Technique For Order Preference By Similarity To An Ideal Solution Method Research Articles

Evaluating the landfill leachate quality using leachate pollution index (LPI) and technique for order preference by similarity to an ideal solution (TOPSIS)

Variability and diversity of landfill leachate cause difficulties in assessing the actual degree of threat to the environment and selecting an appropriate method of disposal or treatment. Therefore, quantifying leachate contamination potential is essential in landfill management and could be used to assess the accuracy of landfill operation and its impact on surrounding areas. The aim of this paper was to evaluate the performance of the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method and its suitability in determining leachate pollution potential in comparison to the Leachate Pollution Index (LPI) method. For this purpose, the quality of leachate from the landfill, collected four times a year from 2004 to 2021, was analysed. The following parameters were monitored: pH, EC, Pb, Cu, Zn, Cr, and Hg. On the basis of the measured parameters, the LPI and TOPSIS indexes were calculated. The obtained results indicated that the TOPSIS method is more sensitive and accurate in observing changes in leachate quality. It can be applied to any number of contaminant parameters without restrictions on scope, quantity, or their relative importance. It can also be used to compare the variations in leachate quality over time or to analyse differences in leachate quality among various landfill sites.

Effects of Nutrient Solution Application Rates on Yield, Quality, and Water-Fertilizer Use Efficiency on Greenhouse Tomatoes Using Grown-in Coir.

The yield, quality, and water-fertilizer use efficiency of crops are important parameters for assessing rational water and fertilizer management. For an optimal water and fertilizer system with respect to the nutrient solution irrigation of greenhouse tomatoes using cultivation substrates, a two-year greenhouse cultivation experiment was conducted from 2022 to 2023. Three drip fertigation treatments (T1, T2, and T3) were implemented in the experiment, where nutrient solutions were supplied when the substrate's water content reached 60%, 70%, and 80%. The frequency of nutrient solution applications is based on weighing coconut coir strips in the morning and evening at 7:00 to determine the daily water consumption of plants. Nutrient solutions were supplied when the substrate's water content reached the lower limit, and the upper limit for nutrient supply was set at 100% of the substrate water content. The nutrient solution application was carried out multiple times throughout the day, avoiding the midday heat. The nutrient solution formula used was the soilless tomato cultivation formula from South China Agricultural University. The results show that plant height and the leaf area index rapidly increased in the early and middle stages, and later growth tended to stabilize; the daily transpiration of tomatoes increased with an increase in nutrient solution supply, and it was the greatest in the T3 treatment. Between the amount of nutrient solution application and the number of years, the yield increased with the increase of the amount of nutrient solution, showing T3 > T2 > T1. Although the average yield of the T2 treatment was slightly lower than that of the T3 treatment by 3.65%, the average irrigation water use efficiency, water use efficiency, and partial fertilizer productivity of the T2 treatment were significantly higher than those of the T3 treatment by 29.10%, 19.99%, and 28.89%, respectively (p < 0.05). Additionally, soluble solid, vitamin C, and soluble sugar contents and the sugar-acid ratio of tomatoes in the T2 treatment were greater than those in the other two treatments (p < 0.05). Using the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method, it was concluded that the nutrient solution application rate of 70% can significantly increase water and fertilizer use efficiency and markedly improve the nutritional and flavor quality of the fruit without a significant reduction in yield. This finding provides significant guidance for the high-yield, high-quality, and efficient production of coconut coir-based cultivated tomatoes in greenhouses.

Risk management of green supply chains for agricultural products based on social network evaluation framework

AbstractThe green supply chain of agricultural products (GSCAP) is a key link for rural revitalization and sustainable development in China. However, it faces various risks from internal and external environments that threaten its performance and stability. This paper proposes a novel framework and system for identifying and evaluating the main risks in the GSCAP from the perspective of agricultural enterprises. The framework combines social network analysis (SNA) and an improved technique for order preference by similarity to an ideal solution (TOPSIS) method. SNA is used to analyze the correlations and influences among different types of risks, while the improved TOPSIS method is used to rank the risks of different GSCAPs and identify the key risks in each supply chain. The framework and system are verified by a case study of CDYBIT, a leading platform of food safety big data service in China. The results show that the supermarket supply chain has the highest risk, followed by the group catering supply chain, and the five‐star hotel supply chain has the lowest risk. The main risk factors for each supply chain are also discussed, and some suggestions for risk management are provided. This paper contributes to the literature by providing a comprehensive and systematic risk assessment framework and system for the GSCAP, which can help agricultural enterprises improve their risk awareness and response capabilities.

Regional differences in health resource allocation: a longitudinal study in the Chengdu-Chongqing economic circle, China

ObjectiveTo analyse regional differences in health resource allocation in the Chengdu-Chongqing economic circle.DesignA longitudinal analysis that collected data on health resource allocation from 2017 to 2021.SettingThe number of beds, health...

A Hybrid Group Multi-Criteria Approach Based on SAW, TOPSIS, VIKOR, and COPRAS Methods for Complex IoT Selection Problems

The growth of Internet of Things (IoT) systems is driven by their potential to improve efficiency, enhance decision-making, and create new business opportunities across various domains. In this paper, the main selection problems in IoT-type systems, criteria used in multi-criteria evaluation, and multi-criteria methods used for solving IoT selection problems are identified. Then, a Hybrid Group Multi-Criteria Approach for solving selection problems in IoT-type systems is proposed. The approach contains the Best Worst Method (BWM) weighting method, multi-criteria Simple Additive Weighting (SAW), Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), and Complex Proportional Assessment Method (COPRAS), and a method that combines the solutions obtained using the four considered multi-criteria methods to obtain a single solution. The SAW, TOPSIS, VIKOR, and COPRAS methods were analyzed in relation to their advantages, disadvantages, inputs, outputs, measurement scale, type of normalization, aggregation method, parameters, complexity of implementation, and interactivity. An application of the Hybrid Group Multi-Criteria Approach for IoT platform selection and a comparison between the SAW, TOPSIS, VIKOR, and COPRAS solutions and the solution of the proposed approach is realized. A Spearman correlation analysis is presented.

Comprehensive Assessment and Empirical Research on Green and Low-Carbon Technologies in the Steel Industry

The iron and steel industry is the leading industry supporting China’s industrial sector. Currently, there is less assessment work on green and low-carbon technologies for the iron and steel industry. This study clarifies the overall strategy of technology assessment by researching the relevant theories and methods of technology assessment. The study further establishes a scientific and reasonable comprehensive assessment index system of green and low-carbon technologies for the iron and steel industry from the aspects of technology index, economy and promotion, and application, including factors such as 11 indexes, the amount of energy saving, carbon dioxide emission reduction, and the resource recovery rate by utilising analytical and comprehensive methods and combining with the characteristics of the technologies. By analysing and comparing the advantages and disadvantages of the commonly used assessment methods, the entropy weighting method, grey correlation analysis method, and TOPSIS (technique for order preference by similarity to an ideal solution) method are combined and optimised to construct a comprehensive assessment model. The Latin hypercube sampling method is also introduced to analyse the technical parameters in combination with the evaluation model. Finally, fourteen iron and steel green and low-carbon technologies were selected for case assessment and uncertainty analysis of technical parameters, and it was found that the comprehensive assessment result of gas combined cycle power generation technology was optimal. After determining the weights of each assessment indicator through the entropy weighting method, it is concluded that the technical performance indicator &gt; economic indicator &gt; promotional indicator. A comparative analysis of the results under the three preference decisions concludes that technical performance is the main obstacle to improving the comprehensive assessment score of the technology, followed by the economics of the technology. Finally, the uncertainty analysis of the technical parameters shows that the fluctuation of the technical parameters not only affects the performance of the technology, but also affects the weights of the indicators and the comprehensive evaluation results of the technology.

Rheological performance evaluation of activated carbon powder modified asphalt based on TOPSIS method

In this study activated carbon powder (ACP) was incorporated into asphalt to substitute a portion of the conventional filler (mineral powder, MP). The dynamic modulus at elevated temperatures, temperature-dependent viscosity sensitivity, low-temperature creep, and the interaction between asphalt and ACP were examined through dynamic shear rheometer testing, viscosity testing, and bending beam rheometer testing. Moreover, statistical methodologies such as the entropy weight method (EWM) and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) were employed to optimize the proportion of ACP by evaluating the comprehensive rheological behavior of asphalt mastic (including high temperature performance, low temperature performance, flowability, and asphalt-ACP interaction). The findings demonstrate that ACP can enhance the resistance of asphalt mastic to high-temperature deformation to a certain degree. The ratio of creep rate to stiffness (m/S) decreases with the addition of ACP, indicating that ACP may exacerbate the occurrence of low-temperature thermal cracking in asphalt mastic. The interaction ability of asphalt mastic is significantly enhanced when a portion of the filler is replaced with ACP. The loss factor shows significant impact on the comprehensive evaluation. According to TOPSIS analysis, asphalt mastic with a blending proportion of 40% ACP and 60% MP performs better in terms of comprehensive rheological properties.

Green Residential Building Design Scheme Optimization Based on the Orthogonal Experiment EWM-TOPSIS

A multi-objective decision method is proposed based on the combining orthogonal test, entropy weight method (EWM) with TOPSIS (technique for order preference by similarity to an ideal solution) in this article. The method is more objective and efficient than traditional methods in the design of green residential buildings. A villa in Nanjing was taken as an example, and the cost, building energy consumption, and daylight factors were used as decision-making indexes. A total of six control factors were selected: terrain elevation, window area, building orientation, the opening ratio of exterior windows, roof structure, and window glass material. Each factor was designed with three levels. First, a design scheme index system was constructed, and the orthogonal experimental design was used to select representative design schemes. Then, the EWM and the TOPSIS method were used to determine the weight of each index, a comprehensive evaluation of the residential building design scheme was conducted, and, finally, the optimal scheme was confirmed via range analysis. The results show that the multi-objective decision-making model based on the orthogonal experiment EWM-TOPSIS is suitable for green residential building design and the optimal solution obtained is “15 m elevation, a 1200 × 1500 mm size vacuum glass, an orientation of 170° and an external window opening ratio 45% with a 40 mm thick expanded insulation board roof”.

Optimal Scheduling of Micro-Energy Grid Based on Pareto Frontier Under Uncertainty and Pollutant Emissions

With the continuous improvement of micro-energy grid, in order to reduce carbon emissions and environmental pollution, a multi-objective optimization operation strategy considering the distributed energy generation uncertainty, environmental factors, and self-supply rate is proposed in this paper. First, to simulate the uncertainty of distributed energy, we used the three-parameter Weibull distribution to simulate the wind power. Then, for the load side, an innovative electric and thermal comprehensive demand response model is proposed. Different from the traditional micro energy network that only considers the heat energy balance, this paper also considers the thermal inertia of buildings to more accurately describe the characteristic of the heat load. Meanwhile, on the basis of economic factors, the abandon rate of distributed energy, environmental coefficient and self-sufficiency rate are also regarded as three objective functions. Finally, in order to obtaining a set of solutions at the Pareto front, the entropy-weighted TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method is introduced to obtain the global optimal solution. Simulation study of multiple scenarios shows the effectiveness of the proposed method. Compared with the method that considers only economic costs, the pollutant emissions are reduced by 50kg and self-power supply rate is increased by 20%.

Comparative Analysis Of Saw And Topsis In Selecting Recipients Of Basic Food Assistance

The Basic Food Program is one of the Indonesian government's alternative programs for distributing aid to underprivileged or poor communities. A selection process needs to be carried out to determine recipients of basic food assistance. Decision Support Systems are effective systems used to produce calculations with output in the form of rankings. The methods that are quite widely used are the Simple Additive Weighting (SAW) method and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). This research aims to apply the SAW and TOPSIS methods in selecting aid recipients so that appropriate results are obtained which can be proposed as solutions to decision-making problems. There are 6 criteria used in this case, including: residence, occupation of the head of the family, type of floor, type of wall, place to urinate, lighting source. The data used as a test is data from the Banyuurip village community in 2023. The calculation process is carried out by finding the weight value of each alternative for each criterion. The selected aid recipients are those who have the greatest value as the best alternative. From the calculation results of the SAW (Simple Additive Weighting) and TOPSIS methods, the calculation results of the two methods were obtained. The alternative with the largest value or rank 1 produced by SAW and TOPSIS was both selected as alternative A10. Of the 12 data tested, SAW and TOPSIS have 50% similar alternative ranking results, including: rank 1 = A10, rank 5 = A9, rank 7 = A7, rank 8 = A6, rank 11 = A2, and rank 12 = A12. The SAW method gets better results compared to the TOPSIS method, because it gets precise, stable results and shorter processing time.

A Systematic Decision-Making Approach for Quality Function Deployment Based on Hesitant Fuzzy Linguistic Term Sets

As a powerful tool for improving customer satisfaction, quality function deployment (QFD) can convert customer requirements (CRs) into engineering characteristics (ECs) during product development and design. Aiming to address the deficiencies of traditional QFD in expert evaluation, CRs’ weight determination and ECs’ importance ranking, this paper proposes an enhanced QFD model that integrates hesitant fuzzy binary semantic variables, the Best–Worst Method (BWM), and the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). The objective is to determine the prioritization of product engineering characteristics. Indeed, hesitant fuzzy linguistic term sets (HFLTS) have found extensive application in decision-making problems. Compared to other fuzzy language methods, HFLTS offers greater convenience and flexibility in addressing decision-makers’ hesitations and uncertainties. Initially, the combination of hesitant fuzzy linguistic term sets with interval binary tuple language variables is employed to articulate the uncertainty in the assessment information provided by QFD team members. Subsequently, the improved BWM and TOPSIS methods based on HFLTS are used to improve the accuracy of the importance ranking of engineering characteristics by determining the weights of CRs and prioritizing ECs in two stages. Finally, the feasibility and effectiveness of the proposed method are validated through an illustrative example.

Risk assessment of China's overseas energy investments considering the response ability to major risk events: A case study of COVID-19

This paper constructs a new risk evaluation index system for overseas energy investment, while considering the country's response ability to major risk events using COVID-19 as experience. The entropy weight method and the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method are used to conduct overall and sub-dimensional risk assessment for 52 countries. The results show that: (1) among the seven risk dimensions considered, the response ability to major risk events dimension has the highest weight, accounting for 16.47 %. This indicates that Chinese energy corporations cannot ignore the risk posed by major risk events, such as COVID-19, in their overseas investments. (2) Among the 52 countries investigated, investment risk is significantly lower in developed countries than in developing countries, mainly because of the better performance of the former across the four dimensions of economics foundation, governing ability, social development, and investment environment. (3) The COVID-19 pandemic has impacted the landscape of China's overseas energy investment risk. Due to the different performance of each country in other dimensions, the risk rankings of the majority of developing countries decreased when considering their COVID-19 response, while that of most developed countries increased.

TOPSIS Method Based on Entropy Measure for Solving Multiple-Attribute Group Decision-Making Problems with Spherical Fuzzy Soft Information

A spherical fuzzy soft set (SFSS) is a generalized soft set model, which is more sensible, practical, and exact. Being a very natural generalization, introducing uncertainty measures of SFSSs seems to be very important. In this paper, the concept of entropy, similarity, and distance measures are defined for the SFSSs and also, a characterization of spherical fuzzy soft entropy is proposed. Further, the relationship between entropy and similarity measures as well as entropy and distance measures are discussed in detail. As an application, an algorithm is proposed based on the improved technique for order preference by similarity to an ideal solution (TOPSIS) and the proposed entropy measure of SFSSs, to solve the multiple attribute group decision-making problems. Finally, an illustrative example is used to prove the effectiveness of the recommended algorithm.

Spatial-temporal pattern and influencing factors of tourism ecological security in Huangshan City

It is of important theoretical and practical value to scientifically evaluate tourism ecological security for the sustainable development of tourist cities. The study focuses on the “characteristics of the impact factors on tourism ecological security at different levels” of tourism ecological security that have been neglected in the previous literature. From the perspective of Compound Ecological systems theory, we built an evaluation index system for tourism ecological security in Huangshan City based on the Pressure-State-Impact-Economic-Environmental-Social (PSR-EES) model and used a combination of the entropy weight TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method, traditional and spatial Markov chains, and panel quantile regression to analyze and characterize the spatial-temporal dynamics of security levels and driving factors. The results showed that (1) the level of tourism ecological security of the districts and counties in Huangshan City improved rapidly, but the difference was expanding. The level of tourism ecological security in the four counties was generally higher than that in the three districts. (2) In terms of the spatial-temporal dynamic evolutionary characteristics, the transfer of tourism ecological security in Huangshan City has its characteristics of stability and path dependence. Type transfers usually occur between adjacent levels. The lower the level of tourism ecological security, the higher the probability of upward transfer. A neighborhood background plays an important role in the process by which a higher neighborhood rank increases the probability of upward transfer. (3) Regarding the driving factors, environmental pollution and economic development have a negative inhibitory effect on tourism ecological security, and the negative effect decreases as the level of TES improves. The top three positive effects were government intervention and educational levels. The degree of regional greening and government intervention had greater positive marginal effects on lower-level areas. In contrast, tourism development, educational level, and labor input had greater positive marginal effects on areas with higher TES levels.

Optimizing water and nitrogen management strategies to improve their use efficiency, eggplant yield and fruit quality.

With improvement in living standards, consumer preferences for vegetables are changing from quantity- to quality-oriented. Water and nitrogen supply, as two major determinants of vegetable crop yield and quality, can be optimally managed to improve the yield and quality. To evaluate the response in yield, fruit quality, and water and nitrogen utilization of eggplant to different water and nitrogen management strategies, a 2-year (2021 and 2022) field trial under mulched drip irrigation was conducted. The growth period was divided into seedling, flowering and fruit set, fruit development, and fruit ripening stages. Three irrigation levels were applied during the flowering and fruit set stage: W0, adequate water supply (70%-80% of field water capacity, FC); W1, mild water deficit (60%-70% FC); and W2, moderate water deficit (50%-60% FC). In addition, three nitrogen application rates were applied: N1, low nitrogen level (215 kg ha-1); N2, medium nitrogen level (270 kg ha-1); and N3, high nitrogen level (325 kg ha-1). The irrigation and nitrogen rates were applied in all combinations (i.e., nine treatments in total). Adequate water supply throughout the reproductive period in combination with no nitrogen application served as the control (CK). The yield of the W1N2 treatment was significantly increased by 32.62% and 35.06% in 2021 and 2022, respectively, compared with that of the CK. Fruit soluble protein, soluble solids, and vitamin C contents were significantly higher under W1 than W2. Fruit quality was significantly higher under the N2 rate compared with the other nitrogen rates. The W1N2 treatment showed the highest water productivity, with a significant increase of 11.27%-37.84% (2021) and 14.71%-42.48% (2022) compared with that under the other treatments. Based on the average water-deficit degree and nitrogen application rate, W0 and N1 had the highest partial factor productivity of nitrogen. Assessment of the results using the TOPSIS (technique for order preference by similarity to an ideal solution) method indicated that mild water deficit in combination with the medium nitrogen application rate (W1N2) was the optimal water and nitrogen management strategy for cultivated eggplant. The present findings contribute novel insights into the sustainable cultivation of eggplant in an oasis arid environment.

Prioritization of CMIP5 based climate models in simulating precipitation using multicriteria decision making methods

Selecting climate models that are accurate in simulating observed weather is a difficult task for impact modellers. For more reliable future projections, model selection is desirable. The effectiveness of nine GCM-RCM combinations in simulating precipitation over the Meenachil river basin in Kerala is examined in this study using data from the CORDEX-SA datasets. Four performance indicators—correlation coefficient (R), percentage bias (PBIAS), skill score (SS), and root mean square error (RMSE)—were used to evaluate the models’ simulation abilities. The models were ranked based on their ability to simulate observed climate data measured over a baseline period (1980–2005) using the TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method and the PROMETHEE-2 (Preference Ranking Organisation Method of Enrichment Evaluation) method of multi-criteria decision making approaches. Rankings of GCM-RCM combinations were carried out in both scenarios of equal and varying weight. The results of the study found that the top three precipitation prediction models for the Meenachil river basin are GFDL-RCA4, GFDL-RegCM4, and CNRM-RCA4.

Evaluation of community basic public health service effect in a city in Inner Mongolia Autonomous Region--based on entropy weight TOPSIS method and RSR fuzzy set.

By analyzing 23 evaluation indicators included in 14 national basic public health service programs in a region of Hohhot City, Inner Mongolia Autonomous Region, China, the performance of basic public health services in the region in 2021 were analyzed to clarify the implementation and conduct of relevant programs. We also use this study as a basis to radiate the work of municipal basic public health services centered on the region and the outstanding problems reflected and to provide theoretical contents and suggestions that can be referred to for the same regions in central and western China as well as worldwide. Using the TOPSIS method as the basis for the data analysis method, the evaluation indexes are ranked in terms of their proximity to the idealized target, and combined with the entropy value method, Technique for order preference by similarity to an ideal solution (TOPSIS) and rank-sum ratio (RSR) were used to rank 14 basic health care providers by grade. A comprehensive evaluation of the performance of basic public health services in a region of Hohhot City, Inner Mongolia Autonomous Region in 2021 was conducted through a joint model of entropy -weighted TOPSIS and RSR, making full use of the characteristics and advantages of the fuzzy joint, and conducting a comprehensive analysis from the perspective of the ratio weight and the method of graded calculation, making the study more distinguishable and measureable. In this study, for the regional basic public health services, a total of 23 evaluation indicators of basic public health service projects were included, among which the top three indicators with the weight of the entropy value method indicators were found to include the rate of Chinese medicine health management for the elderly, the rate of health management for the elderly, and the BCG vaccination rate after the analysis of the weight of the indicators; After the entropy-weighted TOPSIS evaluation showed that the Ci values of the regions were found to be between 0.378 and 0.715 through the calculation of the positive and negative ideal values of each indicator; RSR staging method evaluation showed that three community health centers (X2, X10, X12) had excellent evaluations of basic public health services; The number of evaluations as poor and moderate are 2 (X3, X9) and 9 (X1, X4, X5, X6, X7, X8, X11, X13, X14), respectively; Finally, the results of the entropy-weighted TOPSIS method and the fuzzy joint model of RSR staging method are basically consistent with the overall trend of the above two methods, and the reliability and credibility of the research results are high. The entropy-weighted TOPSIS and RSR joint model can evaluate the effectiveness of basic public health services in a more comprehensive and holistic way. The results of the RSR staging results and the related weight ratio analysis show that the basic public health service programs in Hohhot, Inner Mongolia Autonomous Region are relatively balanced, but there are some differences; The same genus of elderly Chinese medicine health management rate, health management rate of the elderly, BCG vaccination rate several indicators accounted for a higher weight, its correlation with the key population-related items is high, suggesting that the future key population health service items should be focused on, and future research should be suggested from two key research.

Selection of Optimal Well Trajectory Using Multi-Objective Genetic Algorithm and TOPSIS Method

This study presents a novel approach for optimizing well paths in extended reach drilling (ERD) wells. Different trajectories can be used for ERD wells, each with its pros and cons. Previous research overlooked certain objective functions in single-objective optimization and lacked an autonomous method for selecting the best solution from Pareto optimal solutions in multi-objective optimizations. Furthermore, they lacked comparing different profiles in well design. Risk assessment and operational factors, which greatly influence optimization and drilling success, were insufficiently considered. This study utilized the multi-objective genetic algorithm (MOGA) and the technique for order preference by similarity to an ideal solution (TOPSIS) method to select the optimal well path based on torque, wellbore length, risk (e.g., keyseat), and required tools. First, all possible trajectories were determined, and MOGA identified the optimal path with minimal torque and length. The fuzzy decision-making method automatically selected the best solution from the Pareto optimal solution set. The associated risks and required tools are evaluated for each trajectory. Finally, the TOPSIS method selected the optimal trajectory based on torque, length, risks, and required tools. The case study demonstrated that the undersection path was the most advantageous trajectory for ERD wells, with a 60% closeness to the ideal state. The multiple build trajectory achieved 57% closeness, while the build and hold and double build paths had lower closeness values (43 and 28%, respectively). Consequently, it can be inferred that in the context of ERD wells, it is preferable to carry out the deviation process at deeper depths.

A risk assessment method of the energy supply chain based on combination weights and Technique for Order Preference by Similarity to an Ideal Solution

Nowadays, the energy supply chain (ESC) with the coupling of multiple energy systems is able to promote the complementation between various energy types. However, due to a more complex structure, ESCs are facing more risks from the internal major links and external environment. Hence, an risk assessment method of the ESC based on combination weights and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is proposed. First, a multi-level risk index system with 4 main indices and 16 sub-level indices is established. Next, methods of Criteria Importance Though Intercriteria Correlation (CRITIC) and entropy weighting are presented for determining the initial weights of each sub-level index respectively, in which the CRITIC method considers the conflicts between the indices, and the entropy method focuses on the variation of the index values. After that, a combination weighting approach based on relative entropy is used to assign the final combination weight to each index. Then, considering the final combination weights, the TOPSIS method is adopted to assess the risk level of an ESC. Finally, case studies of 4 regional ESCs are carried out to verify the effectiveness of the proposed method, while the final risk level score of region B’s ESC is the lowest which indicates the best performance in predicting, controlling, and mitigating its internal and external risks.

Comfort and functional evaluation of silk/profiled antibacterial polyester fabric

In this study, a novel multifunctional woven silk fabric characterized by quick-drying and bacteriostasis was developed through the addition of modified polyester filaments. The effect of fabric structure and filament proportion on the properties of multifunctional silk fabrics was investigated to determine the optimal weaving parameters for optimizing the overall fabric manufacturing process. Moreover, the fabric’s basic wearing properties, hygroscopic performance (e.g. wicking height, drip diffusion, and permeability), and antibacterial performance against Escherichia coli and Staphylococcus aureus were examined. Subsequently, the optimum parameters and weave structures were analyzed and evaluated using AHC (Analytic Hierarchy Process)-TOPSIS (Technique for Order Preference by Similarity to an Ideal Solution) method. The novel fabric exhibits great wearability, antibacterial properties, dyeing properties, and hand feeling, and it shows great commercial potential and takes on a vital significance in future silk product development.