Hierarchical Evaluation Research Articles

Evaluation of Mangrove Wetlands Protection Patterns in the Guangdong–Hong Kong–Macao Greater Bay Area Using Time-Series Landsat Imageries

The protection of mangroves through nature reserves has been demonstrated to be effective. There were many studies evaluating the mangrove protection effect. However, the evaluation of mangrove growth quality with positive or negative growth trends, as well as restoration potential against disturbance in nature reserves, is still lacking. Thus, this study proposed a hierarchical evaluation framework for mangrove protection in nature reserves, which takes long-term metrics at three levels of loss and gain areas, patch pattern dynamics, and pixel growth trends into account. The continuous change detection and classification (CCDC) was utilized to identify the change condition of mangroves in six nature reserves of the Guangdong–Hong Kong–Macao Greater Bay Area. The Entropy Weight Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was utilized for scores evaluation of protection effort comparison from 2000 to 2020. The study results had the following three main findings. Firstly, the mangrove forest area increased by about 294.66 ha in four reserves and slightly decreased by about 58.86 ha in two. Most reserves showed an improved patches intact pattern and more positive growth trends. Secondly, the establishment of nature reserves and afforestation were the main causes of mangrove area gain. Until 2010, aquaculture, agriculture, and urban development were the biggest threats to mangroves. Finally, the protection of the reserves was successful in the early decades, but the general evaluation scores showed a decline in recent years once we considered the growth trends for quality. The proposed hierarchical evaluation methods provide a new sight to research the impacts of abrupt change and protection resilience status of the gradual restoration of nature reserves.

Materials selection of 3D printed polyamide-based composites at different strain rates: A case study of automobile front bumpers

The selection of 3D printed composite materials considering multiple criteria has become a challenging issue for designers/engineers and can be regarded as a typical decision-making problem. Especially for diverse engineering applications, the different strain rates encountered need to be addressed in the decision-making process. In this study, a systematic hierarchical evaluation model of 3D printed polyamide-based composites with 27 indicators is established considering economic, environmental, social and mechanical aspects. The mechanical responses at four strain rates (8 × 10−4 s−1, 8 × 10−3 s−1, 1700 s−1 and 3510 s−1) are incorporated into the model. A hybrid decision-making approach combining the fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory)-Entropy and fuzzy TODIM (Tomada de Decisão Interativa Multicritério)-VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) methods is proposed to solve the composite material selection problem. An automobile front bumper, as an empirical application, is investigated to demonstrate the proposed model and decision-making approach. The results show that PACF-C, that is the short carbon fibre reinforced polyamide printed with a concentric strategy, is the optimal alternative. This study provides an effective approach for solving the material selection problem of 3D printed composites.

Hierarchical evaluation framework for coupling effect enhancement of renewable energy and thermal power coupling generation system

Renewable energy and thermal power coupling generation system (RETCS) is a special virtual power plant that aggregates renewable energy and thermal power to the main power system through the coupling point. RECTS can coordinate as an integrated system to handle the power fluctuation of renewable energy. Analyzing the interaction of RETCS in resource, economy, and environment comprehensively is the key to improving the coupling effect of the system. This work proposes a coupling coordination degree (CCD) evaluation system to assess and improve the coupling effect of the RETCS. First, CCD evaluation system is established to assess the RETCS using indicators from resource, economy, and environment subsystems in detail. Second, a stochastic RETCS planning model is established to investigate the coordination strategy of the system. Finally, a RETCS case study with different wind power penetration levels and power demand in northeast China is carried out to demonstrate the effectiveness of CCD evaluation system in representing the coupling effect of RETCS and helping to improve the system. Numerical results show that thermal units with deep peak regulation capability can better utilize the ramping and power regulation potential to handle the wind power fluctuation in most cases. An appropriate power source capacities in RETCS can improve the coupling effect of the system under a certain power demand.

Modeling and Quantitative Evaluation Method of Environmental Complexity for Measuring Autonomous Capabilities of Military Unmanned Ground Vehicles

This paper proposes a sampling-based multi-dimensional entropy hierarchical evaluation method to evaluate the environmental complexity for measuring autonomous capabilities of military unmanned ground vehicles. Through establishing the multi-dimensional environment model, the complexity of environmental elements in various dimensions is measured by combining the analytic hierarchy process and the improved gravitational field model. Based on the graph entropy and the environment segmentation sampling strategy, the environmental complexity is comprehensively evaluated from the two perspectives of the objective complexity of the environmental structure and the subjective complexity of environmental characteristics. The evaluation of the actual test environment shows that the environmental complexity evaluation model can effectively reflect the individual complexity differences of environmental elements, and achieve the comprehensive complexity evaluation of the environment including multiple test scenarios, which provides a basis for the test scenario design and measuring autonomous capabilities of military unmanned ground vehicles.

Segmentation of kidney mass using AgDenseU-Net 2.5D model

The Kidney and Kidney Tumor Segmentation Challenge 2021 (KiTS21) released a kidney CT dataset with 300 patients. Unlike KiTS19, KiTS21 provided a cyst category. Therefore, the segmentation of kidneys, tumors, and cysts will be able to assess the complexity and aggressiveness of kidney mass. Deep learning models can save medical resources, but 3D models still have some disadvantages, such as the high cost of computing resources. This paper proposes a scheme that saves computing resources and achieves the segmentation of kidney mass in two steps. First, we preprocess the kidney volume data using the automatic down-sampling method of 3D images, reducing the volume while preserving the feature information. Second, we finely segment kidneys, tumors, and cysts using the AgDenseU-Net (Attention gate DenseU-Net) 2.5D model. KiTS21 proposed using Hierarchical Evaluation Classes (HECs) to compute a metric for the superset: the HEC of kidney considers kidneys, tumors, and cysts as the foreground to compute segmentation performance; the HEC of kidney mass considers both tumor and cyst as the foreground classes; the HEC of tumor considers tumor as the foreground only. For KiTS21, our model achieved a dice score of 0.971 for the kidney, 0.883 for the mass, and 0.815 for the tumor. In addition, we also tested segmentation results without HECs, and our model achieved a dice score of 0.950 for the kidney, 0.878 for the tumor, and 0.746 for the cyst. The results demonstrate that the method proposed in this paper can be used as a reference for kidney tumor segmentation.

Why the ‘Ideal Victim’ Persists: Queering representations of victimhood in human trafficking discourse

The image of a young, victimised woman bound and gagged for implied sexual exploitation persists in the imagination, promotional material, and reports of the anti-trafficking sector. She is presented as the ‘ideal’ victim, and while people who have experienced this undoubtedly exist, many victim accounts deviate from this prescriptive path. Why then does the image of a universal, ideal victim endure? This paper argues that the idealised subject of contemporary trafficking law is not merely a symptom of uncritical representation, but intrinsic to the formation of anti-trafficking law. Often feminised, she becomes a tool for maintaining heteronormative and white nationalism, but one which never existed beyond her confines of anti-trafficking law. To unearth her production, I present a queer genealogy of the human trafficking subject from British campaigns against white slavery in the late nineteenth century to contemporary law. A queer reading of this history demonstrates that rather than preceding laws, the ideal victim serves to personify cultural anxiety over race and gender housed in anti-trafficking policy. This is essential because without contending with this history and restrictive definition of victimhood, it would be impossible for current trafficking law in developed countries to adequately protect LGBTQ+ and irregular migrants who often do not conform to idealised forms of victimhood. Furthermore, a critical analysis of the ideal victim is essential to moving away from a hierarchical evaluation of victimhood altogether.

Retraction Note: Hierarchical evaluation algorithm of logistics carrying capacity based on transfer learning in multimedia environment

Retraction Note: Hierarchical evaluation algorithm of logistics carrying capacity based on transfer learning in multimedia environment

Research on the Effective Fusion of Traditional Art and Old Street Culture Construction Based on Fuzzy Algorithm

With the rapid development of modern science and technology, people gradually lose the importance of traditional art and old street culture, and it plays a vital role in improving the knowledge and cultural level of the people. This paper aims to effectively integrate traditional art and old street culture construction by studying fuzzy algorithms. In the era of rapid technological development, traditional culture and art must keep pace with the times and combine traditional art and old street culture through more scientific algorithms through fuzzy algorithm to solve the effective integration of traditional art and old street culture in today's society. Based on the fuzzy algorithm and visualization technology, this paper checks the meaning of traditional art and collective research by analyzing the fuzzy algorithm, uses experiments to verify the theory, refines cultural symbols, and proposes activation methods to integrate traditional art and old street culture as a whole. Through the defuzzification algorithm and the hierarchical evaluation fuzzy algorithm, people's subjective evaluation of the integration of traditional art and old street culture is calculated, and the algorithm is optimized from the above aspects, which substantially contributes to the effective integration of traditional art and old street culture. This case study can also provide new ideas for the protection of historical and cultural blocks in many cities and the integration of traditional art, remedy the dying traditional art and old street culture, and bring a gluttonous feast to the construction of traditional art and old street culture.

