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Rock Mass Quality Rating Based on the Multi-Criteria Grey Metric Space

Computer Modeling in Engineering & Sciences 2024年第9期140卷 2635-2664页

作者： miloš gligoric Zoran gligoric Saša Jovanovic Suzana Lutovac Dragan Pamucar Ivan Jankovic Faculty of Mining and Geology University of BelgradeBelgrade11000Serbia Faculty of Technical Sciences University of PrištinaKosovska Mitrovica38220Serbia Department of Operations Research and Statistics Faculty of Organizational SciencesUniversity of BelgradeBelgrade11000Serbia College of Engineering Yuan Ze UniversityTaoyuan City320315TaiwanChina

Assessment of rock mass quality significantly impacts the design and construction of underground and open-pit mines from the point of stability and *** study develops the novel Gromov-Hausdorff distance for rock quality(GHDQR)methodology for rock mass quality rating based on multi-criteria grey metric *** usually presents the quality of surrounding rock by classes(metric spaces)with specified properties and adequate interval-grey *** the distance between surrounding rock sample characteristics and existing classes represents the core of this *** Gromov-Hausdorff distance is an especially useful discriminant function,i.e.,a classifier to calculate these distances,and assess the quality of the surrounding *** efficiency of the developed methodology is analyzed using the Mean Absolute Percentage Error(MAPE)*** existing methods,such as the Gaussian cloud method,Discriminant method,Mutation series method,Artificial neural network(ANN),Support vector machine(SVM),Grey wolf optimizer and Support vector classification method(GWO-SVC)and Rock mass rating method(RMR)are used for comparison with the proposed GHDQR *** share of the highly accurate category of 85.71%clearly indicates compliance with actual values obtained by the compared *** results of comparisons showed that the model enables objective,efficient,and reliable assessment of rock mass quality.

关键词： Rock mass rating multi-criteria class metric space interval-grey numbers

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Assessing Criteria Weights by the Symmetry Point of Criterion (Novel SPC Method)–Application in the Efficiency Evaluation of the Mineral Deposit Multi-Criteria Partitioning Algorithm

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Computer Modeling in Engineering & Sciences 2023年第7期136卷 955-979页

作者： Zoran gligoric milos gligoric Igor Miljanovic Suzana Lutovac Aleksandar Milutinovic Faculty of Mining and Geology University of BelgradeBelgrade11000Serbia

Information about the relative importance of each criterion or theweights of criteria can have a significant influence on the ultimate rank of ***,assessing the weights of criteria is a very important task in solving multi-criteria decision-making *** methods are commonly used for assessing the weights of criteria:objective,subjective,and integrated *** this study,an objective approach is proposed to assess the weights of criteria,called SPCmethod(Symmetry Point of Criterion).This point enriches the criterion so that it is balanced and easy to implement in the process of the evaluation of its influence on *** SPC methodology is systematically presented and supported by detailed calculations related to an artificial *** validate the developed method,we used our numerical example and calculated the weights of criteria by CRITIC,Entropy,Standard Deviation and MEREC *** analysis between these methods and the SPC method reveals that the developedmethod is a very reliable objective way to determine the weights of ***,in this study,we proposed the application of SPCmethod to evaluate the efficiency of themulti-criteria partitioning *** main idea of the evaluation is based on the following fact:the greater the uniformity of the weights of criteria,the higher the efficiency of the partitioning *** research demonstrates that the SPC method can be applied to solving different multi-criteria problems.

关键词： Multi-criteria decision-making weights of criteria symmetry point of criterion mineral deposit partitioning algorithm performance evaluation

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