Entropy Weight Method Research Articles

Slagging tendency analysis and evaluation of biomass and coal during co-firing

Co-firing of biomass and coal may cause slagging and fouling and impact the operational lifespan of the boilers. In this paper, eucalyptus bark (EB) and four kinds of coal were used as raw materials, and the degree of slagging was experimentally investigated by scanning electron microscope (SEM), X-ray fluorescence (XRF), and X-ray diffraction (XRD). Moreover, the technique for order preference by similarity to ideal solution (TOPSIS) method and the entropy weight (EW) method were used to establish a slagging evaluation model E-TOPSIS. The results showed that the co-firing of EB and coal caused an increase in ash particle size, particle sintering, and adhesion. XRD analysis confirmed that EB promoted the reaction of calcium compounds with quartz and enhanced the diffraction intensity of muscovite, anorthite, and calcite. The evaluation results of the E-TOPSIS showed that the slagging tendency of EB, IC, and ICEB was severe, which is aligned with the experimental results, and proves the accuracy of this method. The research results can provide a reference for predicting the slagging tendency of biomass and coal during co-firing.

The spatial overlay effect of urban waterlogging risk and land use value

Urban waterlogging poses a severe threat to lives and property globally, making it crucial to identify the distribution of urban value and waterlogging risk. Previous research has overlooked the heterogeneity of value and risk in spatial distribution. To identify the overlay effect of urban land value and risk, this study employs the Entropy Weighting Method (EM) to assess urban value, Principal Component Analysis (PCA) to determine waterlogging risk and key areas (RK), local Moran's I (SC) to identify key areas (HK), and finally Bivariate local Moran's I (DC) to comprehensively evaluate urban value and waterlogging risk to delineate key areas (BH). The results indicate that waterlogging risk is primarily influenced by proximity to water systems (PCA coefficient: 0.567), population density (0.550), and rainfall (0.445). There is a positive correlation between urban value and waterlogging risk, with a global Moran's I of 0.536, indicating that areas with higher urban value also face greater waterlogging risk. The DC method improved identification precision, reducing the BH area by 6.42 and 3.51 km2 compared to RK and HK, accounting for 25.50 % and 15.76 % of the RK and HK identified areas, respectively. At present, rescue resources can access less than one-third of the area within 5 min, but with the DC method, during the centennial rainfall scenario, the accessibility rate within 5 min for the BH area reaches 63 %, and all BH key areas can be covered within 15 min. This study provides a new methodology for identifying key areas of waterlogging disasters and can be used to enhance urban rescue efficiency and the precision management of flood disasters.

Research on green assessment method for prefabricated buildings

In view of the problem that the current evaluation of prefabricated buildings in China focuses more on the ‘assembly rate’, this paper puts forward a green assessment method suitable for prefabricated buildings in China, which determines the evaluation index system according to four aspects: green design, intelligent construction, assembled building quality and comprehensive benefit. In addition, the decision making trial and evaluation laboratory method is used to optimise the index weight, and then the analytic hierarchy process–entropy weight method is used to determine the weight of the index system, and the evaluation index set is quantified and graded. Finally, taking the Hutuo Village public rental housing project in Xi’an City of Shaanxi Province as an example, this paper uses the evaluation method to conduct a green assessment and gives suggestions for improvement in each stage of the project.

Digital infrastructure and innovation: Digital divide or digital dividend?

With more activities being moved online during the COVID-era, digital infrastructure, as a public service, is now playing a greater role in influencing innovation and making the symbiotic relationship between innovation subjects closer. While the surge in patenting in China is associated with a significant innovation gap, there is noticeable regional disparity in digital infrastructure. This study investigates whether the digital infrastructure divide widens the innovation gap in the context of the innovation ecosystem. Based on the entropy weight method, a comprehensive index of digital infrastructure was constructed using provincial panel data from China for the years 2013 to 2018. The findings suggest that the digital infrastructure divide widens the innovation gap; however, this gap can be narrowed by upgrading the industrial structure. The relationship between different regions in China involves both competitive and reciprocal symbiosis. The mediating effect of the industrial structure in the eastern region is smaller than that in the non-eastern region. Moreover, the digital infrastructure divide has a disadvantage for late adopters when digital infrastructure falls below a specific threshold. Once this threshold is crossed, its impact changes from a digital divide to a digital dividend.These findings have several theoretical implications. In digital economy literature, our support for comprehensively assessing the level of digital infrastructure is noteworthy. In innovation ecosystem literature, the broad framework that encompasses the evolution of innovation, including digital infrastructure and industrial structure, is significant. This study highlights the digitization of the innovation ecosystem and offers practical implications for narrowing the innovation gap between researchers, individuals, and policymakers.