Fuzzy Comprehensive Evaluation of APTS Dispatcher Working Level Based on Cloud Model

Many cities in China have built an advanced public transportation system (APTS) in recent years. These systems cannot carry out automated dispatches but rely on the dispatcher to ensure normal operations. Based on the theory of fuzzy comprehensive evaluation, this study created a hierarchical evaluation model to evaluate the work level of the dispatcher. Firstly, a hierarchical evaluation system was established based on the data of line complexity and dispatch workload provided by the APTS. Secondly, we assigned the weight of the evaluating indicator by combing an expert scoring method and the entropy weight method. We then transformed the quantitative data into qualitative evaluation data with a cloud model. Through a comparison with the standard cloud, the work level of an APTS dispatcher can be defined. The evaluation results for 12 cities in China showed that there was no obvious connection between the working level and bus company size, but the work level was always higher in large cities. We finally obtained the standard range of the evaluation indicator through cluster analysis. This method can be used as a reference to evaluate the work level of dispatchers in other cities, and can reflect the correlation between the work level and dispatching system construction, population and city size.

User Experience Evaluation of B2C E-Commerce Websites Based on Fuzzy Information

With the popularization of personal computers and the development of the Internet, the number of netizens is increasing. The emerging B2C e-commerce platform shows the fierce competition in the e-commerce market. B2C e-commerce distribution is faced with the problems of high distribution cost, long time, and poor quality, which leads to the poor user experience of B2C online shopping and the lack of trust in e-commerce enterprises. This research mainly discusses the user experience evaluation of B2C e-commerce websites based on fuzzy information. First, the AHP analytic hierarchy process is used to construct a hierarchical evaluation system, and then, the two-by-two judgment matrix is compared to the index factors at all levels, and experts are invited to score the method to determine the weight of each index to test whether it meets the consistency requirements. Finally, the fuzzy comprehensive evaluation method is used to perform fuzzy conversion of the original weight, and the membership degree set of the user experience evaluation factors is given, and the fuzzy comprehensive calculation result of the B2C website performance level is calculated. By combining in-depth interviews with website users and questionnaire surveys to analyze the behavioral characteristics of user information navigation, summarize the demand list for product search, product selection, product comparison, and product detail page browsing, and provide a reference for the design and development of information navigation. Calculating the decision model, mainly using fuzzy calculation, calculate the foreground value under each attribute and get the comprehensive foreground value. By comparing with the decision-making behavior model constructed by expected utility theory, it is found that the behavioral decision-making model constructed in this paper based on prospect theory can be closer to the actual situation. In this study, the satisfaction with the function provided reached 68 points, the emotional response 66 points, the aesthetic response 70 points, and the information construction 64 points. Through empirical research, the key factors affecting user satisfaction of B2C e-commerce logistics distribution are summarized, and a B2C e-commerce logistics distribution evaluation system based on user experience is established. This research will provide methods and ideas for the research on user experience design of e-commerce websites and the research and development of related network products. The article helps to draw out the countermeasures and suggestions for the development of the current B2C e-commerce logistics distribution.

Evaluation Method of Students’ “Hierarchical” Education Management Effect Based on Data Mining

In order to improve the accuracy of students’ hierarchical education management effect evaluation, this paper proposes a method of students’ hierarchical education management effect evaluation based on data mining. Firstly, the effect of data mining technology in the evaluation of students’ “hierarchical” education management effect is analyzed, and the abnormal data of education management is eliminated by cosine determination calculation method to realize the preprocessing of students’ “hierarchical” education management data. Then, establish the index system for the evaluation of students’ “hierarchical” education management effect, design the association rules for the evaluation of students’ “hierarchical” education management effect according to the Apriori algorithm, calculate the evaluation index weight according to the analytic hierarchy process and the average method of expert opinions, and realize the consistency test of the evaluation index weight according to the judgment matrix. Finally, the effect evaluation of students’ “hierarchical” education management is realized through data mining. The experimental results show that the accuracy of this method is up to 98.8%, and the evaluation time is only 1.05 s, which shows that this method can effectively improve the evaluation effect of education management effect.

Decision-Making Framework for GI Layout Considering Site Suitability and Weighted Multi-Function Effectiveness: A Case Study in Beijing Sub-Center

The effectiveness of runoff control infrastructure depends on infrastructure arrangement and the severity of the problem in the study area. Green infrastructure (GI) has been widely demonstrated as a practical approach to runoff reduction and ecological improvement. However, decision-makers usually consider the cost-efficacy of the GI layout scheme as a primary factor, leading to less consideration of GI’s environmental and ecological functions. Thus, a multifunctional decision-making framework for evaluating the suitability of GI infrastructure was established. First, the study area was described by regional pollution load intensity, slope, available space, and constructible area. Then, to assess the multifunctional performance of GI, a hierarchical evaluation framework comprising three objectives, seven indices, and sixteen sub-indices was established. Weights were assigned to different indices according to stakeholders’ preferences, including government managers, researchers, and residents. The proposed framework can be extended to other cities to detect GI preference.

Risk Assessment of Building Foundation Pit Construction Based on Fuzzy Hierarchical Comprehensive Evaluation Method

The safety of foundation pit construction is gaining widespread attention. In order to reduce the risks of foundation pit construction and avoid the safety problems brought by the pits, it is necessary to study the risks of foundation pit construction. This paper takes the actual construction of a building as the background. Firstly, the possible main risks of foundation pit construction were identified and summarized, and then, the evaluation index system was formed. Secondly, the risk levels of various types of foundation pit risks were derived through analytic hierarchy process (AHP). In the expert scoring session of the Delphi method, the influences of both the degree of risk consequences and the probability of occurrence are combined. The risk value of the risk event is obtained in combination, which overcomes the bias problem of the traditional single assignment. Finally, an affiliation matrix was established to judge the affiliation of risk indicators to the risk level. The comprehensive risk evaluation level of this foundation pit project construction was assessed as level II. It is the degree of general risk.

Quantitative Evaluation Method of Structural Safety for the Great Wall Hollow Defensive Forts under Gravity Loads

ABSTRACT The Great Wall is one of the most famous cultural heritages in the world. The defensive forts constitute the most important parts of the Great Wall. However, many of them have been severely damaged through the centuries, and their status requires a scientific evaluation. Taking the part of the Great Wall in the Yanqing district with 101 defensive forts as an example, on-site investigations were carried out and the main architectural forms, as well as the damage characteristics, were detected. Based on the architectural form analysis, a hierarchical quantitative evaluation system of the structural safety for the hollow defensive forts was established under vertical load. The grading criteria of crack and displacement indexes were obtained by using the elastic-plastic damage model through the finite element method. The weights of each layer index were calculated with the component importance method and the Analytic Hierarchy Process method. The component importance of the defensive forts is ordered as stone stereobate > brick stereobate > brick arch > flank wall > crenellation. Finally, four representative hollow defensive forts were chosen to demonstrate the proposed quantitative evaluation method. The research results can provide a preliminary screening method for conservation prioritization of the Great Wall forts.

Selection of at-grade highway-rail crossings for grade separation

ABSTRACT Highway-rail at-grade crossings (HRGCs) are critical spatial locations of utmost importance for transportation safety. Using the national HRGC inventory database and 5 years of accident data in Oklahoma, a data-driven hierarchical evaluation process was developed for identifying and prioritizing potential HRGCs as candidates for grade separations, which includes four sequential levels of analyses: the practice guidelines, hazard index-based ranking, safety analysis, and full investment analysis. Various types of benefits, in terms of traffic safety, travel time, vehicle operating cost, and environment, were considered. The top-ranked HRGCs were identified and their ranking results were compared among the different methods. The prioritization results were mostly consistent while with several exceptions. This study relied on existing analysis tools and developed a comprehensive while practical sequential prioritization process, which can be directly implemented at state highway agencies for statewide selection of grade separation projects.

