Grey Relational Analysis Method Research Articles

Turned Surface Monitoring Using a Confocal Sensor and the Tool Wear Process Optimization

Laser scanning technology has been used for several years. Nevertheless, no comprehensive study has been conducted to prove that the application of confocal chromatic sensor (CCHS) laser technology is effective and suitable to verify the integrity parameters of machined surfaces in terms of cutting tool damage. In this paper, the optimization and effects of five factors (cutting speed, feed, depth of cut, attachment length of the workpiece, and tip radius) on the roundness deviation measured by CCHS and, at the same time, on the amount of wear on the back side of the cutting part of the tool were studied according to ISO 3685, which was measured with a microscope. The results obtained were evaluated using the gray relational analysis method (GRA), in conjunction with the Taguchi method, and the significance of the factors was demonstrated using the analysis of variance (ANOVA) method.

Performance Comparison of Optical Wireless Communication Using Gray Relational Analysis

In this study, Indian Optical Wireless Communication (IOWC) is examined as a short-range method for transferring data at high rates. It is rapidly gaining popularity as an effective method, with an optical transmitter at the IOWC terminal and a receiver included. For example, it can be used in tall buildings separated by several hundred meters, where light beams propagate through the atmosphere and convey information to the recipient. IOWC has several advantages over its competitors, most notably its quick setup, free-of-charge licensing, and lightweight, high-capacity communications. However, IOWC still faces many challenges, including improving communication efficiency in adverse weather conditions or during construction. In the field of underwater acoustic communication, great progress has been made, but IOWC is still better than traditional audio communication systems due to its significantly lower power consumption and ability to provide simple computational problems for short-range wireless links. IOWC has many potential applications, including in Indian coastal waters. The gray relational analysis (GRA) method is simple in calculations and optimizations, and research shows that it is easy to extend this proposed method for problems with more than two answers. To determine the material and life strategies in a one-dimensional array, a method provides multidimensional alternatives based on Taguchi using gray correlation analysis. The optimization design is done on a top cap with a thin wall section unique to TWBs structures. The gray relational analysis method can be used to describe the alternative and evaluation parameters in optical wireless communication. As far as the optical wireless communication APM-EDM process is concerned, alternatives include Lamina Atlas NT-42C1-0484, AOP LED Corp PU-5WAS, Kingbright AADI-9090QB11Gitek/3, LGLB-313E, Toshiba TL12B01 (T30), and Lumex SML-LX1610USBC. The evaluation parameters are wavelength (nm) and luminous flux (Im). From the final result, it is seen that AOP LED Corp PU-5WAS got the first rank, whereas Toshiba TL12B01 (T30) has the lowest rank

Analysis of heterogeneous and distributed manufacturing environment using Gray Relational Analysis (GRA) Method

Manufacturing Environment Production of one or more products Dedicated production lines to do or areas. Convenience stores stock items that can manufacture or have them made to order, only if requested by the buyer. The objective of this thesis Finding the best cleaning location Manufacturing Environment or Gray Relational Analysis (GRA) method showing. GRA (Gray Relational Analysis) Method, Cincinnati Milagron T3-726, Cybotech V15 Electric Robot, Hitachi America Process Robot, Unimation PUMA 500/600, United States Robots Maker 110 Alternatives or Load Capacity, Computational Steps for Solving Repeatable Multi-Attribute Decision-Making Problems Node Speed, Memory Capacity, the evaluation parameters reached by the handler The United States Robots Maker 110is got the first rank whereas the Hitachi America Process Robot is having the lowest rank. In this paper Manufacturing Environment United States Robots Maker 110is got the first rank whereas the Hitachi America Process Robot is having the lowest rank

Selection of Handloom Fabrics Based on Thermo-Physiological Characteristics Using Multi - Attributes Decision Making Algorithm

ABSTRACT Dissolution of one component from multi-component yarn by suitable chemical treatment brought a significant change in structure that ultimately enhance the performance in terms of thermo-physiological behavior of fabrics. In this study, attempt has been made to develop a ranking of handloom fabric quality, which can be used for selecting fabrics based on thermo-physiological characteristics like thermal resistance, air permeability, water vapor permeability, compressibility, drying capacity, and bending rigidity. Technique for Order Preference by Similarity to Ideal Solution Method (TOPSIS) and Grey Relational Analysis Method (GRA) has been used for ranking 48 handloom samples (before and after treatment) made up of same warp yarn and different filling (for both machine and hand spun) prepared according to mixture design from different percentages of wool, polyester and poly vinyl alcohol (PVA). Ranking results obtained through TOPSIS and GRA show that after treatment of handloom fabric made up of hand spun yarn having less percentage of wool as a weft can be used in place of treated handloom fabric having machine spun yarn with higher percentage of wool. Results also indicate that dissolution of PVA component improves ranking in both fabrics either having machine spun or hand spun yarns as a weft.

Performance evaluation of Wireless Network selection using Gray Rational Analysis (GRA) Method

This paper proposes a network selection solution that is user location- and knowledge-based, aiming to diversify by choosing the best value network in a wireless network environment, improving video delivery. When multi-attribute decision making (MADM) techniques are used for wireless network vertical approval, the impact of weighting techniques combined with Gray Rational Analysis (GRA) is studied. Performance analysis of the GRA algorithm is conducted for hierarchical, background, conversational, interactive, and streaming classes of services using Random Weighting (RW) and Least Square Weight (LSW) techniques. In the MCDM context, multiple alternatives (e.g., wireless networks) refer to attributes such as Network 1, Network 2, Network 3, Network 4, and Network 5. Delay (msec), Jitter (msec), BER (x 10), Throughput (kbps), and Cost (units) are used as evaluation methods. In this type of analysis, gray relational analysis (GRA) methods determine the best solution for negative short distances and very long distances to settlement, but do not consider the relative importance of these distances. As a result, Wireless Network 5 ranked first, and Wireless Network 4 ranked the lowest.

Performance optimisation of the turning process along with multi-surface heating process

AbstractMaterials that are difficult to cut possess excellent qualities and machinability, though conventional machining techniques require additional energy to circumvent the problems associated with the turning process. In this study, heat-assisted turning of duplex stainless steel (SS) was carried out. Various heating techniques such as infrared (IR)-, ultraviolet (UV)- and hot air (HA)-assisted heating were adopted. The experiment used an L16orthogonal array with the most significant parameters such as heating method, feed rate in millimetres per revolution (mm/rev), depth of cut (millimetres [mm]) and cutting speed (metres per minute [m/min])on the cutting force and surface roughness. The technique for order performance by similarity to ideal solution (TOPSIS) and grey relational analysis (GRA), were used to optimise the output performance. The results of TOPSIS showed that the 16th experimental combination, i.e., the HA heating method, with feed rate = 0.175 mm/rev, depth of cut = 0.1 mm and cutting speed = 150 m/min, required a smaller cutting force and resulted in lower surface roughness. In case of the GRA method, the best output performance was observed for the 15th experimental combination, that is, the HA heating method, with feed rate = 0.15 mm/rev, depth of cut = 0.2 mm and cutting speed = 200 m/min. Compared to the non–heat-assisted turning process, the HA- and UV-assisted processes required 10.25% and 7.69% lesser cutting force, respectively, and the surface roughness in case of the HA method was 15.13% lesser.

ASSESSMENT OF CORPORATE SUSTAINABILITY PERFORMANCE WITH ENTROPY AND GREY RELATIOANAL ANALYSIS: AN APPLICATION IN THE BANKING SECTOR