Research on gradual planning scheme of power grid based on AHP and entropy weight method

AbstractThe integration of renewable energy into power grid planning poses significant challenges. In this investigation, planning strategies across eight key indicators encompassing economic, reliability, environmental, and adaptability are assessed. Leveraging the analytical hierarchy process alongside the entropy weight method, subjective and objective weights are ascertained and comprehensive weights with parsimonious discriminative data are synthesized. Scores for planning strategies are then derived utilizing these weights. To illustrate and validate the efficacy of the proposed methodology, it was applied to four schemes within the IEEE‐6 node system, incorporating wind and photovoltaic power plants.

High-quality agricultural development in the central China: Empirical analysis based on the Dongting Lake area

High-quality agricultural development constitutes the primary point for forthcoming agricultural and rural endeavors. This study aimed to analyze the characteristics and obstacle factors of the high-quality agricultural development in central China, and the Dongting Lake area was taken as a case. Statistical data, land use data, and other data were adopted, and GIS spatial analysis and mapping technologies, obstacle model, and entropy weight method were used. The research results indicated that: 1) The comprehensive index has increased from 0.4290 in 2010 to 0.4717 in 2020. The change rates of the subsystem ranked from the highest to the lowest were as follows: cultural construction (36.25 %), ecological environment (15.18 %), social security (4.42 %), and material output (2.63 %). 2) The composite index has changed from higher in the west and lower in the east to a unconspicuous spatial difference. The material production index has shifted from higher in the north and lower in the south to a scattered distribution. The social security index has changed from higher in the west and lower in the east to higher in the northwest southeast and lower in the centre. The ecological environment index was higher in the west and lower in the east. The cultural construction index was higher in east and west and lower in the centre. 3) The top 4 obstacle factors were the high-quality development platforms, the agricultural driving force of per cultivated land, the number of agricultural geographical indication and the grain yield of per cultivated land. At the same time, the material output was the biggest obstacle. It is recommended to focus on the agricultural cultural resources in the eastern and western parts. This study can provide guidance and methodological references for similar studies, as well as scientific references for the sustainability of agriculture and optimization of related policies.

Study on the multifunctional spatial-temporal evolution and coupling coordination of cultivated land: A case study of Hebei Province, China.

The rational use of cultivated land can guarantee food security and thus is highly important for ensuring social stability, economic development and national security. The current study investigated the multifunctional temporal and spatial variation characteristics of cultivated land and explored the spatial and temporal characteristics of the multifunction and coupling coordination degrees of cultivated land throughout Hebei Province. Based on the administrative division data, statistical yearbook data and land use status data of the impacted areas, a multifunctional evaluation index system of cultivated land was established. The CRITIC weight method and entropy weight method were used to determine the weight of the index, the comprehensive index model was used to determine the production, social security, ecology and landscape functions of cultivated land of Hebei Province in different periods, the coupling coordination model was used to explore the multifunctional coupling coordination degree of cultivated land in each county, and spatial autocorrelation analysis was performed to determine the correlation of the multifunctional coupling coordination degrees. From 2000 to 2020, the production, social security and landscape function of cultivated land in Hebei Province trended upward; the ecological function trended slightly downward. The multifunctional coupling coordination degree of cultivated land in Hebei Province trended significantly upward and changed from limited coordination to intermediate coordination. Furthermore, it exhibited strong agglomeration and a significant positive spatial correlation, forming a 'V'-type change rule of first decreasing and then increasing. Hebei Province exhibited remarkable spatial and temporal characteristics of the multifunction and coupling coordination degrees of cultivated land. Regions could thus customize different cultivated land functions to maximize the benefits of cultivated land use. The findings of this study may provide a scientific basis and theoretical support for sustainably using and managing cultivated land resources in areas with similar human geographical environments.

