AHP Model Research Articles

Assessing groundwater potential zones in Sundargarh district: a comparative study using AHP and FR models

Assessing groundwater potential zones in Sundargarh district: a comparative study using AHP and FR models

An integrated Delphi and Fuzzy AHP model for contractor selection: a case of Addis Ababa Design and Construction Works Bureau

An integrated Delphi and Fuzzy AHP model for contractor selection: a case of Addis Ababa Design and Construction Works Bureau

Research of Green GDP Evaluation System Based on AHP Model

GDP (Gross domestic product) is of extraordinary significance in measuring national economic development, while it tends to have inaccuracy. The concept of Green GDP (hereinafter referred to as GGDP), which introduces environmental factors into the accounting system, is more conducive to sustainable development and the building of a harmonious economy. This paper selects main factors and establish a GGDP evaluation index system using the AHP model, then conducts the robustness test by one-dimensional linear regression model and "children dropping out of school" model. Finally, a sensitivity analysis is carried out to prove the accuracy. The results indicate that GGDP system contributes to improving environmental conditions and promoting sustainable development.

Numerical comprehensive optimization and evaluation on ballistic behavior of ceramic/FRP composites based on AHP model

Numerical comprehensive optimization and evaluation on ballistic behavior of ceramic/FRP composites based on AHP model

Assessment of gully erosion susceptibility using four data-driven models AHP, FR, RF and XGBoosting machine learning algorithms

Gully erosion is a significant global threat to socioeconomic and environmental sustainability, making it a widespread natural hazard. Developing spatial models for gully erosion is crucial for local governance to effectively implement mitigation measures and promote regional development. This study applied two machine learning (ML) models, RF and XGB, alongside an AHP-based multi-criteria decision method and FR bivariate statistics, to assess gully erosion susceptibility (GES) in the Kangsabati River basin in eastern India's Chotonagpur plateau fringe. A GIS database was created, incorporating recorded gully erosion incidents and 20 conditioning variables, which were evaluated for multicollinearity. These variables served as predictive factors for assessing gully erosion presence in the study area. The models' performance was evaluated using metrics such as RMSE, MAE, specificity, sensitivity, and accuracy. The XGB model outperformed the others, achieving a predictive accuracy of 90.22%. The study found that approximately 6.56% of the Kangsabati catchment is highly susceptible to gully erosion, with 12.39% moderately susceptible and 81.05% not susceptible. The XGB model had the highest ROC value of 85.5 during testing, indicating its superiority over the FR (ROC ​= ​81.7), AHP (ROC ​= ​79.8), and RF (ROC ​= ​83.8) models. These findings highlight the XGB model's efficacy and potential for large-scale GES mapping.

Study on the variation regularities of minimum explosion concentration of moist magnesium dust/derived hydrogen hybrids under multiple working conditions

Magnesium is widely used but often accompanied by frequent magnesium powder explosion accidents. If the variation regularity and mechanism of the minimum explosion concentration (cm) of magnesium powder under the multi-factor coupling effect can be understood, the occurrence of magnesium powder explosion accidents can be fundamentally avoided, and intrinsic safety can be achieved. In this paper, experiments were conducted using a self-made 20 L explosion device to explore the effects of particle size, initial temperature, and equilibrium relative humidity (ERH) coupling on the cm of magnesium powder. The study found that an increase in ERH of moist magnesium powder would lead to easier agglomeration of the dust, making it less prone to activation. Additionally, excessive moisture also absorbed more heat, reducing the ignition sensitivity of the dust cloud and resulting in a continuous increase in cm. However, increasing the initial temperature and decreasing the dust particle size both decreased the cm of moist magnesium powder, weakening the effect of ERH on cm. Furthermore, using the analysis methods of orthogonal experimental range and AHP model, it was determined that the influence weights of the factors coupling effects on the cm of magnesium powder, from highest to lowest weight, were: particle size > ERH > initial temperature.Furthermore, in order to deeper understand the mechanism of the action process that affect the cm of moist magnesium powder, additional experiments were conducted to further confirm that the addition of hydrogen derived from the erosion reaction of moist magnesium powder to the explosion system can reduce the cm of magnesium dust clouds. Moreover, a quantitative mathematical model for predicting the cm of magnesium powder/hydrogen two-phase system was also established.

