Correlation and K-means clustering based small current ground fault line selection algorithm Article Swipe
Wenli Gao
,
Dongmin Xi
,
Linan Zheng
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2598/1/012010
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1742-6596/2598/1/012010
The existing small current grounding line selecting technique has consequences by transition resistance, fault closure angles, and the fault location, and there is a problem of low selection accuracy, which is addressed by proposing a line-choosing algorithm that employs a combination of transient zero-sequential current (TZSC) waveform correlation and K-means clustering. First, to obtain the correlation coefficient matrix, the correlation analysis is performed for each line of the zero-sequence currents transient measurement values; second, to address the issue of the difficulties in manually setting the threshold, we apply the K-mean cluster analysis algorithm to group the row vectors of the correlation coefficients matrices; and finally, we output the label of the cluster to realize the fault line selection. Simulation and real-world fault data validate the method, showing that it is independent of transition resistance, fault closure angles, and fault location. It can achieve precise and dependable line selectivity.
Related Topics
Concepts
Cluster analysis
Algorithm
Line (geometry)
Fault (geology)
Waveform
Correlation coefficient
Transient (computer programming)
Computer science
Closure (psychology)
Selection (genetic algorithm)
Correlation
Current (fluid)
Data mining
Mathematics
Engineering
Artificial intelligence
Machine learning
Electrical engineering
Geology
Geometry
Radar
Operating system
Telecommunications
Seismology
Market economy
Economics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1742-6596/2598/1/012010
- OA Status
- diamond
- Cited By
- 1
- References
- 2
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4386923840
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4386923840Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1742-6596/2598/1/012010Digital Object Identifier
- Title
-
Correlation and K-means clustering based small current ground fault line selection algorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-09-01Full publication date if available
- Authors
-
Wenli Gao, Dongmin Xi, Linan ZhengList of authors in order
- Landing page
-
https://doi.org/10.1088/1742-6596/2598/1/012010Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1088/1742-6596/2598/1/012010Direct OA link when available
- Concepts
-
Cluster analysis, Algorithm, Line (geometry), Fault (geology), Waveform, Correlation coefficient, Transient (computer programming), Computer science, Closure (psychology), Selection (genetic algorithm), Correlation, Current (fluid), Data mining, Mathematics, Engineering, Artificial intelligence, Machine learning, Electrical engineering, Geology, Geometry, Radar, Operating system, Telecommunications, Seismology, Market economy, EconomicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
2Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4386923840 |
|---|---|
| doi | https://doi.org/10.1088/1742-6596/2598/1/012010 |
| ids.doi | https://doi.org/10.1088/1742-6596/2598/1/012010 |
| ids.openalex | https://openalex.org/W4386923840 |
| fwci | 0.2488531 |
| type | article |
| title | Correlation and K-means clustering based small current ground fault line selection algorithm |
| biblio.issue | 1 |
| biblio.volume | 2598 |
| biblio.last_page | 012010 |
| biblio.first_page | 012010 |
| topics[0].id | https://openalex.org/T10972 |
| topics[0].field.id | https://openalex.org/fields/22 |
| topics[0].field.display_name | Engineering |
| topics[0].score | 0.9969000220298767 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/2207 |
| topics[0].subfield.display_name | Control and Systems Engineering |
| topics[0].display_name | Power Systems Fault Detection |
| topics[1].id | https://openalex.org/T11102 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9742000102996826 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2208 |
| topics[1].subfield.display_name | Electrical and Electronic Engineering |
| topics[1].display_name | HVDC Systems and Fault Protection |
| topics[2].id | https://openalex.org/T11941 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9675999879837036 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2213 |
| topics[2].subfield.display_name | Safety, Risk, Reliability and Quality |
| topics[2].display_name | Power System Reliability and Maintenance |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C73555534 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7362165451049805 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q622825 |
