Fuzzy Structured Element Integrated Decision of Metamorphism on Coal Dust Ignition Hazard Rating Article Swipe
Xiaoting Dong
,
Tianqi Liu
,
Xiaoyi Wang
,
Xiaoliang Xu
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2549/1/012013
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2549/1/012013
To discuss the coal dust ignition hazard rating of different metamorphism, the fuzzy structure element integrated decision model about “no danger”, “weak danger”, “general danger”, and “strong danger” of coal dust ignition is established. 40 kinds of coal samples are selected to carry out coal quality analysis test, overpressure test, temperature test, flame propagation properties test and particle size distribution test. Based on this, coal dust ignition hazard rating decision-making index system is built. The triangular structure element is added to fuzzy comprehensive decision model, by sequencing weighted Hamming distance between fuzzy index value function and fuzzy maximal function, the coal dust ignition hazard rating of different coal quality can be decided. The result shows that: with increasing metamorphic grade, coal dust ignition hazard rating is decreasing, which provides study basis for relation between metamorphism and ignition hazard rating.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/2549/1/012013
- https://iopscience.iop.org/article/10.1088/1742-6596/2549/1/012013/pdf
- OA Status
- diamond
- References
- 11
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4384701255
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4384701255Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1088/1742-6596/2549/1/012013Digital Object Identifier
- Title
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Fuzzy Structured Element Integrated Decision of Metamorphism on Coal Dust Ignition Hazard RatingWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
-
2023-07-01Full publication date if available
- Authors
-
Xiaoting Dong, Tianqi Liu, Xiaoyi Wang, Xiaoliang XuList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/2549/1/012013Publisher landing page
- PDF URL
-
https://iopscience.iop.org/article/10.1088/1742-6596/2549/1/012013/pdfDirect link to full text PDF
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YesWhether a free full text is available
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-
diamondOpen access status per OpenAlex
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https://iopscience.iop.org/article/10.1088/1742-6596/2549/1/012013/pdfDirect OA link when available
- Concepts
-
Ignition system, Coal, Coal dust, Hazard, Fuzzy logic, Bituminous coal, Mining engineering, Environmental science, Reliability engineering, Engineering, Computer science, Waste management, Chemistry, Artificial intelligence, Aerospace engineering, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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11Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.fuzzy | 13, 82, 92, 97 |
| abstract_inverted_index.index | 71, 93 |
| abstract_inverted_index.kinds | 36 |
| abstract_inverted_index.model | 18 |
| abstract_inverted_index.shows | 115 |
| abstract_inverted_index.study | 130 |
| abstract_inverted_index.test, | 48, 50, 52 |
| abstract_inverted_index.test. | 61 |
| abstract_inverted_index.that: | 116 |
| abstract_inverted_index.this, | 64 |
| abstract_inverted_index.value | 94 |
| abstract_inverted_index.which | 128 |
| abstract_inverted_index.“no | 20 |
| abstract_inverted_index.built. | 74 |
| abstract_inverted_index.grade, | 120 |
| abstract_inverted_index.hazard | 7, 68, 104, 124, 138 |
| abstract_inverted_index.model, | 85 |
| abstract_inverted_index.rating | 8, 69, 105, 125 |
| abstract_inverted_index.result | 114 |
| abstract_inverted_index.system | 72 |
| abstract_inverted_index.Hamming | 89 |
| abstract_inverted_index.between | 91, 134 |
| abstract_inverted_index.discuss | 2 |
| abstract_inverted_index.element | 15, 78 |
| abstract_inverted_index.maximal | 98 |
| abstract_inverted_index.quality | 46, 109 |
| abstract_inverted_index.rating. | 139 |
| abstract_inverted_index.samples | 39 |
| abstract_inverted_index.“weak | 22 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.analysis | 47 |
| abstract_inverted_index.decided. | 112 |
| abstract_inverted_index.decision | 17, 84 |
| abstract_inverted_index.distance | 90 |
| abstract_inverted_index.function | 95 |
| abstract_inverted_index.ignition | 6, 32, 67, 103, 123, 137 |
| abstract_inverted_index.particle | 58 |
| abstract_inverted_index.provides | 129 |
| abstract_inverted_index.relation | 133 |
| abstract_inverted_index.selected | 41 |
| abstract_inverted_index.weighted | 88 |
| abstract_inverted_index.danger” | 28 |
| abstract_inverted_index.different | 10, 107 |
| abstract_inverted_index.function, | 99 |
| abstract_inverted_index.structure | 14, 77 |
| abstract_inverted_index.“strong | 27 |
| abstract_inverted_index.danger”, | 21, 23, 25 |
| abstract_inverted_index.increasing | 118 |
| abstract_inverted_index.integrated | 16 |
| abstract_inverted_index.properties | 55 |
| abstract_inverted_index.sequencing | 87 |
| abstract_inverted_index.triangular | 76 |
| abstract_inverted_index.“general | 24 |
| abstract_inverted_index.decreasing, | 127 |
| abstract_inverted_index.metamorphic | 119 |
| abstract_inverted_index.propagation | 54 |
| abstract_inverted_index.temperature | 51 |
| abstract_inverted_index.distribution | 60 |
| abstract_inverted_index.established. | 34 |
| abstract_inverted_index.metamorphism | 135 |
| abstract_inverted_index.overpressure | 49 |
| abstract_inverted_index.comprehensive | 83 |
| abstract_inverted_index.metamorphism, | 11 |
| abstract_inverted_index.decision-making | 70 |
| cited_by_percentile_year | |
| corresponding_author_ids | https://openalex.org/A5100618134 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I125904092 |
| citation_normalized_percentile.value | 0.12386435 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |