Comprehensive Evaluation Method Research Articles

Determination of mine fault activation degree and the division of tectonic stress hazard zones

This article conducts a comprehensive study on the activation characteristics of faults in the mine and analyzes the distribution patterns of the original rock stress field. Through quantitative research and analysis, we determine the partitioning characteristics of tectonic stress in the mine field under the dual effects of fault activation and original rock stress. The study also reveals the significant impact of different fault activation characteristics and different tectonic stress partitions on the stability of roadway surrounding rock. Using the Mohr–Coulomb strength criterion as a foundation, we investigate the mechanisms of fault activation and establish a mathematical model for fuzzy comprehensive evaluation. This model enables us to determine the strength level of fault activation in coal seam 9 of the Limin coal mine and construct a geological structure model. It has realized the transformation of fault activation degree from qualitative evaluation to quantitative evaluation. The stress state analysis software is used to draw the division of tectonic stress dangerous areas under the synergistic effect of fault activation and original rock stress. We then analyze the impact on the stability of roadway surrounding rock in these different hazardous areas. Utilizing the fuzzy comprehensive evaluation method, we take into account the impact of faults on the distribution characteristics of stress fields and the stability of roadway surrounding rock. This approach enables us to more accurately and comprehensively determine the hazardous areas of tectonic stress in the mine field under the dual effects of faults and original rock stress.

Life cycle assessment of sewage sludge treatment and disposal technologies based on carbon emissions and environmental impacts

ABSTRACT This study aimed to create a comprehensive evaluation method for sewage sludge (SS) treatment and disposal technologies, considering carbon emission and environmental impacts. Life cycle assessment (LCA) were conducted on six SS treatment and disposal technologies in China. The assessments used the IPCC emission factor approach to calculate carbon emissions and the CML2001 method to determine environmental impact factors. Additionally, a colour-coded method was implemented to quantify the evaluation results. The study found that S1 (anaerobic digestion + land application) had the lowest carbon emissions and environmental impact, making it the optimal technology. The S1 scenario had carbon emissions of 669 kg CO2(t DS)−1 and environmental impacts of 5.20E-10. A sensitivity analysis was conducted to show the impacts of each unit in the six technologies on total carbon emissions and environmental impacts. The results showed that landfilling has a high sensitivity to carbon emissions and environmental impacts. Therefore, controlling greenhouse gases and toxic substances in sludge landfills is crucial for reducing carbon emissions and environmental pollution.

Optimizing Healthcare Business Processes with Process Mining Software: A Comparative Analysis

This study focuses on the application of process mining in the healthcare sector. Despite its potential to enhance efficiency, reduce costs, and improve patient satisfaction, the selection of process-mining software poses significant challenges due to the diverse nature of healthcare processes and the lack of comprehensive evaluation methods. To bridge this gap, this study employed a hybrid Multi-Criteria Decision-Making (MCDM) approach, integrating the Neural Network-Augmented Analytical Hierarchy Process (NNA-AHP) and Grey Relational Analysis—a technique for Order Preference by Similarity to Ideal Solution (GRA-TOPSIS). The study evaluated process mining software on functionalities, ease of use, cost, technical support, scalability, and security with their respective sub-criteria. The principal results indicate that Disco is the top-performing alternative, followed by Celonis and ProM. Sensitivity analysis was conducted to understand the influence of variations in criteria weights on evaluating alternatives. In the NNA-AHP, Celonis consistently scored the highest. The GRA-TOPSIS method provided performance scores, indicating that higher scores yield better performance. The new hybrid method consolidates evaluations from all methods and offers the most comprehensive and dependable alternative assessment. Disco and its alternatives, Celonis and ProM, are recommended for optimizing healthcare processes. Further research is needed to investigate the integration of NNA-AHP and GRA-TOPSIS in healthcare management, especially in areas beyond business process analysis. This study provides valuable insights for professionals and researchers in the field and contributes to understanding the effectiveness of process mining.

A comprehensive evaluation method for dust pollution: Digital image processing and deep learning approach

Dust pollution poses a grave threat to both the environment and human health, especially in mining operations. To combat this issue, a novel evaluation method is proposed, integrating grayscale average (GA) analysis and deep learning (DL) in image classification. By utilizing a self-designed dust diffusion simulation system, 300 sample images were generated for analysis. The GA method establishes a correlation between grayscale average and dust mass, while incorporating fractal dimension (FD) enhances classification criteria. Both GA and DL methods were trained and compared, yielding promising results with a testing accuracy of 92.2 % and high precision, recall, and F1-score values. This approach not only demonstrates efficacy in classifying dust pollution but also presents a versatile solution applicable beyond mining to diverse dust-contaminated work environments. By combining image processing and deep learning, it offers an automated and reliable system for environmental monitoring, thereby enhancing safety standards and health outcomes in affected industries. Ultimately, this innovative method signifies a significant advancement towards mitigating dust pollution and ensuring sustainable industrial practices.

Analytic Hierarchy Process-Fuzzy Comprehensive Evaluation Method-based Depletion Assessment Study of Xinshan Iron Ore Mine

Taking the Xinshan iron ore mine as an example, this paper, based on collecting and analyzing the actual production data and similar simulation test data of this iron ore mine, analyses various factors affecting ore depletion by bottomless column segmental chipping method by using hierarchical analysis method (AHP) and fuzzy comprehensive evaluation method (FCE), and establishes an evaluation system for comprehensively assessing the depletion of the ores. The results show that structural parameters, blasting parameters, loading parameters, and geological conditions are the main factors affecting ore depletion. The structural parameters are the most important factors, accounting for 35%. With the increase of the released amount, the released grade gradually decreases, the depletion rate gradually increases, and the comprehensive evaluation value gradually decreases. The released body is an approximate ellipsoidal block with a wide upper and narrower lower part. The end wall plays an obstructive role in the flow of the bulk body, which makes the end of the released grade higher and the middle of the released body higher. At the same time, due to the influence of blasting and shovel loading, the particles in the release body show some sorting phenomena. This paper provides a scientific basis and reference for predicting and controlling ore depletion in the bottomless column segmental chipping method.

Water quality evaluation based on water quality index and multiple linear regression: A research on Hanyuan Lake in southern Sichuan Province, China.

This study aims to understand the changes in the water quality of Hanyuan Lake and to show these changes over time. In this study, monthly sampling was conducted at three sampling sites in Hanyuan Lake, and water samples were measured for water quality indicators in the laboratory according to the methods specified in the Environmental Quality Standards for Surface Water (GB3838-2002). Based on the monitoring data from January to December 2019, the WQI comprehensive evaluation method was used to conduct multiple linear stepwise regression analysis, extract key indicators, and establish the WQImin model. The results show that according to the WQI comprehensive evaluation method, the WQI values of Hanyuan Lake are all above 90, and the grade is excellent. The overall water quality of Hanyuan Lake is excellent, and most of the water quality indexes reach the Class I standard in the Environmental Quality Standards for Surface Water (GB3838-2002). WQImin1 (R2 = 0.86, p < 0.001, PE = 4.28) as the best WQImin model. In this study, a model with fewer parameters was established by multiple linear regression method, which is conducive to better monitoring of water quality at monitoring stations while saving costs. PRACTITIONER POINTS: According to the WQI comprehensive evaluation method, the WQI values of Hanyuan Lake are all above 90, the rating is excellent. From January 2019 to September 2020, the monthly change trend of each section is roughly the same, showing a trend of first decreasing, then rising, then decreasing, and finally rising and flattening. The WQImin model was developed to completely describe the change in the water body.

Research on safety condition assessment methodology for single tower steel box girder suspension bridges over the sea based on improved AHP-fuzzy comprehensive evaluation

In order to propose a reliable method for assessing the safety condition for single-tower steel box girder Suspension bridges over the sea, a condition monitoring system is established by installing sensors on the bridge structure. The system is capable of gathering monitoring data that influence the safety status of the bridge. These include cable tension, load on the main tower and pylon, bearing displacement, wind direction, wind speed, and ambient temperature and humidity. Furthermore, an improved Analytic Hierarchy Process (AHP) algorithm is developed by integrating a hybrid triangular fuzzy number logic structure. This improvement, coupled with comprehensive fuzzy evaluation methods, improves the consistency, weight determination, and security evaluation capabilities of the AHP algorithm. Finally, taking the No.2 Channel Bridge as an example and based on the data collected by the health monitoring system, the application of the safety assessment method proposed in this paper provides favorable results in evaluating the overall safety status of the bridge in practical engineering applications. This provides a basis for management decisions by bridge maintenance departments. This project confirms that the research results can provide a reliable method for assessing the security status of relevant areas.

Performance Evaluation of School Enterprise Collaborative Innovation and Practice of Innovation and Entrepreneurship Education Based on the Improved AHP Fuzzy Comprehensive Evaluation Method

Under the influence of the COVID-19, great changes have taken place in China’s economic structure and market subjects and college students are facing difficulties in employment. By carrying out collaborative innovation between schools and enterprises, cultivating high-quality talents to meet social needs has become an important way to solve difficulties. Based on the input-process-output principle, a performance evaluation index system for collaborative innovation is constructed, which includes 3 primary indicators and 22 secondary indicators. The weights of each indicator are determined using improved AHP. A mathematical model for evaluating the performance of school enterprise collaborative innovation is established using the fuzzy comprehensive evaluation method. The evaluation value of the innovation and entrepreneurship education case project is 0.82, indicating that the overall operation is in good condition. The cooperation between schools and enterprises has created a favorable atmosphere and accumulated rich experience for carrying out innovation and entrepreneurship education. Good results have been achieved in talent cultivation and scientific and technological output, but there are also problems such as low conversion rates of scientific and technological achievements. Based on the evaluation results, the article proposes suggestions to improve the performance of collaborative innovation between schools and enterprises. The research results provide theoretical reference for the performance evaluation of school enterprise collaborative innovation and the practice of innovation and entrepreneurship education.

Research on Saihanba Nature Reserve Based on Comprehensive Evaluation Method and Cluster Analysis

In this paper, we analyze the environmental impact of Saihanba Nature Reserve by constructing a comprehensive environmental assessment model. Specifically, we use the entropy weight method to determine the weight of each secondary index and quantitatively study the environmental changes before and after the construction of Saihanba. In addition, we established a mathematical model to evaluate the influence of Saihanba's ability to resist sand and dust storms and quantitatively evaluated the effect of Saihanba's ability to resist sand and dust storms. Finally, we investigated the scale of the constructed ecoregions using a clustering algorithm.

Evaluation and control model for resilience of water resource building system based on fuzzy comprehensive evaluation method and its application

Abstract The conflict between the supply and consumption of water resources (WR) is a growing concern, and water scarcity has become a major obstacle to the sustainable development of Chinese cities. To address this issue, the resilience assessment regulation model has proven to be an effective tool for decision makers. This model helps them determine how to improve the resilience of WR building systems and mitigate potential risks and threats. The aim of this article is to explore the evaluation and regulation of the resilience of WR building systems, with the goal of alleviating the WR crisis and promoting sustainable development. Through the construction of an evaluation index system, determination of index weights, design of evaluation models, and application of case studies, the fuzzy comprehensive evaluation method was employed to assess the resilience of WR systems. Additionally, an evaluation regulation model was established, along with the proposed regulation method. The evaluation index system consists of four dimensions: flexibility, adaptability, resilience, and fault tolerance.

Study on the Selection of Countries for Wildlife Trade Protection Based on Comprehensive Evaluation Methods

Study on the Selection of Countries for Wildlife Trade Protection Based on Comprehensive Evaluation Methods

A Method for Determining Target Areas of Hot Dry Rock Resources: A Case Study in Continental China

Geothermal resources have been recognized as important sources of clean renewable energy. The exploration, development, and utilization of geothermal resources, especially hot dry rock (HDR) resources, are highly important for achieving peak carbon and carbon neutrality. However, there is no comprehensive evaluation method for determining HDR target areas, and the evaluation scale and application disciplines are relatively simplistic. In this paper, we sought to optimize the identification of HDR target areas through a multiscale and multidisciplinary method and formed a set of generalized and demonstrative processes to guide the exploration of HDR resources. Through practical application to the Gonghe Basin and the Zhangzhou Basin, it was found that the comprehensive geothermal conditions of the Gonghe Basin are superior to those of the Zhangzhou Basin, and the geothermal reservoir depth, geothermal reservoir temperature, geothermal gradient, and heat flow are the four most important factors affecting hot dry rock geothermal resources. Using this method, the prioritization of target areas changes from a qualitative study to a quantitative and semiquantitative study, increasing the specificity and reliability of the decision-making process.

Functional-Combination-Based Comprehensive Benefit Evaluation of Energy Storage Projects under Source-Grid-Load Scenarios via Super-Efficiency DEA

As an important support for power systems with high penetration of sustainable energy, the energy storage system (ESS) has changed the traditional model of simultaneous implementation of electricity production and consumption. Its installed capacity under the source-grid-load scenario is rising year by year, contributing to sustainable development, but it faces the problems of insufficient utilization and benefits. This study analyzes the functional combination of ESS under source-grid-load scenarios. A comprehensive benefit evaluation method of energy storage projects (ESPs), based on a fuzzy decision-making trial and evaluation laboratory (DEMATEL) and super-efficiency data envelopment analysis (DEA), is proposed. Firstly, the functional requirements of energy storage in source-grid-load scenarios are explored, and the characteristics of various functions are analyzed to form eight functional combination schemes. Secondly, index modeling is carried out from three aspects—the whole life cycle cost, functional combination benefits, and social and environmental benefits—and a comprehensive benefit evaluation index system of ESP is proposed. Then, the intuitionistic trapezoidal fuzzy number (ITFN) is combined with DEMATEL to form an effective analysis method for the input–output relationship of the indices, and the comprehensive evaluation is realized based on the SE-DEA model. Compared with other methods, this model can ensure the objectivity and stability of the evaluation results in ESP evaluation. Finally, the effectiveness of the proposed evaluation method and the rationality of the functional combination are verified under source-grid-load scenarios. The calculation results show that in the application scenario of source-grid-load, after adopting the functional combination scheme formulated in this article, the comprehensive investment benefits of ESPs have been improved. Moreover, the source side effect is at its best, with an efficiency value of 2.209.

Optimizing the performance of TPCB/SCA composite-modified asphalt using improved response surface methodology

Abstract A composite-modified asphalt was developed by incorporating tire pyrolytic carbon black (TPCB) with a silane coupling agent (SCA) to enhance its ductility and storage stability. The functional binding between asphalt and TPCB was improved by the addition of SCA. The gray correlation comprehensive evaluation method is incorporated into the response surface methodology (RSM), leading to an improved RSM. The improved RSM was employed to optimize the content of the modifier and the preparation process to enhance overall performance. A central composite design-based experiment was conducted to optimize the penetration, softening point, 10°C ductility, Brookfield rotational viscosity, and storage stability indicators of modified asphalt. The response surface of the gray comprehensive evaluation value of the evaluation indicators was calculated using the gray correlation analysis method, and a second-order regression model was established between independent variables such as TPCB, SCA content, and shear time factor and the gray comprehensive evaluation value. This model analyzed the impact of a single variable and variable interaction on the performance of the TPCB/SCA composite-modified asphalt. The optimized model results showed that the preparation parameters that optimize the expected comprehensive performance of the composite-modified asphalt are 9.2% TPCB content, 2.1% SCA content, and a shear time of 56.3 min. Finally, the TPCB/SCA composite-modified asphalt prepared with the improved RSM exhibited the highest gray comprehensive evaluation value and the best overall performance, indicating the feasibility of the optimized preparation parameters with the improved RSM.