Geospatial assessment of ecological vulnerability of fragile Eastern Duars Forest integrating GIS-based AHP, CRITIC and AHP-TOPSIS models

Assessment of the ecological vulnerability of regional forests is extremely vital for easing the struggle for forest conservation. Therefore, the present study aims to delve into the ecological vulnerability of the Eastern Duars forest in the Indian sub-Himalayan region. The study employs three cutting-edge multi-criteria decision-making methods, including AHP, CRITIC, and AHP-TOPSIS methods, in which geo-environmental (elevation, slope, soil texture), hydro-meteorological (precipitation, temperature, waterbodies), vegetation index and anthropogenic (land use land cover, road, settlement) criteria are integrated, to assess ecological vulnerability. The vulnerability maps indicate that very high vulnerable areas comprise 0.05%, 0.01%, 23.96%, high vulnerable 19.72%, 17.51%, 41.52%, moderate vulnerable 63.45%, 49.66%, 29.49%, low vulnerable 16.70%, 30.82%, 4.10% and very low vulnerable 0.08%, 2.02%, 0.92% of area as per AHP, CRITIC, and AHP-TOPSIS method respectively. The highly vulnerable region is found in human-modified areas, where anthropogenic activities disrupt the natural ecological process, and deforestation is evident. Hence, careful strategic policies should be enforced regarding the restriction of anthropogenic activities, human habitation expansion, and changing climate to sustain the fragile Duars forest ecosystem. The inclusion of objective and hybrid criteria weighting methods, along with predominant knowledge-driven subjective weighting method, will promote the practice of comprehensive ecological vulnerability assessment.

Health assessment of TBM diversion tunnel structure based on AHP and AMV models

Health assessment is one of the important theoretical bases for deciding whether the diversion tunnel can operate safely and stably. A project of the TBM diversion tunnel is taken as the research object to ensure the normal operation of the diversion tunnel. Based on measured data and considering multiple safety aspects such as structural response, durability, and external factors of the diversion tunnel, a TBM diversion tunnel structural health evaluation index system is established. A new method for the TBM diversion tunnel structural health comprehensive evaluation based on Analytic Hierarchy Process-Matter Element Extension-Variable Weight Theory (AMV) is proposed to explore the impact of AMV fluctuation with the measured results of the indicators on the weight, closeness, and health grade of each evaluation index. The high sensitivity and high-risk evaluation indicators for the structural health of the diversion tunnels are identified. It is found that the variable weight varies with the changes in various indicator values, which can accurately evaluate the health status of tunnels in real-time. The characteristic values of the tunnel grade calculated by the AHP and the AMV are 1.589 and 1.695, respectively. The results of the corresponding interval diversion tunnel are the basic safety state of grade B. Except for the two evaluation indicators of concrete strength and slurry properties, the variable weight values and grade characteristic values of other evaluation indicators increase with the increase of indicator values. The four indicators of segment settlement, segment opening, segment misalignment, and segment cracks are more sensitive to the health of the TBM diversion tunnel. This AMV can accurately evaluate the health status of the diversion tunnel structure. The research results can provide references for later maintenance work and similar projects.

Knowledge-Driven Fuzzy AHP Model for Orogenic Gold Prospecting in a Typical Schist Belt Environment: A Mineral System Approach

Knowledge-Driven Fuzzy AHP Model for Orogenic Gold Prospecting in a Typical Schist Belt Environment: A Mineral System Approach

Ecological Suitability Analysis for Beekeeping Using GIS and AHP Model in Gedeo Zone of Southern Ethiopia

Ecological Suitability Analysis for Beekeeping Using GIS and AHP Model in Gedeo Zone of Southern Ethiopia

Forecasting and advancing water carrying capacity in Henan Province in China: Application of ‘four determinations with water’ in AHP and SD modeling

Water resources carrying capacity (WRCC) is indispensable for sustainable development, acting as a crucial determinant for harmonizing ecological preservation with socio-economic advancement. This research delineates an advanced evaluation index system for WRCC, focusing on Henan Province, China, a region straddling the Yangtze, Huaihe, Yellow, and Haihe river basins. Leveraging the analytic hierarchy process (AHP) with a system dynamics (SD) model, our analysis dissects the nonlinear interplays among demographic expansion, economic activities, land use patterns, water resources, and water environment. We introduce a novel integration of the “Four Determinations with Water” principle with sustainable development tenets, thereby sculpting six exploratory scenarios that chart Henan's potential paths from 2022 to 2035. Through these scenarios, we forecast and scrutinize the evolution of population dynamics, GDP, water supply, and sewage discharge volumes, employing rigorous quantitative analyses for a holistic evaluation. The results show that: WRCC in Henan Province becomes larger gradually, and, in Scenario 6, the WRCC indicator is the largest (0.643 in 2035) and the prediction effect is the best, while in Scenario 1, the WRCC indicator is the smallest (0.472 in 2035) and the prediction effect is the worst. Based on the prediction results, suggestions were made to adjust the industrial structure and strengthen the awareness of water conservation to improve the regional water resources carrying capacity.

An assessment framework for underground construction methods in the pre-construction stage: a technical perspective

The selection of an appropriate underground construction method plays a crucial role during the pre-construction phase as it must consider various aspects, such as safety, technical feasibility, and cost-effectiveness. However, there is still a lack of technical assessments for selecting suitable underground construction methods in the research field. Therefore, this study aims to build an assessment model to technically assess such methods in the pre-construction stage. Firstly, technical assessment factors were obtained from literature reviews, expert consultations and survey results. Factor analysis was performed to reveal the underlying significance of each factor. The Fuzzy Analytic Hierarchy Process (Fuzzy AHP) model was then constructed to assess the relative importance of each factor. Finally, the assessment model was validated by seeking experts’ opinions on its performance in a practical project. The study resulted in a Fuzzy AHP model established from a list of 8 groups of factors with 35 refined factors, covering many aspects from documents and resources to geology and hydrology. The validation results demonstrated the model’s effectiveness in assisting contractors to make informed decisions. This study has contributed to construction literature by introducing a novel framework for underground construction methods, offering a practical tool for pre-construction planning and decision-making.

Novel Multi-Criteria Group Decision Making Method for Production Scheduling Based on Group AHP and Cloud Model Enhanced TOPSIS

Optimized production scheduling can greatly improve efficiency and reduce waste in the steel manufacturing industry. With the increasing demands on the economy, the environment, and society, more and more factors need to be considered in the production scheduling process. Currently, only a few methods are developed for the comprehensive evaluation and prioritization of scheduling schemes. This paper proposes a novel MCGDM (multi-criteria group decision making) method for the ranking and selection of production scheduling schemes. First, a novel indicator system involving both qualitative and quantitative indicators is put forward. Diverse statistical methods and evaluation functions are proposed for the evaluation of quantitative indicators. The evaluation method of qualitative indicators is proposed based on heterogeneous data, cloud model theory, and group decision-making techniques. Then, a novel Group AHP model is proposed to determine the weights of all evaluation indicators. Finally, a novel cloud-model-enhanced TOPSIS (technique for order of preference by similarity to ideal solution) method is proposed to rank alternative production scheduling schemes. A practical example is presented to show the implementation details and demonstrate the feasibility of our proposed method. The results and comparative analysis indicate that our hybrid MCGDM method is more reasonable, flexible, practical, and effective in evaluating and ranking production scheduling schemes in an uncertain environment.

Retracted: Construction and Index Analysis of Whole Chain Linkage Talent Training System Based on Fuzzy AHP Model

Retracted: Construction and Index Analysis of Whole Chain Linkage Talent Training System Based on Fuzzy AHP Model

Analysis of English Teaching Quality Evaluation in Colleges and Universities Based on AHP Modeling

Abstract English in colleges and universities is an important subject for learning, so it is especially important to evaluate and analyze the quality of teaching English in colleges and universities. This paper constructs the evaluation system of college English teaching quality based on the AHP model, builds the three-level index model of college English teaching quality by combining the relative importance level of Sta, and then carries out the normalization process to determine the importance degree of the indexes at all levels. Combined with factor analysis and data analysis of the results of the expert consultation on the indicator model to measure the factors affecting the quality of teaching in colleges and universities for the overall evaluation and analysis. From the validation data, it can be seen that there are 24 correlation coefficients above 0.5 and 12 above 0.8 in the model influence factor testing. The standardized factor loadings of each potential variable are all greater than 0.75, and the average variance extractions are all greater than 0.65, effectively verifying the internal consistency and convergent validity of the indicator model. In the validation data of the teaching evaluation system, the individual scores of the three-level indicators are all greater than 90, indicating the effectiveness and appropriateness of the teaching evaluation system. The construction of an English teaching quality evaluation system in colleges and universities is conducive to the improvement of teaching management and a more precise grasp of the improvement of teaching quality.

Quantitative Analysis and Modeling of Student Innovation Capability in Higher Education Management in an Innovative and Entrepreneurial Environment

Abstract Colleges and universities often focus on cultivating talent, a practice that directly contributes to the lack of creativity among their students. In light of this, this paper aims to promote education reform and enhance students’ capacity for innovation. This paper constructs the evaluation index system and model of innovation ability of students in colleges and universities to promote the cultivation of innovative talents. Based on the AHP model to determine the index weight of each evaluation factor, with the help of gray correlation to analyze the relationship of each evaluation index, the decision matrix is established, and the gray comprehensive judgment model is constructed. We establish the evaluation sample matrix by using the whitened weight function to determine the evaluation gray class. We then calculate the gray evaluation coefficients, weight vectors, and weight matrices to arrive at a comprehensive evaluation of innovative ability. This paper employs the Hebei University of Technology in China as its research site and applies its methodology to evaluate the innovation capacity of its students. The comprehensive evaluation value of the students’ innovative abilities is only 6.67, placing them at the medium level. The maximum relative error between the evaluation mean value of each specific index at the index level and the expert evaluation result is 1.84%. In terms of the satisfaction of the evaluation method, the satisfaction mean value of this paper’s method exceeds that of the expert evaluation method in the dimensions of the evaluation concept, the evaluation subject, the evaluation method, the evaluation indexes, the evaluation procedure, and the application of the evaluation result, which are respectively 0.14, 1.25, 1.43, 0.7, 1.45, and 0.49.

Correction: Low-income housing location based on affordable criteria Using AHP Model and GIS Technique (Case Study: Babolsar City)

Correction: Low-income housing location based on affordable criteria Using AHP Model and GIS Technique (Case Study: Babolsar City)

Flood hazard mapping using GIS-based statistical model in vulnerable riparian regions of sub-tropical environment

Floods are a recurrent natural calamity that presents substantial hazards to human lives and infrastructure. The study indicates that a significant proportion of the study area, specifically 27.05%, is classified as a moderate flood risk zone (FRZ), while 20.78% is designated as high or very high FRZ. The region’s low and very low FRZ are classified at 52.17%. The GIS-based AHP model demonstrated exceptional predictive precision, achieving a score of 0.749 (74.90%) as determined by the AUC-ROC, a widely used statistical evaluation tool. The current study has identified areas with high FRZ in the affected CD blocks, which are situated in low-lying flood plains, regions with gentle slopes, high drainage density, high TWI, low NDVI, high MNDWI, areas with high population density, intensive agricultural land. The findings of this research offer significant perspectives for decision-makers, city planners, and emergency management agencies in devising efficient measures to mitigate flood risks.

Comparative Studies of Subsurface Layers’ Competence Evaluation using TOPSIS and AHP Models at Ilaramokin, Southwestern Nigeria

Comparative Studies of Subsurface Layers’ Competence Evaluation using TOPSIS and AHP Models at Ilaramokin, Southwestern Nigeria

Groundwater Availability and Suitability Evaluation for Irrigated Agriculture in Mbale District

The purpose of this study was to evaluate the availability and suitability of groundwater in Mbale district basing on potential, quality and vulnerability to support irrigated agriculture. Groundwater potential was assessed using geospatial technique through AHP model. Thematic layers were prepared namely: land use and land cover, slope, soil, rainfall, lineament density, lithology, geomorphology and drainage density. All layers were integrated using the MLC technique. Ranking of each parameter was performed using WOIA. Weights were assigned to each subject class basing on AHP results. The consistency of the outputs was tested by computation of CR and was at a reasonable acceptable level (0.029 < 0.1). Groundwater potential was delineated basing on the values of groundwater potential index. Groundwater quality was determined using IWQI method. Thirty-three water samples were collected. Five chemical parameters were tested in the laboratory: chloride, electrical conductivity, bicarbonate, sodium and SAR to generate the water quality database using Kriging interpolation technique. Computation of IWQI values for each source was made and was used to generate the IWQI map using the weighted summation. DRATIC method was used to delineate vulnerability of groundwater. Layers were generated using the following parameters: depth to groundwater, net recharge, aquifer media, topography, vadose zone impacts, and hydraulic conductivity. The aquifer vulnerability map was prepared by overlaying layers. Three different vulnerability zones were determined according to DRASTIC scores low (<100), medium (100-140) and high (>140). Integration of maps of quality, vulnerability and potential of groundwater was made using an unsupervised MLC classification method. Groundwater potential was in three zones: very good zone was 26.99 km2 (12.98%), the good zone was 126.22 km2 (60.71%) and the poor zone was 54.69 km2 (26.31%). The average annual exploitable groundwater reserves are estimated at 0.026 (MCM/km2) in the zone of “very good”, 0.024 MCM/km2 in the zone of “good” and 0.018 MCM/km2 in the zone of “poor”. Groundwater quality was in two use restrictions: High Restriction of 90.90% with the IWQI value from 40 to 55 on the area of 188.98 km2 of the study area and Severe Restriction of 9.10% with IWQI values from 32 to 40 covering of 18.92 km2. The study area had a high probability of contamination. Low vulnerability covers an area of 11.23km2 (5.40%), 77.83km2 (37.44%) for medium and 118.83km2 (57.16%) for high. The resulting clustered map was classified into five categories with their respective regions: 17.58% very poor (36.56km2), 13.84% poor (28.77km2), 12.69% good (26.39km2), 31.46% very good (65.39km2) and 24.43 % excellent (50.78km2). The sub counties in Mbale district that have inadequate and unsuitable groundwater for irrigated agriculture are Budwale, Wanale, Busano, Bubyangu, Bufumbo and Nyondo since they belong to the zones of very poor and poor. The remaining sub counties have available and suitable groundwater for irrigated agriculture since they belong to the zones of good, very good and excellent.