Grey Relational Analysis Method Research Articles

Grey Relation System Applications in Multi-Attribute Decision-Making and Forecasting in Financial Management

Objective: The objective of the paper is to verify the Grey relation analysis methods and compare them with known models in financial management. The first part is devoted to MADM (multi-attribute decision methods) and the second one to grey forecasting methods. Method: Localization GRA and globalization GRA multi-criteria models are described and compared with the TOPSIS method. The forecasting GRA(1,1) model based on cumulative data is described, derived and compared with the linear growth model. The models are verified on the data set. Results and Discussion: The globalisation model based on a pair-wise comparison of alternatives is different, and the ranking of alternatives is fully different in comparison with the TOPSIS model. It was found that the localisation GRA model and TOPSIS, both constructed on similarity measures, present similar and comparable results. So, the grey relation approach considers the uncertainty of input data. The forecasting model GRA(1,1) is computed and compared with the growth model. Results show that the growth model is the trendy model, and the non-trendy series is overestimated or underestimated, so the GRA model looks more robust. Research Implications: The problem of imprecise data is investigated. And it is a realistic condition for practical decision-making. The problem of lack of data is often a phenomenon in decision-making. Traditional statistical methods cannot be applied. Therefore, grey relation methodology is one approach to overcoming the problem of imprecise data and lack of data. Uncertainty and lack of data problems are topics important for research and the managerial community. Originality/Value: Sometimes, in financial decision-making, high-quality data or long-term time series is not at our disposal, and on the other hand, decisions have to be made. This problem is often neglected and solved by not-relevant traditional statistical models. Therefore, methods that allow the solving of such problems are useful. It was shown that a grey relation methodology for multicriteria financial performance evaluation and forecasting shows more robust and stable results and could be more relevant for imprecise data or short time series data in financial decision-making problems.

Lifetime prediction of epoxy coating using convolutional neural networks and post processing image recognition methods

The rapid failure of organic coatings in deep-sea environments complicates accurate lifetime prediction. Given the rapid cracking characteristic on the coating surface in this environment, a comprehensive “performance-structure” failure model was established. Initially, a targeted image recognition approach containing convolutional neural network (CNN) and post-processing was constructed for the crack area detection. An overall precision of 82.81% demonstrated the network’s good accuracy. The length distribution and the statistical evolution of cracks were extracted from SEM images to obtain the kinetic equation of the cracks related to coating structure degradation. In addition, the kinetics of water diffusion and coating adhesion were examined, as they represent critical parameters of coating performance. Based on this achievement, a failure model incorporating three dominant factors was integrated by the gray relational analysis method. The average prediction error of the model was 2.60%, which lays the groundwork for developing image-based methods to predict coating life.

An improved interval‐grey‐probability QFD method for prioritizing engineering characteristics under vague environment

AbstractAt present, the interval‐grey quality function deployment (QFD) has been widely used to address a vague information at the early stage of product design. However, the existing interval‐grey QFD method suffers from a problem that it is incapable of comparing specific values from any two intervals within overlapping segments associated with the importance of engineering characteristics (ECs) during the process of prioritizing their importance. This problem consequently impedes the effective prioritization of their magnitudes, thus hindering the prioritization of the importance of ECs. Aiming at addressing the problem, an improved interval‐grey‐probability QFD method is proposed. The proposed method integrates interval grey numbers, grey relational analysis (GRA), and interval‐probability ranking method into the interval‐grey QFD framework to prioritize the importance of ECs under a vague environment. Specifically, the interval grey numbers are used to assess the importance of customer requirements (CRs) and the GRA method is adopted to construct the relationship matrix of CRs‐ECs, respectively. Based on the importance of CRs and the relationship matrix of CRs‐ECs, the interval‐probability ranking method is introduced to measure the prioritization of the importance of ECs. The proposed method is validated by a multi‐function flash drive. Results show that the proposed method is more accurate than existing methods in terms of the deviation degree.

A comprehensive validation of GRA with ant colony optimization for robust optimal design: A case study on the forming process

Sheet metal forming design involves numerous factors and controlling all these parameters to prevent cracks is a major challenge to maintain the quality. Therefore, the careful selection of process parameters is critical for ensuring product longevity. Several researchers employed different techniques for optimal selection of process parameters but consistency among the techniques and validation of results in real time scenarios will play a pivotal role in determining the suitable parameters. Therefore, the current work presents a validation method of Grey Relational Analysis (GRA) results with Ant Colony Optimization (ACO) for the robust optimum design with an illustrative example of forming process. Al 6061 – T6 alloy was chosen as a material for deep drawing process and L27 Orthogonal Array was planned to conduct experiments with four input parameters such as blank thickness, Die and Blank Temperature, Die Speed, Lubrication at three levels each. Punch force and Thickness variation were considered as the output parameters. GRA Technique was implemented to find the best optimal combination and regression equation was developed to predict the nature of objective function. These results were given as an input to ACO, a nature inspired algorithm to search for the optimal solution with in the design space. Sensitivity analysis has also been performed to highlight the effectiveness of the proposed solution in terms of solution quality and computational efficiency. The ACO method, GRA technique and the experimental results are almost similar with a margin of acceptable deviation. The results indicated the robustness of the projected approach in achieving the quality of solution.

Evaluation system of vocational education construction in China based on linked TOPSIS analysis

In response to the task of vocational education reform in the new era, in order to cultivate innovative skilled talents, it is necessary to improve traditional evaluation methods to enhance their efficiency. This study proposes an evaluation model for vocational education construction that combines grey relational analysis and approximate ideal point method (TOPSIS). By selecting indicators and combining subjective analytic hierarchy process and objective entropy weight method for weight allocation, the weights of the indicators are determined using subjective analytic hierarchy process and objective entropy weight method. Through experimental analysis, the results showed that among the 11 analysis indicators, the weight of policy environment indicators was the highest at 0.124, while the weight of employment rate and contract signing rate indicators was the lowest at 0.050. The above results indicate that the TOPSIS comprehensive evaluation system based on grey correlation analysis has better application effects in practical scenarios and is more suitable for the development requirements of vocational education.

Multi-objective optimization and influence degree analysis of the thermally integrated HP-ORC carnot battery based on the orthogonal design method and grey relational analysis

Thermally integrated heat pump (HP)-organic Rankine cycle (ORC) Carnot battery is a promising solution for efficient energy storage and waste heat utilization. Firstly, in order to research the influence degree of the operating parameters on the system performance, single-objective optimization is conducted by the orthogonal design method. Then, multi-objective optimization is conducted by combining the grey relational analysis (GRA) and orthogonal design method to assess the comprehensive performance of the system. The importance order and contribution rates of the operating parameters and the optimal operating combinations are determined. Finally, in order to explore the influence mechanism of the parameters on the system performance, the influence of the parameters on the subsystems and the subsystems on the whole system is quantitatively analyzed. The results show that thermal storage temperature difference, waste heat temperature difference and cold source temperature are the most important parameters affecting the comprehensive performance of the whole system. Under the optimal operating conditions, round-trip efficiency, exergy efficiency, energy storage capacity (ESC), energy storage density (ESD) and levelized cost of storage (LCOS) are 47.05 %, 22.66 %, 1943 kW, 2.90 kWh/m3 and 0.38$/kWh, respectively. Compared to the ORC subsystem, the HP subsystem is more important to round-trip efficiency and exergy efficiency.

Evaluation and comparison for higher temperature performance index of emulsified asphalt mastic using coal gangue powder

In order to investigate the rheological behavior and the influence of solid waste coal gangue powder on the high-temperature performance of cold recycled Emulsified Asphalt Mastics (EAM), Dynamic Shear Rheometer (DSR) and Multiple Stress Creep Recovery (MSCR) tests were conducted using three different fillers and four powder-to-binder ratios of EAM. Evaluation indexes such as rutting factor (G*/sinδ), improved rutting factor (G*/1−1/sinδ∙tanδ), Unrecoverable Creep Compliance (Jnr), Cumulative Strain (CS) and Creep Recovery Ratio (R) were used to analyze the influence of filler type and dosage on high temperature of EAM, and the effectiveness of these indexes to evaluate high temperature is considered. Moreover, atomic force microscopy experiments were carried out to study on interaction mechanism between the fillers and emulsified asphalt. Finally, grey relational analysis method was used for quantitative assessment of these indexes for EAM. The results indicate that all three fillers effectively improve the high-temperature performance, with a larger improvement observed as the filler dosage increases, among which the tunneling coal gangue powder is the most significant. Under a stress level of 0.1 KPa, the coal gangue filler mastic appears the best deformation recovery ability, whereas under a stress level of 3.2 KPa, the cement filler mastics appears the best deformation recovery ability. The additional fillers significantly influence the nano-scale surface morphology of the residues, and the tunneling coal gangue powder appears a stronger adsorption capacity for free polar components compared to the cement and limestone mineral powder. It is suggested that the Jnr and CS can be used as evaluation indexes of high temperature evaluation index of EAM, instead of G*/1−1/sinδ∙tanδ or G*/sinδ or R.

A combined method for the evaluation of contributing factors to maritime dangerous goods transport accidents

This paper evaluates the contributing factors to maritime dangerous goods (DG) transport accidents by integrating the Entropy Weight (EW) and Grey Relational Analysis (GRA) methods. For this purpose, investigation reports of maritime DG transport accidents that occurred worldwide between 2000 and 2023 are derived from the International Maritime Organization’s Integrated Shipping Information System (IMO GISIS) database’s Marine Casualties and Incidents (MCI) module. Eleven main ship operations and thirteen primary causes were selected by analysing accident investigation reports. The weights of main ship operations are calculated utilizing the EW method. The correlational degrees of the primary causes are then calculated using the GRA method. Most maritime DG transport accidents occur during unberthing, bunkering, and pilotage operations. The most common contributing factors of maritime DG transport accidents are collisions and occupational accidents. Specifically, maritime DG transport accidents are most likely to be caused by collisions during sailing, passage, maneuvering, and bunkering operations, as well as occupational accidents during cargo loading, anchoring, berthing, and mooring operations. The results of this paper can support stakeholders in developing the needed policies to guarantee the safety of maritime DG transport.

How sustainable are agricultural practices in European Union countries? A spherical fuzzy logic based evaluation

ABSTRACT Climate change and population growth have heightened the need for a comprehensive framework to analyse the environmental impacts of agricultural practices. While traditional agricultural activities have detrimental environmental effects such as soil degradation, water pollution, and greenhouse gas emissions, sustainable agriculture is an innovative approach to minimizing humanity’s significant problems, such as depletion of natural resources, climate change, and biodiversity loss. In this study, a model is developed to evaluate the agri-environmental performance of countries. This model evaluates and ranks countries using the spherical fuzzy analytical hierarchy process and grey relational analysis methods within the European Union’s agri-environmental indicators framework. This study is among the pioneering studies to utilise the spherical fuzzy logic approach for determining the relative importance of agri-environmental performance criteria. The findings reveal that crucial factors such as the irrigable utilised agricultural area, the sales of pesticides per utilised agricultural area, and the share of main livestock types in total livestock units are critical to agri-environmental performance. In addition, in the implementation phase of the study, the performances of the European Union member countries are evaluated using the proposed model. This constitutes another contribution of the research. The results of this study indicate that Finland, Lithuania, and Sweden are the frontrunners in agri-environmental performance, while Italy, the Netherlands, and Malta rank lower. The model developed in this study has far-reaching implications for developing targeted environmental protection policies and advancing sustainable agricultural practices on a global scale.

In vivo and in vitro chemical composition and biological activity of traditional vs. dispensing granule decoctions of Coptidis Rhizoma: A comparative study.

Coptidis Rhizoma (CR) holds significant clinical importance. In this study, we conducted a comparative analysis of CR's dispensing granule decoction (DGD) and traditional decoction (TD) to establish a comprehensive evaluation method for the quality of DGD. We selected nine batches of DGD (three from each of manufacturers A, B and C) and 10 batches of decoction pieces for analysis. We determined the content of representative components using high-performance liquid chromatography and assessed the content of blood components in vivo post-administration using ultra-performance liquid chromatography-mass spectrometry. The antibacterial activity was measured using the drug-sensitive tablet method. To evaluate the overall consistency of DGD and TD, we employed the CRITIC method and Grey relational analysis method. Our CRITIC results indicated no significant difference between the CRITIC scores of DGD-B and TD, with DGD-B exhibiting the highest consistency and overall quality. However, DGD-A and DGD-C showed variations in CRITIC scores compared with TD. After equivalent correction, the quality of DGD-A and DGD-C approached that of TD. Furthermore, our Grey relational analysis results supported the findings of the CRITIC method. This study offers a novel approach to evaluate the consistency between DGD and TD, providing insights into improving the quality of DGD.

Research on the identification and detection technology of electricity theft in power distribution areas under a smart grid environment

Abstract With the extensive application of smart meters, power companies can access a wealth of customer electricity usage data, which has not yet been fully utilized. This paper proposes a substation area user identification and electricity theft detection method based on smart meter data, aiming to enhance the level of intelligent management of power grid enterprises and reduce operational costs. By using the grey relational analysis method, analyzing the measurement data collected by smart meters at different time points, it is possible to determine the substation area and phase to which the user belongs and to detect electricity theft behavior. Finally, through simulation, the effectiveness of the proposed method is verified.

Multi-objective optimization of Stinger PDC cutter breaking rock parameters under intrusion-cutting action using Taguchi-based gray relational analysis.

To enhance the efficiency of the Stinger Polycrystalline Diamond Compact (PDC) cutter in breaking hard rocks, this study focuses on optimizing the cutter intrusion-cutting rock breaking parameters. A numerical calculation model for the rotational breaking of granite by a Stinger PDC cutter was established. A comprehensive statistical examination was performed to assess the influence of various factors on intrusion ability (IA), tangential force (TF), and mechanical specific energy (MSE). The Taguchi method was used to determine the optimal settings for each factor, while analysis of variance was employed to assess the significance and relative impact of these factors on the target outcomes. In addition, the multi-objective function was optimized using the gray relational analysis method. The primary process parameters obtained for the various performance characteristics are the cone top angle (α), the cone top radius (r), the cutter diameter (d), the cutter back inclination angle (β), and weight on bit (P). The impact ratios of these parameters are 6.20%, 7.66%, 3.93%, 17.20%, and 65.02%, respectively. The optimal geometrical parameters are α = 60°, r = 2mm, and d = 15mm, while the optimal working parameters are β = 30° and P = 800 N. In the optimal case, IA and MSE were reduced by 55.335% and 15.809%, respectively, compared to the initial case. Despite a 15.706% increase in TF, the overall GRG increased for all three evaluation criteria, with an overall increase in efficiency of 18.229%. The results of this paper can provide guidance for the design of Stinger cutter PDC drill bits.

Research on the development relationship between safety production indicators and economic and social indicators in China

In order to study the relationship between China's safety production indicators and economic and social indicators, the development trend of indicator data in the past 20 years was statistically analyzed, and qualitative and quantitative research was conducted using grey relational analysis and multiple linear regression analysis methods. In the past two decades, there has been a significant improvement in the number of deaths, work-related injuries, and occupational patients in China's safety production, and the country's three categories of 14 economic and social indicators have achieved rapid development. Using the grey relation analysis method, the grey correlation degree between the number of deaths, work-related injuries, and occupational patients in China over the past twenty years and 14 economic and social indicators was obtained. The ranking of economic and social indicators that affect the number of deaths, work-related injuries, and occupational patients varies greatly. A multiple linear regression model was established for the number of deaths, work-related injuries, occupational diseases, and 14 economic and social indicators. The rationality of the model was verified from four aspects: R2, F-value, P-value, and deviation between actual and fitted values. Provide guidance for the development of safety production indicators and economic and social indicators in China through research.

Optimization of Agricultural Tractor Engine Hood Forming Quality Based on Neural Network Genetic Algorithm Function

To improve the forming quality of agricultural tractor engine hood and effectively solve the problems of wrinkling and cracking during the drawing forming process, DYNAFORM 5.9 finite element software was used for numerical simulation of the part. Based on a comprehensive scoring method of orthogonal experiments and grey relational analysis, the critical process parameters affecting the “maximum thickening rate” and “maximum thinning rate” were determined. Latin hypercube sampling was used to randomly sample the key process parameters, and the sampled samples served as the data basis for the optimization stage of the neural network genetic algorithm function; an optimization model of the neural network genetic algorithm function was established, with the key process parameters, and the “maximum thickening rate” and “maximum thinning rate” as inputs and outputs respectively, to construct a nonlinear mapping relationship and optimize the process parameters. The study showed that the blank holder force and die clearance had the greatest impact on the “maximum thickening rate” and “maximum thinning rate”, identifying them as key process parameters; the optimal process parameter combination was the blank holder force of 462.71 kN, the die clearance of 1.09 mm, and corresponding “maximum thickening rate” and “maximum thinning rate” of 3.97% and 25.96%, respectively. Overall, this research provides a practical optimization strategy to solve the quality issues of the engine hood, offering a theoretical basis for its actual production and processing with significant practical application value.

An experimental investigation on copper square electrode wear in electric discharge machining of Hastelloy B2

Hastelloy B2 is a high-performance nickel-molybdenum alloy and has been used in micro reactor, pump, pipe, and corrosion-resistant equipment. Square holes are required in the above application components. Although square holes are easily produced by spending more electrodes wear in Electrical Discharge Machining (EDM). Moreover, the square hole with small electrode wear achieved is a challenging task in thermal machining. Hence, in this work, the effects of EDM process parameters on electrode taper angle, electrode radius, electrode wear length and cutting time of Hastelloy B2 are studied. Taguchi based VišekriterijumskoKompromisnoRangiranje (VIKOR) method is used to find the optimum process parameters and compared with Taguchi based Grey Relational Analysis (GRA) method for validation. The results showed that current and pulse duration greatly affects the electrode wear out surface and edges. The square electrodes with sharp edges and surfaces are fully transformed into hemispherical shapes at electrode ends due to an unstable spark with diffusion of heat. Also, the VIKOR method provides an alternative multi-criteria optimization method that enhances the process performance over the grey relational analysis due to comparability, uniqueness, assessment and prediction.

Physical Properties of High-Rank Coal Reservoirs and the Impact on Coalbed Methane Production

The physical characteristics of coal reservoirs are important factors affecting the occurrence status of coalbed methane, as well as key factors restricting the production capacity. Therefore, taking 3# coal in Qinnan region of China as the research object, based on the actual production data of 200 coalbed methane wells in the research area, experimental testing combined with simulation analysis was used to explore the physical properties of medium and high-order reservoirs and their impact on the occurrence and production of coalbed methane. The characteristics of coalbed methane reservoir formation and production capacity changes in the research area were revealed, and the factors restricting the production capacity of coalbed methane wells were calculated using the gray correlation analysis method. The results indicate that the micropores in the coal reservoir in the study area are well-developed, while the macropores and mesopores (exogenous fractures) are underdeveloped, the surface of the micropores is complex, and the connectivity of the micropores is poor, resulting in reservoirs with high gas adsorption characteristics and low permeability. The fractal characteristics of pores and fractures can reflect the permeability characteristics of reservoirs. Permeability is positively correlated with macropores (exogenous fractures) and mesopores, and negatively correlated with micropores. There is a positive correlation between permeability and productivity, and the reservoir in the study area has a stress-sensitive boundary. The main factors restricting productivity under the complex pore and fracture system of high-rank coal reservoir were identified, and the gray relational analysis method was used to evaluate the development effect of the research area. This study provides guidance for the development of coalbed methane production in high-rank coal reservoirs.

Comprehensive quality evaluation of Lysimachia christinae Hance via fingerprint, spectrum-effect relationship, and quantitative analyses of multiple components by single marker.

Lysimachia christinae Hance (LCH) is a traditional medicine used to treat gallstone disease and cholecystitis. Despite its known anti-inflammatory and choleretic effects, its quality has not been extensively evaluated. In this study, we aimed to establish a reliable quality evaluation method for LCH via fingerprint, spectrum-effect relationship, and quantitative analyses of multicomponents by a single marker (QAMS). First, the fingerprints and anti-inflammatory and choleretic activities of 14 LCH batches were determined. Then, the gray relation analysis method was used to analyze the peak areas of the fingerprint profile and pharmacodynamic data. Subsequently, the characteristic peaks were tentatively identified using high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Finally, rutin was selected as the internal reference material, and QAMS was used to analyze the LCH components. Pharmacodynamic experiments confirmed that LCH exerted anti-inflammatory and choleretic effects. Moreover, 15 flavonoids related to the anti-inflammatory and choleretic effects of LCH were identified. Notably, relative error percentage between the QAMS and external standard method was less than 5%. This study successfully established a comprehensive evaluation method for the qualitative and quantitative analyses of LCH.

An Overview of Qualitative Comparative Analysis Using GRA Methodology

Comparative Analysis, Introduction: Comparative analysis involves contrasting objects against one another to identify their differences and similarities. A corporation can better comprehend an issue and develop solutions in response by performing a comparative analysis while analyzing an idea, problem, theory, or question. You will be required to write comparison and contrast essays throughout your academic career. These essays can compare and contrast two works, two ideologies, two historical people, two scientific methods, etc. Two similar things may have crucial differences (2 different pesticides of different impacts on the environment), or two similar things may have crucial differences but turn out to have surprising similarities in "classic" compare-and-contrast papers where you weight A and B equally. Research significance: Comparative analysis examines two or more things, individuals, acts, occasions, etc. You can comprehend the topic better by pointing out the parallels and contrasts between these. You might use a character analysis from a book, a movie, a main character from history, etc. You can also include nations, states, international organizations, businesses, calamities naturally occurring, ideologies and faiths, as well as commercial marketing and many other things. Before writing your own, you might find it beneficial to read some constant comparative sample essays. Comparative analysis essays can be formatted in a variety of ways. A quality or attribute may be combined in separate blocks. Each paragraph could discuss the traits' similarities and contrasts. Methology: Deng originally suggested Grey Relational Analysis (GRA), a tool for MCDM problems. It has been used successfully to address many MCDM challenges. The GRA is a model for evaluating effects that can evaluate the relationship between successions and fit with certain information investigation techniques or calculation strategies. Alternative: Japan, South Korea, and Delhi, Taiwan. Evaluation Preference: 1965, 1970, 1975, 1980, 1984. Result: from the result it is seen that 1980 and is got the first rank whereas is the 1975 got is having the lowest rank. Conclusion: The value of the dataset for Comparative Analysis in GRA (Gray-related analysis) method shows that it results in 1980 and top ranking.

The Nearshore Marine of ShenZhen Environmental Risk Assessment Method Based on the DPSIR Framework

The nearshore marine areas are the most intensely concentrated regions for human economic activities and serve as vital carriers for the development of the marine economy. Accurately assessing the environmental risks in these areas is of significant importance for the sustainable development of the marine economy. This study constructs an environmental risk assessment system for the nearshore marine areas of Shenzhen City based on the DPSIR framework and evaluates it using the comprehensive index method. Specifically, the study begins by selecting 27 indicators related to the marine environment to construct the evaluation index system. It employs the grey relational analysis and entropy weight method to weight the indicators and finally assesses the environmental risks of Shenzhen's nearshore marine areas from 2013 to 2020 using the comprehensive index method. The study finds that the environmental risks of Shenzhen's nearshore marine areas from 2013 to 2020 are generally low, with the risk score increasing from 0.3277 to 0.7308 year by year, shifting from a more dangerous to a safe risk level. The research indicates that the marine environment of the nearshore areas in Shenzhen is greatly influenced by local human economic activities and the industrial structure of Shenzhen. The study suggests that the environmental safety level of Shenzhen's nearshore marine areas could be improved by leveraging policy guidance, optimizing the industrial structure, and perfecting tourism management methods.

Development of high-strength geopolymer mortar based on fly ash-slag: Correlational analysis of microstructural and mechanical properties and environmental assessment

Given the insufficient mechanical performance of existing fly ash-based geopolymer mortars under ambient curing conditions, this study is dedicated to developing a high-strength geopolymer mortar that meets the requirements of modern structural engineering. Based on the rheological performance tests of the fresh geopolymer mortar, the evolution of its rheological characteristics was revealed. Through macroscopic mechanical performance tests, the influence of slag content on the compressive and flexural strength of geopolymer mortar was clarified. Employing microstructural performance testing methods such as Thermogravimetric and Mercury Intrusion Porosimetry, the micro-mechanisms behind the improvement of mechanical properties were revealed. Utilizing the grey relational analysis method, a framework was established to analyze the correlation between the microstructural and macroscopic mechanical properties of geopolymer mortar. Additionally, an assessment system for evaluating environmental and economic benefits was developed using statistical analysis methods. The results show that increasing slag content enhances the yield stress and plastic viscosity of geopolymer mortar. Optimizing slag content boosts the compressive strength of fly ash-based geopolymer mortar, reaching up to 88.13 MPa under ambient curing conditions. An optimal amount of slag also promotes gel formation during polymerization, improving the internal pore structure. Furthermore, the content of reaction products correlates more strongly with macroscopic mechanical properties than pore structure characteristics. Geopolymer mortar also presents significant environmental and economic advantages over traditional cement-based materials, with its carbon and economic intensity indices at only 5.50 % and 10.80 %, respectively, of those in cement-based materials.