| concepts[0].display_name | Cluster analysis |
| concepts[1].id | https://openalex.org/C11413529 |
| concepts[1].level | 1 |
| concepts[1].score | 0.6311419010162354 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[1].display_name | Algorithm |
| concepts[2].id | https://openalex.org/C198352243 |
| concepts[2].level | 2 |
| concepts[2].score | 0.5904918909072876 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q37105 |
| concepts[2].display_name | Line (geometry) |
| concepts[3].id | https://openalex.org/C175551986 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5777415037155151 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q47089 |
| concepts[3].display_name | Fault (geology) |
| concepts[4].id | https://openalex.org/C197424946 |
| concepts[4].level | 3 |
| concepts[4].score | 0.5617496967315674 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1165717 |
| concepts[4].display_name | Waveform |
| concepts[5].id | https://openalex.org/C2780092901 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5426351428031921 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q3433612 |
| concepts[5].display_name | Correlation coefficient |
| concepts[6].id | https://openalex.org/C2780799671 |
| concepts[6].level | 2 |
| concepts[6].score | 0.5233361124992371 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q17087362 |
| concepts[6].display_name | Transient (computer programming) |
| concepts[7].id | https://openalex.org/C41008148 |
| concepts[7].level | 0 |
| concepts[7].score | 0.48201146721839905 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[7].display_name | Computer science |
| concepts[8].id | https://openalex.org/C146834321 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4820071756839752 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q2979672 |
| concepts[8].display_name | Closure (psychology) |
| concepts[9].id | https://openalex.org/C81917197 |
| concepts[9].level | 2 |
| concepts[9].score | 0.47123727202415466 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q628760 |
| concepts[9].display_name | Selection (genetic algorithm) |
| concepts[10].id | https://openalex.org/C117220453 |
| concepts[10].level | 2 |
| concepts[10].score | 0.46707063913345337 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q5172842 |
| concepts[10].display_name | Correlation |
| concepts[11].id | https://openalex.org/C148043351 |
| concepts[11].level | 2 |
| concepts[11].score | 0.4439549446105957 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q4456944 |
| concepts[11].display_name | Current (fluid) |
| concepts[12].id | https://openalex.org/C124101348 |
| concepts[12].level | 1 |
| concepts[12].score | 0.3313988447189331 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[12].display_name | Data mining |
| concepts[13].id | https://openalex.org/C33923547 |
| concepts[13].level | 0 |
| concepts[13].score | 0.3167656660079956 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[13].display_name | Mathematics |
| concepts[14].id | https://openalex.org/C127413603 |
| concepts[14].level | 0 |
| concepts[14].score | 0.23589134216308594 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[14].display_name | Engineering |
| concepts[15].id | https://openalex.org/C154945302 |
| concepts[15].level | 1 |
| concepts[15].score | 0.18539708852767944 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[15].display_name | Artificial intelligence |
| concepts[16].id | https://openalex.org/C119857082 |
| concepts[16].level | 1 |
| concepts[16].score | 0.10539472103118896 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[16].display_name | Machine learning |
| concepts[17].id | https://openalex.org/C119599485 |
| concepts[17].level | 1 |
| concepts[17].score | 0.07030490040779114 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q43035 |
| concepts[17].display_name | Electrical engineering |
| concepts[18].id | https://openalex.org/C127313418 |
| concepts[18].level | 0 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q1069 |
| concepts[18].display_name | Geology |
| concepts[19].id | https://openalex.org/C2524010 |
| concepts[19].level | 1 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q8087 |
| concepts[19].display_name | Geometry |
| concepts[20].id | https://openalex.org/C554190296 |
| concepts[20].level | 2 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q47528 |
| concepts[20].display_name | Radar |
| concepts[21].id | https://openalex.org/C111919701 |
| concepts[21].level | 1 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[21].display_name | Operating system |
| concepts[22].id | https://openalex.org/C76155785 |
| concepts[22].level | 1 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[22].display_name | Telecommunications |
| concepts[23].id | https://openalex.org/C165205528 |
| concepts[23].level | 1 |
| concepts[23].score | 0.0 |
| concepts[23].wikidata | https://www.wikidata.org/wiki/Q83371 |
| concepts[23].display_name | Seismology |
| concepts[24].id | https://openalex.org/C34447519 |
| concepts[24].level | 1 |
| concepts[24].score | 0.0 |
| concepts[24].wikidata | https://www.wikidata.org/wiki/Q179522 |
| concepts[24].display_name | Market economy |
| concepts[25].id | https://openalex.org/C162324750 |
| concepts[25].level | 0 |
| concepts[25].score | 0.0 |
| concepts[25].wikidata | https://www.wikidata.org/wiki/Q8134 |
| concepts[25].display_name | Economics |
| keywords[0].id | https://openalex.org/keywords/cluster-analysis |
| keywords[0].score | 0.7362165451049805 |
| keywords[0].display_name | Cluster analysis |
| keywords[1].id | https://openalex.org/keywords/algorithm |
| keywords[1].score | 0.6311419010162354 |
| keywords[1].display_name | Algorithm |
| keywords[2].id | https://openalex.org/keywords/line |
| keywords[2].score | 0.5904918909072876 |
| keywords[2].display_name | Line (geometry) |
| keywords[3].id | https://openalex.org/keywords/fault |
| keywords[3].score | 0.5777415037155151 |
| keywords[3].display_name | Fault (geology) |
| keywords[4].id | https://openalex.org/keywords/waveform |
| keywords[4].score | 0.5617496967315674 |
| keywords[4].display_name | Waveform |
| keywords[5].id | https://openalex.org/keywords/correlation-coefficient |
| keywords[5].score | 0.5426351428031921 |
| keywords[5].display_name | Correlation coefficient |
| keywords[6].id | https://openalex.org/keywords/transient |
| keywords[6].score | 0.5233361124992371 |
| keywords[6].display_name | Transient (computer programming) |
| keywords[7].id | https://openalex.org/keywords/computer-science |
| keywords[7].score | 0.48201146721839905 |
| keywords[7].display_name | Computer science |
| keywords[8].id | https://openalex.org/keywords/closure |
| keywords[8].score | 0.4820071756839752 |
| keywords[8].display_name | Closure (psychology) |
| keywords[9].id | https://openalex.org/keywords/selection |
| keywords[9].score | 0.47123727202415466 |
| keywords[9].display_name | Selection (genetic algorithm) |
| keywords[10].id | https://openalex.org/keywords/correlation |
| keywords[10].score | 0.46707063913345337 |
| keywords[10].display_name | Correlation |
| keywords[11].id | https://openalex.org/keywords/current |
| keywords[11].score | 0.4439549446105957 |
| keywords[11].display_name | Current (fluid) |
| keywords[12].id | https://openalex.org/keywords/data-mining |
| keywords[12].score | 0.3313988447189331 |
| keywords[12].display_name | Data mining |
| keywords[13].id | https://openalex.org/keywords/mathematics |
| keywords[13].score | 0.3167656660079956 |
| keywords[13].display_name | Mathematics |
| keywords[14].id | https://openalex.org/keywords/engineering |
| keywords[14].score | 0.23589134216308594 |
| keywords[14].display_name | Engineering |
| keywords[15].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[15].score | 0.18539708852767944 |
| keywords[15].display_name | Artificial intelligence |
| keywords[16].id | https://openalex.org/keywords/machine-learning |
| keywords[16].score | 0.10539472103118896 |
| keywords[16].display_name | Machine learning |
| keywords[17].id | https://openalex.org/keywords/electrical-engineering |
| keywords[17].score | 0.07030490040779114 |
| keywords[17].display_name | Electrical engineering |
| language | en |
| locations[0].id | doi:10.1088/1742-6596/2598/1/012010 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210187594 |
| locations[0].source.issn | 1742-6588, 1742-6596 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 1742-6588 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Journal of Physics Conference Series |
| locations[0].source.host_organization | https://openalex.org/P4310320083 |
| locations[0].source.host_organization_name | IOP Publishing |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310320083, https://openalex.org/P4310311669 |
| locations[0].source.host_organization_lineage_names | IOP Publishing, Institute of Physics |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Journal of Physics: Conference Series |
| locations[0].landing_page_url | https://doi.org/10.1088/1742-6596/2598/1/012010 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5101513851 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-8101-820X |
| authorships[0].author.display_name | Wenli Gao |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I55654194 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Electric Power, Inner Mongolia University of Technology, Huhhot 010000, China. |
| authorships[0].affiliations[1].raw_affiliation_string | Engineering Research Center of Large Energy Storage Technology, Ministry of Education, Huhhot 010000, China. |
| authorships[0].institutions[0].id | https://openalex.org/I55654194 |
| authorships[0].institutions[0].ror | https://ror.org/05564e019 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I55654194 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Inner Mongolia University of Technology |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Wenli Gao |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Engineering Research Center of Large Energy Storage Technology, Ministry of Education, Huhhot 010000, China., School of Electric Power, Inner Mongolia University of Technology, Huhhot 010000, China. |
| authorships[1].author.id | https://openalex.org/A5035571648 |
| authorships[1].author.orcid | |
| authorships[1].author.display_name | Dongmin Xi |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].raw_affiliation_string | Engineering Research Center of Large Energy Storage Technology, Ministry of Education, Huhhot 010000, China. |
| authorships[1].affiliations[1].institution_ids | https://openalex.org/I55654194 |
| authorships[1].affiliations[1].raw_affiliation_string | School of Electric Power, Inner Mongolia University of Technology, Huhhot 010000, China. |
| authorships[1].institutions[0].id | https://openalex.org/I55654194 |
| authorships[1].institutions[0].ror | https://ror.org/05564e019 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I55654194 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Inner Mongolia University of Technology |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Dongmin Xi |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Engineering Research Center of Large Energy Storage Technology, Ministry of Education, Huhhot 010000, China., School of Electric Power, Inner Mongolia University of Technology, Huhhot 010000, China. |
| authorships[2].author.id | https://openalex.org/A5109456074 |
| authorships[2].author.orcid | |
| authorships[2].author.display_name | Linan Zheng |
| authorships[2].affiliations[0].raw_affiliation_string | . State Grid Tibet Electric Power Co., Ltd, Lhasa 850000, China. |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Linan Zheng |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | . State Grid Tibet Electric Power Co., Ltd, Lhasa 850000, China. |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.1088/1742-6596/2598/1/012010 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Correlation and K-means clustering based small current ground fault line selection algorithm |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10972 |
| primary_topic.field.id | https://openalex.org/fields/22 |
| primary_topic.field.display_name | Engineering |
| primary_topic.score | 0.9969000220298767 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/2207 |
| primary_topic.subfield.display_name | Control and Systems Engineering |
| primary_topic.display_name | Power Systems Fault Detection |
| related_works | https://openalex.org/W2372194214, https://openalex.org/W3081640970, https://openalex.org/W4200439127, https://openalex.org/W2021013714, https://openalex.org/W2412250669, https://openalex.org/W2359856669, https://openalex.org/W2078603735, https://openalex.org/W1488551807, https://openalex.org/W2023979854, https://openalex.org/W2560331580 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1088/1742-6596/2598/1/012010 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210187594 |
| best_oa_location.source.issn | 1742-6588, 1742-6596 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 1742-6588 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Journal of Physics Conference Series |
| best_oa_location.source.host_organization | https://openalex.org/P4310320083 |
| best_oa_location.source.host_organization_name | IOP Publishing |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320083, https://openalex.org/P4310311669 |
| best_oa_location.source.host_organization_lineage_names | IOP Publishing, Institute of Physics |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Journal of Physics: Conference Series |
| best_oa_location.landing_page_url | https://doi.org/10.1088/1742-6596/2598/1/012010 |
| primary_location.id | doi:10.1088/1742-6596/2598/1/012010 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210187594 |
| primary_location.source.issn | 1742-6588, 1742-6596 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 1742-6588 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Journal of Physics Conference Series |
| primary_location.source.host_organization | https://openalex.org/P4310320083 |
| primary_location.source.host_organization_name | IOP Publishing |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320083, https://openalex.org/P4310311669 |
| primary_location.source.host_organization_lineage_names | IOP Publishing, Institute of Physics |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Journal of Physics: Conference Series |
| primary_location.landing_page_url | https://doi.org/10.1088/1742-6596/2598/1/012010 |
| publication_date | 2023-09-01 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W2363571259, https://openalex.org/W2362142601 |
| referenced_works_count | 2 |
| abstract_inverted_index.a | 24, 35, 40 |
| abstract_inverted_index.It | 141 |
| abstract_inverted_index.by | 11, 33 |
| abstract_inverted_index.in | 82 |
| abstract_inverted_index.is | 23, 31, 62, 130 |
| abstract_inverted_index.it | 129 |
| abstract_inverted_index.of | 26, 42, 67, 79, 99, 110, 132 |
| abstract_inverted_index.to | 53, 75, 94, 113 |
| abstract_inverted_index.we | 87, 106 |
| abstract_inverted_index.The | 1 |
| abstract_inverted_index.and | 17, 21, 49, 104, 120, 138, 145 |
| abstract_inverted_index.can | 142 |
| abstract_inverted_index.for | 64 |
| abstract_inverted_index.has | 9 |
| abstract_inverted_index.low | 27 |
| abstract_inverted_index.row | 97 |
| abstract_inverted_index.the | 18, 55, 59, 68, 77, 80, 85, 89, 96, 100, 108, 111, 115, 125 |
| abstract_inverted_index.data | 123 |
| abstract_inverted_index.each | 65 |
| abstract_inverted_index.line | 6, 66, 117, 147 |
| abstract_inverted_index.that | 38, 128 |
| abstract_inverted_index.apply | 88 |
| abstract_inverted_index.fault | 14, 19, 116, 122, 135, 139 |
| abstract_inverted_index.group | 95 |
| abstract_inverted_index.issue | 78 |
| abstract_inverted_index.label | 109 |
| abstract_inverted_index.small | 3 |
| abstract_inverted_index.there | 22 |
| abstract_inverted_index.which | 30 |
| abstract_inverted_index.(TZSC) | 46 |
| abstract_inverted_index.First, | 52 |
| abstract_inverted_index.K-mean | 90 |
| abstract_inverted_index.obtain | 54 |
| abstract_inverted_index.output | 107 |
| abstract_inverted_index.K-means | 50 |
| abstract_inverted_index.achieve | 143 |
| abstract_inverted_index.address | 76 |
| abstract_inverted_index.angles, | 16, 137 |
| abstract_inverted_index.closure | 15, 136 |
| abstract_inverted_index.cluster | 91, 112 |
| abstract_inverted_index.current | 4, 45 |
| abstract_inverted_index.employs | 39 |
| abstract_inverted_index.matrix, | 58 |
| abstract_inverted_index.method, | 126 |
| abstract_inverted_index.precise | 144 |
| abstract_inverted_index.problem | 25 |
| abstract_inverted_index.realize | 114 |
| abstract_inverted_index.second, | 74 |
| abstract_inverted_index.setting | 84 |
| abstract_inverted_index.showing | 127 |
| abstract_inverted_index.values; | 73 |
| abstract_inverted_index.vectors | 98 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.analysis | 61, 92 |
| abstract_inverted_index.currents | 70 |
| abstract_inverted_index.existing | 2 |
| abstract_inverted_index.finally, | 105 |
| abstract_inverted_index.manually | 83 |
| abstract_inverted_index.validate | 124 |
| abstract_inverted_index.waveform | 47 |
| abstract_inverted_index.accuracy, | 29 |
| abstract_inverted_index.addressed | 32 |
| abstract_inverted_index.algorithm | 37, 93 |
| abstract_inverted_index.grounding | 5 |
| abstract_inverted_index.location, | 20 |
| abstract_inverted_index.location. | 140 |
| abstract_inverted_index.matrices; | 103 |
| abstract_inverted_index.performed | 63 |
| abstract_inverted_index.proposing | 34 |
| abstract_inverted_index.selecting | 7 |
| abstract_inverted_index.selection | 28 |
| abstract_inverted_index.technique | 8 |
| abstract_inverted_index.transient | 43, 71 |
| abstract_inverted_index.Simulation | 119 |
| abstract_inverted_index.dependable | 146 |
| abstract_inverted_index.real-world | 121 |
| abstract_inverted_index.selection. | 118 |
| abstract_inverted_index.threshold, | 86 |
| abstract_inverted_index.transition | 12, 133 |
| abstract_inverted_index.clustering. | 51 |
| abstract_inverted_index.coefficient | 57 |
| abstract_inverted_index.combination | 41 |
| abstract_inverted_index.correlation | 48, 56, 60, 101 |
| abstract_inverted_index.independent | 131 |
| abstract_inverted_index.measurement | 72 |
| abstract_inverted_index.resistance, | 13, 134 |
| abstract_inverted_index.coefficients | 102 |
| abstract_inverted_index.consequences | 10 |
| abstract_inverted_index.difficulties | 81 |
| abstract_inverted_index.selectivity. | 148 |
| abstract_inverted_index.line-choosing | 36 |
| abstract_inverted_index.zero-sequence | 69 |
| abstract_inverted_index.zero-sequential | 44 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.50915208 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |