Application of Fuzzy Analytic Hierarchy Process to Underground Mining Method Selection

Bajić, Sanja; Bajić, Dragoljub; Gluščević, Branko; Vakanjac, Vesna Ristić

doi:10.3390/sym12020192

Cited by 22 publications

(12 citation statements)

References 33 publications

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“…Finally, the number of hidden dangers on the one hand is affected by the development law of the hidden danger itself, on the other hand, it is also affected by other external factors, such as the change of geological conditions, the transformation of coal mining technology [38][39][40], etc. The model adopted in this paper belongs to the scope of the time series prediction model.…”

Section: Discussionmentioning

confidence: 99%

Predicting Hidden Danger Quantity in Coal Mines Based on Gray Neural Network

Zhao

et al. 2020

Symmetry

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The hidden danger is the direct cause of coal mine accidents, and the number of hidden dangers in a certain area not only reflects the current safety situation, but also determines the development trend of safety production in this area to a large extent. By analyzing the formation and development law of the hidden dangers and hidden danger accident-induced mechanism in coal mines, it is concluded that there are some objective laws in the process of occurrence, development, weakening, and even stabilization of hidden dangers in a certain area. The development of the number of hidden dangers for a coal mine generally presents the law of similar normal distribution curve, with a certain degree of partial symmetry. Many years of hidden danger elimination in coal mines will accumulate large-scale hidden danger data. In this paper, by using the average value of hidden danger quantity in consecutive months to weaken the oscillation of hidden danger quantity sequence, and combining with gray model (1,1) and the neural network of extreme learning machine, and employing big data of hidden dangers available, a hidden danger quantity prediction model based on the gray neural network was established, and the experimental analysis and verification carried out. The results show that the model can achieve good prediction effect on the number of hidden dangers in a coal mine, which not only reflects the complex gray system behavior of hidden dangers of a coal mine, but also can predict dynamically. The safety management efficiency and emergency capacity of the coal mine enterprise will be greatly improved.

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Section: Discussionmentioning

confidence: 99%

Predicting Hidden Danger Quantity in Coal Mines Based on Gray Neural Network

Zhao

et al. 2020

Symmetry

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“…This methodology emerges as a combination of the traditional AHP (Saaty, 1980) with the fuzzy sets theory (Zadeh, 1965). The use of FAHP highlighted the quality of this technique based on expert judgment (Bajic et al , 2020), being able to include the associated uncertainty in decision-making, enabling to improve the consistency and flexibility of the results (Van Laarhoven and Pedrycz, 1983).…”

Section: Methodsmentioning

confidence: 99%

“…The use of fuzzy values is more attractive, easier to use and more assimilable to real life than numerical ones (Ishizaka and Labib, 2011). Table 1 shows the fuzzified Satty's nine-scale for triangular fuzzy number (Bajic et al , 2020; Kim et al , 2020).…”

Section: Methodsmentioning

confidence: 99%

Exploration of employability perceptions with blended multi-criteria decision-making methods

Castro-López

Monteiro

Bernardo

et al. 2021

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PurposeThe purpose of this paper is to explore employment perception of students as a relevant indicator of higher education quality, using blended multi-criteria decision-making methods.Design/methodology/approachThe differential impact of these variables was analyzed in this paper taking a sample of 641 students and six higher education lecturers identified as experts on young vocational careers. The traditional study of student behavior and perceptions of employability does not incorporate the uncertainty associated with multi-criteria decision processes and is therefore less adapted to the human reasoning process. This research applies traditional techniques together with fuzzy techniques capable of managing more effectively the uncertainty associated with student actions and behaviors.FindingsThis research shows that it is important to consider previous work experience, academic achievement and soft skills developed during education experiences. In this way, this research shows the lecturers how to adapt their pedagogical practices according to students' perceptions of employability and assess their students' perceptions of employability. In addition, lecturers will be able to incorporate the uncertainty associated with decision-making processes to optimize employability perception.Originality/valueHigher education-related research on uncertainty environments as multi-criteria decision problems is still in early stages. The incorporation of the uncertainty associated with decision-making processes to this field allows to optimize employability perception thanks to its adaptation to real human behavior in the adoption of decisions.

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“…e relationship between culture and design is closely linked [17]. Starting from cultural space and cultural time, let the form design of the environmental protection gold furnace achieve reasonable integration, and improve the cultural recognition and identity of the environmental protection gold furnace form.…”

Section: Cultural Space and Cultural Timementioning

confidence: 99%

Application of Factor Analysis in Image Modeling Design of Environmental Protection Gold Stove

Zhou

2022

Mathematical Problems in Engineering

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In order to design an environmentally friendly gold furnace that considers both traditional cultural elements and modern decorative elements, this paper puts forward the application of factor analysis in the image modeling design of an environmentally friendly gold furnace. Firstly, the elements of lines, colors, and patterns were extracted by factor analysis. By using the hierarchical structure model and factor analysis, the synchronous parameter fusion model of image modeling design factors of the environmental protection gold furnace is constructed to fuse the output reliability parameters of image modeling of the environmental protection gold furnace and adjust them adaptively. The factor analysis and process control of image modeling of environmental protection golden stoves are carried out using the method of differential feature analysis. Then, the Atlas and image Kanban are analyzed, and the image design factors of the environmental protection golden stove are excavated. Finally, the concepts of cultural space and cultural time are introduced. Based on the study of historical and material materials, the overall comparative analysis is carried out from three aspects: shape, color, and pattern. Combined with the extracted target image and the excavated design factors, the image modeling design of the environmental protection gold furnace is effectively carried out, providing design methods and sample references for the innovative design of the environmental protection gold furnace. The experimental results show that the mining design factors can effectively analyze the problems existing in the modeling design of the current environmental protection gold furnace, with a low bit error rate and strong practicability.

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Application of Fuzzy Analytic Hierarchy Process to Underground Mining Method Selection

Cited by 22 publications

References 33 publications

Predicting Hidden Danger Quantity in Coal Mines Based on Gray Neural Network

Predicting Hidden Danger Quantity in Coal Mines Based on Gray Neural Network

Exploration of employability perceptions with blended multi-criteria decision-making methods

Application of Factor Analysis in Image Modeling Design of Environmental Protection Gold Stove

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