A Hybrid Multiple-Attribute Decision-Making Model for Evaluating the Esthetic Expression of Environmental Design Schemes

A built environment with high-quality esthetic expression can positively contribute to key agendas of urban development. Environmental design is the design of physical environments that mainly respond to people’s behavioral needs and sensory preferences based on environment–behavior relations. Practitioners in this industry often work on esthetic quality improvement. Although previous studies have provided valuable knowledge about important elements of built environment esthetic expression, limited research efforts have been devoted to building a systematic framework that comprises key evaluation elements with high local adaptability and the influence relationships among them. The standards and preferences of esthetic expression in environmental design scheme evaluation are context-based. Providing an effective way to clarify evaluation elements with high local adaptability and the relationships among them may help reduce ambiguity, enhance consensus, and increase efficiency in the decision-making process. Therefore, this study adopted the esthetic expression evaluation of environmental design in China as an example and produced a hybrid decision analysis model by integrating the fuzzy Delphi method (FDM), exploratory factor analysis (EFA), analytic hierarchy process (AHP), and decision-making trial and evaluation laboratory (DEMATEL) method to evaluate the esthetic expression of environmental design schemes. A hierarchical evaluation framework composed of 5 dimensions and 18 evaluation elements was constructed in this study. The key design elements under each dimension and the influence relationships among them were also identified. This paper offers insights into the theoretical investigation and practical development of a systematic evaluation of the esthetic expression of environmental design schemes.

Anti-Poverty Performance Assessment and Forecasting

In order to further help each unit that mitigates the poverty of impoverished regions to improve the efficiency of poverty alleviation, this paper establishes a poverty alleviation performance evaluation index system. Firstly, we analyze the correlation among poverty alleviation indicators through a matrix density diagram. Second, the questions are divided into target layer (poverty alleviation performance), criterion layer (poverty alleviation efficiency, poverty alleviation effect, and poverty alleviation rate), and indicator layer, and the fuzzy hierarchical integrated evaluation method is used to calculate the performance score of each poverty alleviation unit. In addition, based on the historical data, support vector machines were used to calculate the grading rules and predict whether the village could be awarded the title of "advanced village in poverty alleviation". Finally, based on the study, recommendations were made to the National Poverty Alleviation Office for the differences in the individuality of the villages and the distribution of the work content of the poverty alleviation units.

Health status assessment of smart meters based on variable weight and index cloud matter‐element model

Smart meters are one of the crucial terminals in the construction of smart grids, and it is necessary to assess their health status to prevent failures. Based on a hierarchical evaluation index system, this study improved the entropy method and adopted a combined weighting method to integrate subjective and objective weights. The authors constructed an index cloud matter-element model to develop the extensibility of the matter element and used the correlation between the level and index clouds to evaluate the health status of smart meters. Here, the level cloud model and the index cloud model reflected the fuzziness of the boundary of the health level and the uncertainty of the sampling data of indexes, respectively. Based on the theory of constant weight decision and variable weight, the weight was adjusted dynamically by combining the real-time operation data of the entropy method, and the evaluation results were corrected in real time to elucidate the effect of extreme changes and unhealthy conditions on smart meters. Verification of the calculation example demonstrated accurate evaluation using the method in this study, and the maintenance schedule could be adjusted reasonably.

Multi-dimensional evaluation of power market based on multiple attribute decision making

Power market evaluation can reflect the problems in market construction and operation, which is of great significance to the healthy development of power market and the improvement of market rules. Nowadays, several countries are still in the progress of power market liberalization, and an effective power market evaluation system has not been established. In this paper, a hierarchical evaluation system of power market is established according to the construction situation of the developing power markets, which includes market competition level, market operation level, market development level, market opening level and market efficiency level. Then, the Delphi method and the entropy method are used to comprehensively weight the index based on the multiple attribute decision-making theory, and radar charts are used to evaluate the power market. By using the proposed evaluation index and method, the operation condition of a provincial power market in China is analyzed.

Design and Implementation of University Students Scientific Research Ability Evaluation System Based on Neural Network

At present, many colleges attach more and more importance to the cultivation of scientific research ability of college students. However, there is no unified standard to effectively measure the cultivation effect. The current performance inference method cannot comprehensively evaluate the scientific research ability of college students. Few scholars have directly analyzed the college students’ scientific research ability from the internal and external influencing factors. Therefore, this paper tries to design and implement a neural network analysis system for scientific research ability evaluation of college students. After surveying the status quo of scientific research ability evaluation of college students in northern China’s Hebei Province, a hierarchical evaluation index system was constructed for college students’ scientific research ability, referring to the existing evaluation index systems, and the weights were designed for the evaluation indices. Next, the backpropagation (BP) neural network was optimized by chaotic sine-cosine grasshopper optimization algorithm (CSCGOA) and used to establish a neural network analysis system for scientific research ability evaluation of college students. The proposed system was proved effective through experiments. The relevant results effectively enhance the scientific level and accuracy of the evaluation of college students’ scientific research ability, improve the cultivation of college students, and provide a scientific basis for colleges to understand the scientific research ability of their students.