An Empirical Study on Offensive and Defensive Ability of College Men's Football Teams Based on TOPSIS-RSR Comprehensive Evaluation Method

This study aimed to explore the characteristics and rationality of ranking offensive and defensive abilities of 32 college football teams and their division into tiers, as well as the application effects in teaching and training experiments. A combination of literature review, questionnaire survey, TOPSIS method, RSR method, and experimental method were primarily employed. The objective was to furnish a more extensive theoretical reference basis for future college football team training. The findings revealed that the TOPSIS-RSR method was capable of assessing each team's outcomes objectively and quantitatively. However, potential errors were identified in the evaluation process stemming from the final match results, necessitating multifaceted considerations between teams and players. Numerous internal and external uncertain factors, such as time, individuals, and coaches, were acknowledged. The application of the TOPSIS-RSR comprehensive evaluation method to football training technology was found to assist college students with specific football skills in enhancing their technical proficiency. It was concluded that for athletes with variable factors such as age, athlete level, and training years at different phases, the rational arrangement of training cycles must be thoroughly considered.

Low–carbon regulation method for greenhouse light environment based on multi–objective optimization

Controlled environment agriculture is uniquely positioned to contribute to the decarbonization of cities due to its low carbon emissions and high energy efficiency in the food supply process. The energy consumed by the horticultural industry to supplemental lighting is enormous, but improvements in the light environment of greenhouse plants are essential. To make light regulation compatible with low carbon and environmentally friendly while improving photosynthetic production, experiments on tomato plant measurements with nested light intensity, spectra, carbon dioxide concentration and temperature were carried out in a solar greenhouse based on an infrared gas analyzer and machine learning. Based on the photosynthetic response to the photosynthetic photon flux density and red–blue ratio under multi–environmental conditions, the photosynthesis prediction model was developed using the least squares support vector regression, and model hyperparameter optimization was achieved by genetic algorithm nested cross–validation. A calculation method of carbon emissions from supplemental lighting was proposed, and the low–carbon light regulation was abstracted into multi–objective optimization for the solution. Based on the comprehensive objective evaluation method, low–carbon targets for light regulation were obtained through decision–making. The results showed that the developed prediction model with root mean square error of 1.069 and determination coefficient of 0.976, which is both accurate and fast, realizes the description and expression of the net photosynthetic rate in response to the environments. The optimal targets contain two–dimensional information of light intensity and spectra, and reduces carbon emissions by a maximum of 14.85% compared to the light saturation objective based on single–objective optimization at 95.49 % of the net photosynthetic rate. The method is energy efficient and suitable for supporting multi–spectral light environment regulation applications and guiding the greenhouse environment management under the demand of carbon reduction.

An examination of the usefulness of a quantitative appraisal method in nursing human resource management in primary hospital operating rooms: An example of integrated collaborative scheduling.

In recent years, China medical and health services have made great development. However, the management of nursing human resources in operating room of primary hospitals still faces a series of challenges. In the nursing work of operating room, high-quality nursing human resource management is important for improving the efficiency of operating room and ensuring the safety of patients. From January 2022 to December 2022, comprehensive collaborative scheduling and quantitative scoring evaluation methods were carried out in our hospital, and relevant data were collected. The flexible scheduling combined quantitative scoring performance appraisal system and the traditional scheduling plus average distribution performance appraisal system were statistically analyzed and compared in terms of annual surgical cases, annual overtime hours, annual back work hours, annual compensatory rest hours, and average daily working hours. This study was based on 30 medical staff (27 females and 3 males) in the operating room of a primary hospital. The annual operation volume increased by 387 cases compared with before, and the attitudes of patients to the service attitude and preoperative waiting time were significantly improved, reaching more than 95%. In addition, in the survey of surgeons, it was found that their satisfaction with preoperative preparation and operation time was significantly higher than that of the traditional scheduling method, and reached more than 95%. In the survey of nursing staff, it was found that the satisfaction with the traditional scheduling method was about 80%, and the satisfaction directly reached 100% after the comprehensive collaborative scheduling system. Based on the above survey, the satisfaction of nurses, doctors and patients with the new comprehensive collaborative scheduling system has improved compared with before. After the implementation of the comprehensive collaborative scheduling system, the annual surgical volume has increased significantly, and the average daily working hours of nursing staff have decreased. Comprehensive collaborative scheduling is an effective method of nursing human resource management in operating room, which can effectively improve the work efficiency of nurses and the satisfaction of patients, doctors and nurses. In practice, this method needs to be continuously explored and refined to adapt to different application scenarios and requirements.

Evaluation of resource and environmental carrying capacity in Xiong’an New Area

From four dimensions of resource, environment, ecology (green ecology) and social economy, correlation analysis method and principal component analysis method of SPSS are used to screen evaluation indexes to design a scientific and reasonable evaluation indexes system of resource and environmental carrying capacity in Xiong’an New Area in line with regional characteristics. Based on fuzzy comprehensive evaluation method, resource and environmental carrying capacity of the New Area are evaluated. The results show that: the resource and environmental carrying capacity of the New Area from 2014 to 2018 are 0.3229, 0.3556, 0.3521, 0.3859 and 0.4445 respectively, with an average annual growth rate of 8.32% and a steady growth trend. Then, some countermeasures to improve resource and environmental carrying capacity of the New Area are presented from three aspects of development and utilization of land resource, development and utilization of water resource and protection and utilization of water environment.

Proposal of a comprehensive risk assessment model for cut slope considering long-term deterioration characteristics based on the concept of disaster immunity

In Japan, the stability of cut slopes alongside expressways has deteriorated over time due to factors such as weathering, rendering them susceptible to significant collapses, especially during heavy rainfall. This study presents an evaluation model to assess the stability of cut slopes, with the aim of capturing their long-term deterioration characteristics using the logistic regression method. Additionally, to explore variations in deterioration patterns among cut slopes in diverse regions with varying geological compositions, a hierarchical Bayesian model is utilized to estimate parameters in the logistic regression model. This methodology enables the creation of a novel stability probability evaluation model for cut slopes that is adaptable to regions with different geological structures. Moreover, to comprehensively evaluate changes in the disaster resistance capabilities of extensively used cut slopes, the post-disaster recovery capabilities in the slope region are assessed through a comprehensive weighted evaluation method (EWM-TOPSIS). Building on this assessment, a novel, simplified, and more generalized resilience evaluation method is proposed. By integrating stability probability and resilience, an evaluation metric named "disaster immunity" is introduced to measure alterations in the disaster risk resistance of extensively utilized cut slopes. A case study is presented to illustrate the application of the evaluation model on selected cut slopes from various regions. This evaluation framework can assist road managers in predicting the disaster risk status of extensively used cut slopes and identifying priority slopes for implementing preventive measures to mitigate potential losses in the event of slope disasters.

Multiscale evaluation of tunnel construction safety risk: a case study of an offshore tunnel construction in Ningbo

Based on the WBS-RBS method, in this study, the risk factors corresponding to the construction risk events of an offshore tunnel foundation pit in Ningbo were identified, and the fuzzy comprehensive evaluation method was used to evaluate the construction safety risk of the project. The system-level risk value was obtained by using the risk event deformation resulting from changes in two factors, namely, “mechanical property of soil” and “stiffness of the envelope structure”, to calculate the new event-level risk value corresponding to the deformation using a finite element numerical model. The findings indicate that the tunnel project has a risk evaluation score of 62.78 and thus falls within the category of high-risk projects. A change in risk factors will alter the likelihood that risk events will occur, which affects the safety risk status of the entire project. When two factors are coupled, a project’s system-level risk can increase dramatically.