Bu çalışmada Uluslararası Entegre Raporlama Ağı’nın (IIRC) yayınlamış olduğu Entegre Raporlama Çerçevesi ele alınarak, Türkiye’de faaliyet gösteren bankaların 2019 yılına ait Entegre raporları, “Kurumsal Sürdürülebilirlik İlkeleri” olarak bilinen; sosyal sürdürülebilirlik, çevresel sürdürülebilirlik, kurumsal yönetim sürdürülebilirliği ve finansal sürdürülebilirlik ile incelenmiştir. Bu bağlamda 2019-2020 yılları arasında Entegre rapor yayınlayan; Garanti BBVA, İş Bankası, Türkiye Sınai ve Kalkınma Bankası, Ziraat Bankası, VakıfBank ve Yapı Kredi Bankası’na ait Entegre raporlardan, içerik analizi yöntemiyle nitel veriler elde edilmiştir. Elde edilen nitel veriler, sayısal verilere dönüştürülerek çok kriterli karar verme yöntemlerinden, Entropi yöntemine dayalı Gri İlişkisel Analiz (GİA) yöntemiyle bankalar için kurumsal sürdürülebilirlik performansları değerlendirilmiştir. Analiz sonuçları değerlendirildiğinde, Türkiye’de faaliyet gösteren bankaların sürdürülebilirlik faktörleri Entropi ağırlıklarına göre sırasıyla; çevresel sürdürülebilirlik, sosyal sürdürülebilirlik, kurumsal ve finansal sürdürülebilirlik olarak elde edilmiştir. Entropi ağırlıklı GİA yönteminden elde edilen sürdürülebilirlik performans sıralaması sonuçlarında ise Garanti BBVA'nın ilk sırada olduğu sonucuna ulaşılmıştır.

Using GA - BP Coupling Algorithm to Predict the High-performance Concrete Mechanical Property

As a cementitious composite, concrete's property depends on the matrix generated from cement hydration and the dispersed phases such as aggregates. Compression strength is an important mechanics performance index of concrete quality, especially the High-performance Concrete (HPC). However, owing to the expensive cost of test and the existence of high-dimensional nonlinear mapping between compression strength and basic materials, it is uneasiness to precisely forecast the compression strength value of HPC by general formula method. In this research, a novel machine learning system, Genetic Algorithm and BP Neural Network (GA-BPNN) coupling algorithm, is offered to predict the compression strength of HPC. GA-BPNN coupling algorithm model used 181 groups of HPC mixture data to determine 8 factors affecting its compression strength (i.e., Water, Portland Cement, Waterbinder Ratio, Fine Aggregate Ratio, Air-entraining Agent, Fly Ash, Silica Fume, and Superplasticizer) as the input variables of the model, while compression strength was set as the output variable. In addition, 166 sets of training set data were segmented into training, validation and test set again, and BP neural network (BPNN) was compared with GA-BPNN to verify the generalization capacity of the model in this research. By forecasting the compression strength of 15 test sets, the average relative error is only 0.902%. Finally, the sensitivity of input variables of GA-BPNN model was analyzed by using Gray Relational analysis (GRA) method. Six models were established to research the impact of sensitivity and quantity of input variables on model performance by ignoring individual input variable. The research is shown that GA-BPNN model not only has the powerful nonlinear mapping ability of BPNN, but also has the global search optimization ability of GA, and showed stronger robustness and prediction potential in the assessment of compression strength value of HPC. The sensitivity analysis shows that, to compression strength of HPC, Cement, Water and Water-binder ratio has a sensitivity score of 0.8166, 0.70122, 0.66772, respectively while Fly Ash has the lowest sensitivity.

Analyzing critical factors of strategic alignment between operational excellence and Industry 4.0 technologies in smart manufacturing

PurposeThe manufacturing sector is highly competitive and operationally complex. Therefore, the strategic alignment between operational excellence methodologies and Industry 4.0 technologies is one of the issues that need to be addressed. The main aim of the study is to determine the critical factors of strategic alignment between operational excellence methodologies and Industry 4.0 technologies for manufacturing industries and make comparative analyses between automotive, food and textile industries in terms of strategic alignment between operational excellence methodologies and Industry 4.0 technologies.Design/methodology/approachFirst, determining the critical factors based on literature review and expert opinions, these criteria are weighted, and analytical hierarchy process is run to calculate the weights of these criteria. Afterward, the best sector is determined by the grey relational analysis method according to the criteria for the three manufacturing industries selected for the study.FindingsAs a result of AHP, “Infrastructure for Right Methodology, Techniques and Tools, is in the first place,” Organizational Strategy, is in the second place, while the third highest critical factor is “Capital Investment”. Moreover, based on grey relational analysis (GRA) results, the automotive industry is determined as the best alternative in terms of strategic alignment between operational excellence (OPEX) methodologies and I4.0 technologies.Originality/valueThis study is unique in that it is primarily possible to obtain the order of importance within the criteria and to make comparisons between three important manufacturing industries that are important for the economies of the world.

Grey relational analysis method for typhoon vulnerability assessment of civil engineering structures based on the 2-tuple linguistic neutrosophic number.

As one of the severe natural disasters, typhoon hazard brings tremendous tragedy to human beings. The foreland in the southeast of China is one of the most typhoon prone areas in the world. There are amount of damage of civil engineering structures induced by typhoon every year. Especially for the spacious villages, the low-rise buildings are vulnerable to typhoon so that many of them are destroyed regionally. The typhoon vulnerability assessment of civil engineering structures is a classical multiple attribute group decision making (MAGDM) issues. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is built based on the grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNSs) with incomplete weight information. For deriving the weight information of the attribute, an optimization model is built on the basis of the GRA, by which the attribute weights can be decided. Then, the optimal alternative is chosen through calculating largest relative relational degree from the 2-tuple linguistic neutrosophic number positive ideal solution (2TLNNPIS) which considers both the largest grey relational coefficient (GRC) from the 2TLNNPIS and the smallest GRC form 2-tuple linguistic neutrosophic number negative ideal solution (2TLNN NIS). Then, combine the traditional fuzzy GRA model with 2TLNNSs information, the 2TLNN-GRA method is established and the computing steps for MAGDM are built. Finally, a numerical example for typhoon vulnerability assessment of civil engineering structures has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.

Influence of mainland China’s industrial structure evolution on the development of Cross-Strait trade: the grey relational analysis (2011–2020)

Because of the complex and special political relationship between Mainland China and Taiwan. Cross-Strait trade is influenced by many variables, there has been a view that trade relations between Mainland China and Taiwan are more influenced by political factors. However, between the Cross-Strait, the trade volume has generally shown an upward development trend, especially since 2001. Therefore, the political factors can hardly explain the facts, and economic factors, especially industrial structure factors in Mainland China play an important role in Cross-Strait trade. Based on the small sample data since 2001, this study employed Grey Relational Analysis （GRA） method to verify the evolution of Mainland China’s industrial structure and Cross-Strait trade. Based on the results show that the evolution of Mainland China’s industrial structure strongly impacts the development of Cross-Strait trade. The tertiary industry has the strongest correlation with Cross-Strait trade, followed by the secondary and primary industries. Furthermore, the evolution of the mainland’s industrial structure will expand as well as accelerate the imbalance of Cross-Strait trade.

An activated carbon from walnut shell for dynamic capture of high concentration gaseous iodine

In order to capture the high concentration gaseous iodine from off-gas streams under nuclear accident conditions, an advanced activated carbon was prepared by using walnut shell as a raw material and zinc chloride as an activator agent (named WS-ZnCl2). The pore structure and functional groups characteristics of the adsorbent were researched via three techniques including N2 adsorption–desorption isotherms, transmission electron microscope (TEM), and Fourier transform infrared spectroscopy (FTIR). The Brunauer-Emmett-Teller (BET) surface area, the total pore volume and the average pore size of the adsorbent were observed to be 1360 m2/g, 0.68 cm3/g and 2.00 nm, respectively. In addition, the adsorption capacities of the adsorbent to capture gaseous iodine were investigated with static and dynamic experimental adsorption methods. The results of the static experimental adsorption indicated that the gaseous iodine equilibrium adsorption capacity of the walnut shell before and after ZnCl2 activation increased from 606 mg/g to 2374 mg/g at condition of 80 °C and ambient pressure. The dynamic adsorption performance of the adsorbent for capture of gaseous iodine was studied by varying operating parameters, such as temperature, adsorption column height, and the flow rate. More significantly, the maximum dynamic adsorption capacity of the adsorbent for capture gaseous iodine reached a record of 1634 mg/g at 60 °C, 2.2 cm and 250 mL/min. Finally, the importance ranking of the influencing factors on the dynamic adsorption was analyzed by Grey relational analysis (GRA) method. The results showed that adsorption capacity was obviously affected by flow rate, whereas adsorption time was highly influenced by adsorption column height. The adsorbent researched in this paper has potential to capture high concentration gaseous iodine.

Research on coal demand forecast and carbon emission reduction in Shanxi Province under the vision of carbon peak

Facing the increasingly severe climate situation, China strives to improve its Nationally Determined Contributions, promising to reach its carbon peak by 2030. Accurately predicting the future demand quantity and changing the trends of coal resources is the key to maintaining national energy security and achieving the goal of “carbon peak” and is also an important research topic in the future. To improve the prediction accuracy, this study sorts out eight common factors affecting the coal demand from the aspects of the economy, population, and energy. The grey relational analysis method was used to describe the degree of importance of each factor and screen out the relatively vital factors. The system dynamics model for coal demand in Shanxi Province was also established. The coal demand and carbon emission trends in Shanxi Province from 2021 to 2030 were predicted under business-as-usual, low-speed and high-speed development scenarios. The study results show that: 1) During the 14th Five-Year Plan to 15th Five-year Plan, the trend of coal demand has changed from increasing to decreasing. Under the three scenarios, the coal demand in 2021 is expected to be 372.03 million tons, 365.97 million tons, 360.04 million tons, and it is expected that the coal demand will peak in 2025, and will reach 394.77 million tons, 390.27 million tons, and 385.66 million tons under the three scenarios, respectively. 2) With the development of population and economy, the total energy demand shows a continuously increasing trend. It is estimated that the total energy consumption will reach 237.46-242.93 million tons of standard coal in 2030, and the total energy demand will continue to grow in the foreseeable future. 3) The carbon dioxide emission is closely related to the coal demand, showing a similar variation trend. Under the business-as-usual development scenario, carbon emissions in 2021 are 699.62 million tons, and carbon emissions are expected to reach 681.12 million tons in 2030. The low-speed development and high-speed development scenarios have different degrees of energy saving and emission reduction benefits. Compared with the business-as-usual development scenario in 2030, the carbon dioxide emissions will be reduced by 1.64 million tons and 3.56 million tons respectively. Finally, we put forward important policy measures to promote the economic transformation and upgrading of Shanxi Province and accelerate the realization of the “carbon peak” goal.

Characterization of eco-friendly cutting fluid developed from neem seed oil

Cutting fluid is a key component in retaining workpiece quality, tool life and overall high productivity in machine operations. It is needed as input for minimal surface roughness, minimal tool wear and better machining finished product. This study addressed tool wear and surface roughness by evaluating optimal factor effectiveness of the surface roughness and tool wear during turning of AISI 304 alloy steel using an environmentally friendly fluid. The non-biodegradable and non-recyclable nature of conventional cutting fluids as mineral oils have raised serious concerns with the research community and prompted the renewal of research in this area with focus on replacing the mineral based cutting fluids with environmentally friendly cutting fluids such as neem seed prepared cutting fluid (N-PCF). The neem seed oil (NSO) was sourced locally and characterized by investigating the physiochemical properties as well as it’s fatty acid composition (FAC). The cutting fluid formulation was 1:9 of oil to water in the ratio. The cutting fluids which aided surface roughness and tool wear reduction during turning of the austenitic stainless steel AISI 304 and improved the carbide insert tool was evaluated and compared with mineral oil-based cutting fluid. Also, the response surface method (RSM) of experimental design and Grey relational analysis (GRA) multi-response optimization were employed respectively. The experimental results revealed that the formulated oil showed 8.67 pH value, 0.50 mm2/s viscosity, resistant to corrosion, stable and deep yellowish colouration. The multi-response optimal factor combination obtained from GRA showed multi-response effect of the formulated Neem seed prepared cutting fluid at feed rate of 0.82 mm/rev, depth of cut of 0.65 mm and cutting velocity of 800 rev/min while that of Mineral prepared cutting fluid (M-PCF) was achieved with feed rate (0.82 mm/rev), depth of cut (0.65 mm) and cutting velocity (500 rev/min). GRA and RSM results showed acceptable parameters that contribute to the science of machining and this is in good agreement when compared with those obtained from other cutting fluids used for turning operation.

Purchase decision making of garage equipment using an integrated fuzzy AHP and grey relation analysis method

PurposeAutomobile maintenance garages require varieties of equipment for their smooth functioning. However, the purchase of the right equipment from alternatives is a tough task as it depends on several economic, technical, and environmental considerations, etc. Moreover, there are different sellers for such equipment, whose features would be satisfying the purchase criteria in varying levels or degrees. Hence, this purchase decision becomes a complex decision-making problem.Design/methodology/approachAn integrated multi-criteria decision-making approach that includes the combination of fuzzy AHP (analytic hierarchy process) and GRA (grey relational analysis) is used for the purchase decision-making of garage equipment. Various purchase decision criteria regarding garage equipment are assimilated through literature and interaction with garage professionals. The weightage of each purchase criteria of garage equipment is derived using fuzzy AHP. After the establishment of weights, various equipment suppliers are evaluated according to their conformance to the criteria using the GRA method.FindingsThe methodology of FAHP helped in ranking the different purchasing criteria based on their importance. It follows the following sequence: cost of ownership, technical specifications, operational characteristics, reliability and maintenance, after-sales support, commercial features, environmental pollution, and end of life characteristics. GRA methodology has been applied for the purchase of the best common rail test bench among alternatives according to their fulfillment of the purchase criteria requirements that are evaluated by a team of experts.Originality/valueThe integrated approach developed in this work for garage equipment purchase will help garage management to prioritize each supplier of the equipment based on their level of conformance to the purchase criteria.

Identifying influential priority of factors governing the acute biological toxicity of two kinds of industrial wastewaters

Abstract Identifying the key parameters or components mainly contributing to the acute toxicity of wastewater would be helpful to quickly and conveniently reflect their biological toxicity. In this study, the components/parameters and biological toxicity of 64 effluent samples collected from two factories producing konjac and glass were analyzed. It was found that the two types of wastewaters were not effectively dealt with. Moreover, the acute biological toxicity evaluated by the bioluminescence inhibition to Vibrio fischeri revealed that ∼90% of the effluents were marked as toxic with bioluminescence inhibition higher than 50%. By applying a grey relational analysis (GRA) method to investigate the influential priorities of the effluent characteristics on biological toxicity, the results demonstrated that the top four influential factors on the bioluminescence inhibition were as follows: TN ≈ SO42− > Cl− > As ≈ Hg (for konjac-manufacturing effluents) and Zn > SO42− ≈ TN > As > Cl− (for glass-producing effluents). These results would be useful for fast recognizing the biological toxicity features of industrial effluents via evaluating the most influential parameters, and helpful for reducing the biological acute toxicity to protect the downstream wastewater treatment plant from abrupt collapse.

Assessment of Sustainable Maintenance Strategy for Manufacturing Industry

This study creates a framework to aid in the sustainability of maintenance strategies. The framework was created using expertise from the industry and academia. Using this knowledge, three multi-criteria tools were chosen for the maintenance strategies evaluation. The tools include grey relational analysis (GRA) techniques, additive ratio assessment (ARAS), and step-wise weight assessment ratio analysis (SWARA). In a production system, they were used to assess four planned maintenance strategies. The strategies are periodic maintenance (S1), meter-based maintenance (S2), predictive maintenance (S3) and prescriptive maintenance (S4). The ARAS approach was used to obtain the strategy rating for the various requirements. This study used the SWARA method to determine the requirements’ importance using an intuitionistic fuzzy triangular number. The ARAS results were combined using the GRA method. This study observed that the criteria utilised to choose a maintenance strategy for equipment depend on the information collected from six specialists in a manufacturing organisation. For instance, it was discovered that S3 was the maintenance approach that best suited the system’s technical needs. At the same time, S2 was found to be less effective. The economic needs analysis showed that S1 is the maintenance strategy that is most appropriate for the system, while S3 is the least appropriate. S1 is the most appropriate maintenance method for the system, given the social requirements, whereas S2 is the least effective. According to the results of the environmental requirements, S2 is the best maintenance plan for the system, while S4 is the worst. According to the GRA approach, the system’s best and least appropriate maintenance strategies are S2 and S4, respectively.

Evaluation of waste water treatment technologies by combined analytical hierarchy process and grey relational analysis

<p>Recycling of wastewater is an important issue as it is used for many important applications such as industries, agriculture, household applications and due to water scarcity across the different countries. Wastewater treatment is an important activity as it protects human being and the ecosystem from harmful and toxic elements present in wastewater. Performance evaluation of wastewater treatment technologies being complex Multi-criteria Decision Making (MCDM) problem that has contradictory evaluation factors. This paper is focused on the analysis of factors that affect evaluation of wastewater treatment technologies and their impact by developing a model which combine Analytical Hierarchy Process (AHP) and Grey Relational Analysis (GRA) for the assessment and ranking wastewater treatment technologies (WWTTs) respectively. The best WWTT is chosen based on data acquired through a case study. AHP is applied for computing criteria weights based on comparative significance while Grey Relational Analysis method is applied for ranking and selecting the wastewater treatment technologies. Sensitivity analysis is performed to show the impact of grey relational scores of alternatives in line with variations of distinguished coefficients.</p>

An Efficient Method Combined Data-Driven for Detecting Electricity Theft with Stacking Structure Based on Grey Relation Analysis

Nowadays, electricity theft has been a major problem worldwide. Although many single-classification algorithms or an ensemble of single learners (i.e., homogeneous ensemble learning) have proven able to automatically identify suspicious customers in recent years, after the accuracy of these methods reaches a certain level, it still cannot be improved even if it continues to be optimized. To break through this bottleneck, a heterogeneous ensemble learning method with stacking integrated structure of different strong individual learners for detection of electricity theft is presented in this paper. Firstly, we use the grey relation analysis (GRA) method to select the heterogeneous strong classifier combination of LG + LSTM + KNN as the base model layer of stacking structure based on the principle of the highest comprehensive evaluation index value. Secondly, the support vector machine (SVM) model with relatively good results of the stacking overall structure experiment is selected as the model of the meta-model layer. In this way, a heterogeneous integrated learning model for electricity theft detection of the stacking structure is constructed. Finally, the experiments of this model are conducted on electricity consumption data from State Grid Corporation of China, and the results show that the detection performance of the proposed method is better than that of the existing state-of-the-art detection method (where the area under receiver operating characteristic curve (AUC) value is 0.98675).

High throughput millifluidics mixer with double triangle baffle for improvement of mixing performance and reduction of flow resistance designed by grey relational analysis

To improve the mixing performance and reduce flow resistance, in this study, a novel mixer with double triangle baffles was designed and optimized by the combination of CFD simulation and grey relation analysis method. Mixing index and Poiseuille number were selected as two key indexes to evaluate the mixing performance and flow resistance of the mixer. The orthogonal experiment was conducted with selecting the aspect ratio of baffles (α), the thickness of baffles (h), the spacing between adjacent baffles (c) and the number of baffles (d) as design variables. Among all design variables, d has the greatest influence on the mixer performances. The results show that the optimized mixer has a maximum increase of 14.25% in mixing index and a maximum decrease in Poiseuille number of 60.02%. Finally, the optimal configuration was scaled-up to centimeter level, which makes the mixer have high mixing performance, low flow resistance and high throughput at the same time. All the findings provide useful references for high throughput mixer design and optimization.