical evaluation model was employed, along with experimental data, to establish a comprehensive evaluation system for aerobic compost maturity based on multiple indicators, revealing the variation patterns of maturity levels under different mixture ratios. The test results revealed that the composting equipment effectively controls the composting process, shortens the composting cycle, ensures the complete decomposition of organic matter, and meets national standards for livestock and poultry manure treatment. Regarding temperature and humidity, oxygen concentration, seed germination rate, pH value, electrical conductivity (EC), nitrogen, phosphorus, potassium content, and carbon-to-nitrogen ratio, the mixed compost of cattle and sheep manure in various ratios met the relevant standards for agricultural application. Various ratios of organic fertilizers containing cattle and sheep manure significantly promoted the growth of maize, wheat, and mung bean crops. Specifically, the compost decomposition cycle was shortest when sheep and cattle dung were mixed at a ratio of 2:1, while it was longest for all cattle dung. Finally, a fuzzy mathematical comprehensive evaluation model was established by selecting four indicators: water content, carbon-to-nitrogen ratio, apparent score, and germination index. The study demonstrates that the equipment and method offer significant advantages in efficiently treating cattle and sheep manure and producing organic fertilizer, thereby providing strong support for the sustainable development of animal husbandry.

Research on the Production Capacity Evaluation of Prefabricated Component Manufacturing Enterprises

Due to the industrialization of the construction sector, enterprises that manufacture prefabricated components are developing rapidly. Because the production capacity of each enterprise varies immensely, the upstream enterprises are unable to match the component manufacturing enterprises that are suitable for the supply target. With respect to the product capacity, scientific and accurate evaluations are crucial. The authors preliminarily determined factors that impact the production capacity of components and considered a literature review and the inspection results of component manufacturing enterprises. By performing a thorough investigation and analysis, they constructed the index system for evaluating the production capacity of enterprises that manufacture prefabricated components, and each index was interpreted. To determine the weight of the evaluation index, an analytic hierarchy process was utilized; furthermore, the characteristics of each grade were described, and a fuzzy comprehensive evaluation model was built. Moreover, to empirically analyze the built model, the authors selected a construction company and analyzed 127 questionnaires filled in by employees at all the organizational levels related to PCT production and to 34 evaluation results of experts from standard quota research institutions in various provinces. The results of the two methods revealed the following: This enterprise level is the “Reinforcement level” (level 3). The evaluation results are consistent with the empirical results of the model established herein, which verifies its feasibility.

Study on Supply Shain Financing Scheme of A Vietnamese Coffee Company in China

This paper takes G7 Coffee, a Vietnamese coffee company, as an example to design a supply chain financing scheme suitable for the company. First of all, on the basis of explaining the concept of supply chain, supply chain financing and other related concepts, supply chain management theory, supply chain financing model, fuzzy comprehensive evaluation model and other theoretical foundations, based on the financing situation of a Vietnamese coffee company G7 coffee in China, combined with the financing problems of the company and the company's capital needs, The feasibility of supply chain financing of G7 Coffee in China for a Vietnamese coffee company is proposed. Secondly, this paper introduces the evaluation method of supply chain financing scheme of G7 Coffee in China of a Vietnamese coffee company. Finally, on the basis of clear objectives and principles of financing scheme design, an evaluation system of supply chain financing mode of a Vietnamese coffee company based on AHP is constructed. The applicability of accounts receivable supply chain financing, inventory supply chain financing and prepayment supply chain financing adopted by the company is further analyzed by fuzzy comprehensive evaluation method. The fuzzy comprehensive evaluation results show that The accounts receivable financing model is the best financing model for the supply chain financing of G7 Coffee in China of a Vietnamese coffee company. In order to ensure the smooth implementation of the supply chain financing plan of a Vietnamese coffee company G7 Coffee in China, this paper proposes to strengthen the guarantee from three aspects: financial system, credit management and risk control.

Optimizing organic fertilization towards sustainable vegetable production evaluated by long-term field measurement and multi-level fuzzy comprehensive model

Precision and efficient management of organic substitution fertilization is crucial in balancing soil health, environmental risks, and economic benefits for intensive crop cultivation. However, effectively determining the optimal organic substitution ratio in vegetable production remains uncertain and still relatively unexplored. We conducted a five-year vegetable field experiment and established four nitrogen-equivalent fertilization treatments: mineral fertilizer alone, and organic fertilizer substituting a quarter, half, and entirety of the mineral nitrogen. Employing a specialized multi-level fuzzy comprehensive evaluation model, our study assessed impacts of different organic substitution ratios on soil qualities, microbial diversity, vegetable yield and quality, environmental risks, and economic benefits in sustainable vegetable production of eastern China. Our results showed that the 50% organic substitution was optimal, significantly improving soil qualities and microbial characteristics, particularly in the topsoil layer. Compared to the control, this approach significantly reduced methane by 6.6–48.3%, nitrous oxide by 49.5–79.1%, and nitric oxide by 36.5–50.0%, while enhancing vegetable yield by 16.0–28.3% and its five-year average stability as well as quality as evidenced by increased protein, soluble sugar, and vitamin C contents. Economic analysis revealed that while it maximized environmental benefits, complete organic substitution did not consistently yield positive economic returns. In contrast, a 50% substitution ratio was identified as the most economically viable, representing a sustainable compromise that balances environmental health with economic feasibility. Further modeling analysis indicated an optimal comprehensive range between 42.9% and 64.5% for achieving the best balance of multiple objectives in vegetable fields. The study underscores the intricate organic substitution effects on intensive vegetable production, highlighting the necessity for tailored organic substitution strategies that integrate environmental sustainability with agricultural productivity and economic practicality.

Shortest Hamiltonian circuit algorithm for complex environments

Simply taking into account the static path length is insufficient to compute the shortest Hamiltonian circuit in complicated situations. To incorporate the influence of many factors on the shortest Hamiltonian circuit, this paper introduces a multi-objective fuzzy comprehensive evaluation model and quantitatively assesses the fuzzy factors. To better correctly reflect each influencing factor's importance in the problem-solving process, this paper also builds a hierarchical model to decide the weights assigned to each one. Finally, this paper adopts the state compression dynamic programming algorithm to solve the dynamic shortest Hamiltonian loop. In this study, an example analysis is also performed to confirm the algorithm's efficacy. Compared with the traditional algorithm, the algorithm designed in this paper comprehensively considers the influence of several factors when calculating the shortest Hamiltonian loop, and can more comprehensively evaluate the advantages and disadvantages of the path.

Research on training evaluation of new engineering talents in China local colleges under the background of regional economy

Under the regional economic background, local colleges have a crucial role in evaluating and researching the training of new engineering talents. With the continuous development of technology and the improvement of economic strength, training new engineering talents has become an important mission for local higher education institutions. This study aims to explore the evaluation methods and strategies for training new engineering talents in local colleges within the regional economic context. It proposes an evaluation system that selects and assesses indicators from five aspects: basic conditions, teaching process, practical proficiency, cultivation level of innovation ability, and cultivation effect. The results were obtained through a combination of the analytic hierarchy process and fuzzy comprehensive evaluation model and take two majors of A college as an example to evaluate and analyze the training effect of new engineering talents. Furthermore, this article presents valuable recommendations and countermeasures to enhance the training of new engineering talents in local colleges.

Quality evaluation of physical education in colleges and universities based on fuzzy logic

This study aims to evaluate the quality of physical education in colleges and universities by using the evaluation method based on fuzzy logic. First, summarize the basic concept of fuzzy logic and its application in the evaluation process. Then, a physical education quality evaluation index system covering teaching quality and students’ physical quality, teachers’ team construction, sports facilities and management is constructed. Then, the evaluation object and evaluation level are determined, and the specific evaluation results and ranking are calculated by fuzzy comprehensive evaluation model. In the empirical analysis, use the simulation data for model application and result analysis, and further find the problems existing in college physical education. Finally, in view of these problems, a series of improvement and optimization suggestions are put forward. This study shows that the evaluation method of physical education quality based on fuzzy logic can effectively reflect the diversity and complexity of education quality, and provide a practical evaluation tool for colleges and universities. At the same time, this study also provides a reference for other universities to help them better understand their own problems, so that they can take effective measures to improve. In addition, this method can be applied to other fields of education quality evaluation in the future, so as to provide more useful information for education reform and development.

A Comprehensive Evaluation of Shale Oil Reservoir Quality

To enhance the accuracy of the comprehensive evaluation of reservoir quality in shale oil fractured horizontal wells, the Pearson correlation analysis method was employed to study the correlations between geological parameters and their relationship with production. Through principal component analysis, the original factors were linearly combined into principal components with clear and specific physical meanings, aiming to eliminate correlations among factors. Furthermore, Gaussian membership functions were applied to delineate fuzzy levels, and the entropy weight method was used to determine the weights of principal components, establishing a fuzzy comprehensive evaluation model for reservoir quality. Without using principal component analysis, the correlation coefficient between production and evaluation results for the 40 wells in the Cangdong shale oil field was only 0.7609. However, after applying principal component analysis, the correlation coefficient increased to 0.9132. Field application demonstrated that the average prediction accuracy for the cumulative oil production per kilometer of fractured length over 12 months for the 10 applied wells was 91.8%. The proposed comprehensive evaluation method for reservoir quality can guide the assessment of reservoir quality in shale oil horizontal wells.

Ranking of components for reliability estimation of CBSS: an application of entropy weight fuzzy comprehensive evaluation model

Ranking of components for reliability estimation of CBSS: an application of entropy weight fuzzy comprehensive evaluation model