LAPSE:2018.0407
Published Article
LAPSE:2018.0407
Underground Risk Index Assessment and Prediction Using a Simplified Hierarchical Fuzzy Logic Model and Kalman Filter
Muhammad Fayaz, Israr Ullah, Do-Hyeun Kim
August 28, 2018
Normally, most of the accidents that occur in underground facilities are not instantaneous; rather, hazards build up gradually behind the scenes and are invisible due to the inherent structure of these facilities. An efficient inference system is highly desirable to monitor these facilities to avoid such accidents beforehand. A fuzzy inference system is a significant risk assessment method, but there are three critical challenges associated with fuzzy inference-based systems, i.e., rules determination, membership functions (MFs) distribution determination, and rules reduction to deal with the problem of dimensionality. In this paper, a simplified hierarchical fuzzy logic (SHFL) model has been suggested to assess underground risk while addressing the associated challenges. For rule determination, two new rule-designing and determination methods are introduced, namely average rules-based (ARB) and max rules-based (MRB). To determine efficient membership functions (MFs), a module named the heuristic-based membership functions allocation (HBMFA) module has been added to the conventional Mamdani fuzzy logic method. For rule reduction, a hierarchical fuzzy logic model with a distinct configuration has been proposed. In the simplified hierarchical fuzzy logic (SHFL) model, we have also tried to minimize rules as well as the number of levels of the hierarchical structure fuzzy logic model. After risk index assessment, the risk index prediction is carried out using a Kalman filter. The prediction of the risk index is significant because it could help caretakers to take preventive measures in time and prevent underground accidents. The results indicate that the suggested technique is an excellent choice for risk index assessment and prediction.
Keywords
fuzzy inference system, hierarchical fuzzy logic (HFL), membership functions (MFs), risk assessment, simplified hierarchical fuzzy logic (SHFL), underground risk
Suggested Citation
Fayaz M, Ullah I, Kim DH. Underground Risk Index Assessment and Prediction Using a Simplified Hierarchical Fuzzy Logic Model and Kalman Filter. (2018). LAPSE:2018.0407
Author Affiliations
Fayaz M: Department of Computer Engineering, Jeju National University, Jeju 63243, Korea
Ullah I: Department of Computer Engineering, Jeju National University, Jeju 63243, Korea
Kim DH: Department of Computer Engineering, Jeju National University, Jeju 63243, Korea
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Journal Name
Processes
Volume
6
Issue
8
Article Number
E103
Year
2018
Publication Date
2018-07-29
Published Version
ISSN
2227-9717
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PII: pr6080103, Publication Type: Journal Article
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LAPSE:2018.0407
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doi:10.3390/pr6080103
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Aug 28, 2018
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