Quantitative assessment of human error of emergency behavior for hazardous chemical spills in chemical parks

In-depth research on human error is of great significance to improve the human reliability in the emergency rescue as well as to avoid the occurrence of secondary accidents. Therefore, the standardized process and key emergency behaviors in the emergency rescue process of hazardous chemical leakage accidents are first analyzed. Based on the Cognitive Reliability and Error Analysis Method, the human error mode was sorted out, and the human error probability estimation model was established. Combining the improved Analytic Hierarchy Process and entropy weight method, a model for estimating the severity of human error was established, realizing the quantitative analysis of the human reliability of the emergency behavior. The study showed that the 21 emergency behaviors were clustered into 3 categories, with clustering 1 including 2 emergency behaviors, which have the highest level of severity, clustering 2 including 11 emergency behaviors, and clustering 3 including 8 emergency behaviors. Finally, countermeasures were proposed in four areas, including increasing the level of Common Performance Conditions and the ability to transmit information on accidents, etc. It indicates that the method can widely guide the improvement of emergency response capability in chemical parks.

A Novel Grey Fuzzy Clustering Model and its Application on Students’ Performance Evaluation

Aiming to address the issues of traditional student evaluation methods, which tend to be overly subjective and overlook the intrinsic data structure, this paper introduces a novel grey fuzzy clustering model named the grey entropy game-weighted fuzzy c-means (GEG-WFCM) model. Firstly, subjective weights are calculated using the subjective-objective relationship analysis method, while objective weights are determined through the entropy weight method. Then, a comprehensive approach is adopted, leveraging game theory to calculate the final weights. Based on these comprehensive weights, the relative grey correlation coefficient and fuzzy weighted c-mean algorithm are incorporated to yield the ultimate evaluation results. The proposed model was applied to evaluate student performance, and the experiments show that it can obtain scientific and reasonable results. The model not only acknowledges the expertise of experts but also respects the objectivity of the data, thus circumventing the limitations of purely subjective judgments, and surpassing traditional evaluation methods.

Dual-Objective Reinforcement Learning-Based Adaptive Traffic Signal Control for Decarbonization and Efficiency Optimization

To improve traffic efficiency, adaptive traffic signal control (ATSC) systems have been widely developed. However, few studies have proactively optimized the air environmental issues in the development of ATSC. To fill this research gap, this study proposes an optimized ATSC algorithm to take into consideration both traffic efficiency and decarbonization. The proposed algorithm is developed based on the deep reinforcement learning (DRL) framework with dual goals (DRL-DG) for traffic control system optimization. A novel network structure combining Convolutional Neural Networks and Long Short-Term Memory Networks is designed to map the intersection traffic state to a Q-value, accelerating the learning process. The reward mechanism involves a multi-objective optimization function, employing the entropy weight method to balance the weights among dual goals. Based on a representative intersection in Changsha, Hunan Province, China, a simulated intersection scenario is constructed to train and test the proposed algorithm. The result shows that the ATSC system optimized by the proposed DRL-DG results in a reduction of more than 71% in vehicle waiting time and 46% in carbon emissions compared to traditional traffic signal control systems. It converges faster and achieves a balanced dual-objective optimization compared to the prevailing DRL-based ATSC.

Vulnerability Assessment and Spatial Pattern Analysis of Earthquake Disaster in Hebei Province

To evaluate the vulnerability of earthquake disaster in Hebei Province and analyze the spatial pattern, the aim is to provide theoretical basis for emergency management departments to prevent and respond to disasters. This study uses the subjective and objective evaluation mechanism, through the integration of analytic hierarchy process and entropy weight method to determine the weight distribution of each index. The assessment model is used to assess the vulnerability of earthquake disasters, and the spatial pattern characteristics are studied by global spatial autocorrelation analysis and LISA clustering analysis.The main conclusions are as follows: (1) The area with the greatest vulnerability to earthquake disaster is Shijiazhuang High-tech Zone (0.761); The lowest value is 0.243 in Qian 'an City, Tangshan City, and there are great differences among some regions. (2) The vulnerability of all counties (cities and districts) in Hebei Province has a positive correlation and aggregation with their spatial locations, and the spatial distribution is low in the whole province, high in the local area, high in the southeast and low in the northwest. (3) It is found that measures such as training health workers and expanding professional emergency management team can reduce the overall level of earthquake disaster vulnerability in Hebei Province.

A Multi-Objective Evaluation Method for Smart Highway Operation and Management

Smart highways represent a novel highway concept in the era of big data, emphasizing the synergy among people, vehicles, road facilities, and the environment. However, the operation and management of smart highways have become more intricate, surpassing the adaptability of traditional highway evaluation and management methods. This study integrates the distinctive characteristics of smart highway facilities and operational objectives to enhance and modernize the existing highway evaluation system. Drawing from research on smart highway construction projects, a smart highway evaluation system encompassing facility structure, electromechanical facilities, and operation services is formulated based on a hierarchical analysis method. The quantitative evaluation of each indicator is achieved by combining existing specifications and expert questionnaire solicitation. The group decision-making method is initially employed to optimize subjective weights, followed by the calculation of combined weights using both the entropy weight method and critic method in objective evaluation. Finally, a comprehensive evaluation model is established and validated through engineering projects. The results demonstrate that the evaluation system effectively highlights the advantages and disadvantages in the operation and management of smart highways, thereby fostering the advancement of smart highway iteration.

Analysis of the Variation in Antioxidant Activity and Chemical Composition upon the Repeated Thermal Treatment of the By-Product of the Red Ginseng Manufacturing Process.

Steamed ginseng water (SGW) is a by-product of the repeated thermal processing of red ginseng, which is characterized by a high bioactive content, better skin care activity, and a large output. However, its value has been ignored, resulting in environmental pollution and resource waste. In this study, UHPLC-Q-Exactive-MS/MS liquid chromatography-mass spectrometry and multivariate statistical analysis were conducted to characterize the compositional features of the repeated thermal-treated SGW. The antioxidant activity (DPPH, ABTS, FRAP, and OH) and chemical composition (total sugars, total saponins, and reducing and non-reducing sugars) were comprehensively evaluated based on the entropy weighting method. Four comparison groups (groups 1 and 3, groups 1 and 5, groups 1 and 7, and groups 1 and 9) were screened for 37 important common difference markers using OPLS-DA analysis. The entropy weight method was used to analyze the weights of the indicators; the seventh SGW sample was reported to have a significant weight. The results of this study suggest that heat treatment time and frequency can be an important indicator value for the quality control of SGW cycling operations, which have great potential in antioxidant products.

A Grid-Wide Comprehensive Evaluation Method of Power Quality Based on Complex Network Theory

To achieve a hierarchical and quantitative evaluation of grid-wide power quality in the distribution network, reflecting the overall power quality level of the distribution network, a comprehensive evaluation method for power quality in a grid-wide system based on complex network theory is proposed. Firstly, based on the propagation characteristics of power quality disturbances, a power quality evaluation index system is constructed. Secondly, to reflect the constraint effect of the local power quality level of nodes on the overall power quality level of the distribution system, corresponding indices such as improved node degree, improved node electrical betweenness, and node self-healing capability are proposed based on complex network theory, and the power quality influence degree of nodes is calculated. Then, the GRA-ANP (Grey Relational Analysis–Analytic Network Process) subjective weight calculation method is improved by introducing grey relational analysis to address the impact of differences in different decision-making results. Based on power quality monitoring data, the entropy weight method is used for objective weighting. To avoid the partiality of a single weight evaluation result, the game equilibrium algorithm is employed to calculate the comprehensive weight of each power quality index. Subsequently, considering the correlation and dependency among indices, the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) method is used to obtain the power quality grade of each node. Combining this with the calculation of the power quality influence degree of nodes, the overall power quality grade of the distribution network is determined, achieving a hierarchical and quantitative evaluation of power quality in the entire distribution system. Finally, through a case study analysis of an improved 13-node distribution network, it is verified that the proposed method can fully extract data information and produce comprehensive and accurate power quality assessment results by comparing it with other methods. This provides strong support for the safe and stable operation of the distribution system and the subsequent optimization and management of power quality.

Spatio-Temporal Characteristics,Regional Differences and Dynamic Evolution of Green Finance Development Level in China

As an emerging field that integrates finance and environmental protection, green finance aims to promote sustainable development and environmental protection through financial instruments and market mechanisms. The Chinese green finance market is rapidly emerging as a significant force in the global green finance arena. This paper applies methods such as entropy weight method, Dagum Gini coefficient, kernel density estimation, and spatial Markov chain to analyze the spatiotemporal characteristics, regional differences, and dynamic evolution of China’s green finance development level from 2010 to 2021. The results of the study indicate that the comprehensive index of China’s green finance development level has been increasing, with the mean comprehensive index of green finance development level showing a pattern of "East >National>Central>West". The overall level of green finance development in Chinese provinces has been increasing as a whole, and the level of some provinces has been moving upwards. The regional differences in green finance development level have been decreasing over the study period, with the central region having the smallest regional differences and the eastern region having the largest. From the perspective of distribution dynamics, it can be seen that the degree of imbalance in the green finance regional development in China is gradually increasing, with polarization phenomenon existing. The green finance development of Chinese provinces does not exist in isolation, and there is a certain degree of interdependence among them. When the green finance development level of neighboring provinces is better than that of the local area, it is conducive to the improvement of the local green finance development level, and there is the possibility of leapfrogging transfer.

Investigating customer behavior on Instagram to enhance online sale: modeling the effect of content types and broadcasting tools

Purpose This study aims to examine the role of various Instagram contents on customer behavior. The studied case is associated with herbal teas sold on active Instagram pages. Design/methodology/approach A structured questionnaire is exploited to collect data from customers. The integration of two entropy weight methods and weighted sum method are used to evaluate the priority of contents. In addition, model development is illustrated through which Instagram broadcasting tools are prioritized benefiting from fuzzy cognitive map method. Findings The results illustrate that customer behavior is moderated by content types, which empirically enhances the profitability of the business. The results of this study reveal that educational live, show other ones experience at live as well as motivational lives are the most effective contents. This study is a pioneering one to practically assess the construct of social media engagement through the effects of content types on the Instagram platform. Originality/value The effects of various contents, including motivational content, other customers’ experiences, products, educational content and purchase bill, on customer behavior are studied.

Can the best management practices resist the combined effects of climate and land-use changes on non-point source pollution control?

Climate and land-use changes have an overlying impact on non-point source (NPS) pollution in river basins. However, the control effect of Best Management Practices (BMPs) for NPS pollution is not yet clear under future scenarios. The Soil and Water Assessment Tool (SWAT) model was coupled with the entropy-weighted method, global climate patterns and land-use data to explore the dynamic variations in total nitrogen (TN) and total phosphorus (TP) loads in the Jing River Basin during the baseline (2000−2020) and future periods (2021–2065), evaluate the pollution reduction effectiveness of individual and combined BMPs, and propose practical BMP configurations. Results indicate that a future trend of urban land expansion, particularly in the economic scenario (LU_SSP585), leads to weakened environmental ecosystems, while the sustainable scenario (LU_SSP126) exhibits more balanced land development. The MIROC-ES2L model demonstrates higher Taylor skill scores, forecasted significant increases in precipitation, maximum, and minimum temperatures under the SSP585 scenario. Spatial heterogeneity in TN and TP loads is notable, showing an upward trajectory in the future. The interaction between land-use and climate change has complex effects on TN and TP loads, with land-use-induced TN changes being relatively small (4.6 %) and TP changes substantial (24.3 %). The spatial distribution, under overlying effects, leans towards the influence of climate change, emphasizing its dominant role in TN and TP load variations. Distinct differences exist in the reduction of NPS pollution loads among different BMPs, with combined BMPs demonstrating superior effectiveness. The environmental-cost effectiveness trends of BMPs remain consistent across various future scenarios. RG (Return agricultural land to grass), RG + TT (Terracing), and RG + FR10 (Fertilizer reduction: 10 %) + GW (Grassed waterway) + FS (Filter strip) + TT emerge as the most effective single, double, and multiple BMP combinations, respectively. The results offer valuable insights for preventing and mitigating future NPS pollution risks, optimizing land-use layouts, and enhancing watershed management decisions.

The Impact of Water-Saving Irrigation on Rice Growth and Comprehensive Evaluation of Irrigation Strategies

To explore the effects of different water-saving treatments on rice plant growth and select suitable water-saving irrigation strategies for aerobic rice varieties, we conducted relevant field experiments from June to October 2023 at Jiangsu Runguo Agricultural Development Co., Ltd., China, which is located in a north subtropical monsoon climate where the soil is alkaline sandy loam. Four water treatments were set up, including the control of local conventional irrigation (CK, without water stress), mild water-saving treatment (W1, 20% more water saved than CK), moderate water-saving treatment (W2, 30% more water saved than CK), and severe water-saving treatment (W3, 40% more water saved than CK). The experiment results showed that rice plant heights were inhibited and leaf chlorophyll contents increased under all water-saving treatments compared to CK. Among them, the MDA content in paddy leaves under the W1 treatment decreased, while the activities of SOD and POD were enhanced and the membrane lipid peroxidation capacity of rice was also enhanced. Meanwhile, the results showed that the rice yield and quality under the W1 treatment significantly improved. Based on those experiments, a comprehensive evaluation of rice plant height, chlorophyll content, grain yield, yield components, and rice quality was conducted using the TOPSIS entropy weight method. It was preliminarily concluded that the suitable irrigation scheme for south and central Jiangsu was 20% water-saving irrigation compared with CK. In summary, under the premise of maintaining the economic yield of rice cultivation, an appropriate water irrigation plan helped save water resources and promote rice growth.

Optimization of H-type Anti-slide Pile Support Structure Based on RSM-NSGA-II

The parameters of an h-type anti-slide pile are optimized and analyzed with respect to its structural characteristics. Based on laboratory model tests, further analysis of its stress characteristics is carried out through numerical simulation methods. Then, the response surface methodology (RSM) combined with the NSGAII algorithm was employed to perform multiobjective optimization of the reinforcement performance and engineering cost for h-type anti-slide piles regarding landslide consideration. Finally, the entropy weight TOPSIS method was used for comprehensive evaluation to obtain the optimal structural parameters. The results show that the bending moment distribution of the front and rear rows of h-type piles first increases and then decreases with increasing depth, and the front soil pressure of the pile gradually increases. Using RSM-NSGA-II instead of finite element modeling can shorten the optimization time, and the accuracy of the surrogate model reaches 94.8%. NSGA-II is much stronger than that of the particle swarm optimization algorithm. The entropy weight method combined with the TOPSIS method can obtain the unique optimal solution from the Pareto solution set without prior knowledge. The h-type anti-slide pile with the best structural parameters reduces the cost by 75.19%, while the slope safety factor increases by 47.39%. This method provides a new idea for structural optimization.

Constructing and implementing a performance evaluation indicator set for artificial intelligence decision support systems in pediatric outpatient clinics: an observational study

Artificial intelligence (AI) decision support systems in pediatric healthcare have a complex application background. As an AI decision support system (AI-DSS) can be costly, once applied, it is crucial to focus on its performance, interpret its success, and then monitor and update it to ensure ongoing success consistently. Therefore, a set of evaluation indicators was explicitly developed for AI-DSS in pediatric healthcare, enabling continuous and systematic performance monitoring. The study unfolded in two stages. The first stage encompassed establishing the evaluation indicator set through a literature review, a focus group interview, and expert consultation using the Delphi method. In the second stage, weight analysis was conducted. Subjective weights were calculated based on expert opinions through analytic hierarchy process, while objective weights were determined using the entropy weight method. Subsequently, subject and object weights were synthesized to form the combined weight. In the two rounds of expert consultation, the authority coefficients were 0.834 and 0.846, Kendall's coordination coefficient was 0.135 in Round 1 and 0.312 in Round 2. The final evaluation indicator set has three first-class indicators, fifteen second-class indicators, and forty-seven third-class indicators. Indicator I-1(Organizational performance) carries the highest weight, followed by Indicator I-2(Societal performance) and Indicator I-3(User experience performance) in the objective and combined weights. Conversely, 'Societal performance' holds the most weight among the subjective weights, followed by 'Organizational performance' and 'User experience performance'. In this study, a comprehensive and specialized set of evaluation indicators for the AI-DSS in the pediatric outpatient clinic was established, and then implemented. Continuous evaluation still requires long-term data collection to optimize the weight proportions of the established indicators.