Abnormal Monitoring Data Detection Based on Matrix Manipulation and the Cuckoo Search Algorithm Article Swipe
Zhenzhu Meng
,
Yiren Wang
,
Sen Zheng
,
Xiao Wang
,
Dan Liu
,
Jinxin Zhang
,
Yiting Shao
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/math12091345
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/math12091345
Structural health monitoring is an effective method to evaluate the safety status of dams. Measurement error is an important factor which affects the accuracy of monitoring data modeling. Processing the abnormal monitoring data before data analysis is a necessary step to ensure the reliability of the analysis. In this paper, we proposed a method to process the abnormal dam displacement monitoring data on the basis of matrix manipulation and Cuckoo Search algorithm. We first generate a scatter plot of the monitoring data and exported the matrix of the image. The scatter plot of monitoring data includes isolate outliers, clusters of outliers, and clusters of normal points. The gray scales of isolated outliers are reduced using Gaussian blur. Then, the isolated outliers are eliminated using Ostu binarization. We then use the Cuckoo Search algorithm to distinguish the clusters of outliers and clusters of normal points to identify the process line. To evaluate the performance of the proposed data processing method, we also fitted the data processed by the proposed method and by the commonly used 3-σ method using a regression model, respectively. Results indicate that the proposed method has a better performance in abnormal detection compared with the 3-σ method.
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/math12091345
- https://www.mdpi.com/2227-7390/12/9/1345/pdf?version=1714371082
- OA Status
- gold
- Cited By
- 27
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4396229131
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4396229131Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/math12091345Digital Object Identifier
- Title
-
Abnormal Monitoring Data Detection Based on Matrix Manipulation and the Cuckoo Search AlgorithmWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-04-29Full publication date if available
- Authors
-
Zhenzhu Meng, Yiren Wang, Sen Zheng, Xiao Wang, Dan Liu, Jinxin Zhang, Yiting ShaoList of authors in order
- Landing page
-
https://doi.org/10.3390/math12091345Publisher landing page
- PDF URL
-
https://www.mdpi.com/2227-7390/12/9/1345/pdf?version=1714371082Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2227-7390/12/9/1345/pdf?version=1714371082Direct OA link when available
- Concepts
-
Outlier, Cuckoo search, Computer science, Anomaly detection, Artificial intelligence, Pattern recognition (psychology), Algorithm, Data mining, Particle swarm optimizationTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
27Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 9, 2024: 18Per-year citation counts (last 5 years)
- References (count)
-
30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4396229131 |
|---|---|
| doi | https://doi.org/10.3390/math12091345 |
| ids.doi | https://doi.org/10.3390/math12091345 |
| ids.openalex | https://openalex.org/W4396229131 |
| fwci | 17.24702083 |
| type | article |
| title | Abnormal Monitoring Data Detection Based on Matrix Manipulation and the Cuckoo Search Algorithm |
| biblio.issue | 9 |
| biblio.volume | 12 |
| biblio.last_page | 1345 |
| biblio.first_page | 1345 |
| topics[0].id | https://openalex.org/T11512 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9984999895095825 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Anomaly Detection Techniques and Applications |
| topics[1].id | https://openalex.org/T12293 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9959999918937683 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2205 |
| topics[1].subfield.display_name | Civil and Structural Engineering |
| topics[1].display_name | Dam Engineering and Safety |
| topics[2].id | https://openalex.org/T10535 |
| topics[2].field.id | https://openalex.org/fields/23 |
| topics[2].field.display_name | Environmental Science |
| topics[2].score | 0.9815999865531921 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2308 |
| topics[2].subfield.display_name | Management, Monitoring, Policy and Law |
| topics[2].display_name | Landslides and related hazards |
| is_xpac | False |
| apc_list.value | 1800 |
| apc_list.currency | CHF |
| apc_list.value_usd | 1949 |
| apc_paid.value | 1800 |
| apc_paid.currency | CHF |
| apc_paid.value_usd | 1949 |
| concepts[0].id | https://openalex.org/C79337645 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8000591993331909 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q779824 |
| concepts[0].display_name | Outlier |
| concepts[1].id | https://openalex.org/C117241572 |
| concepts[1].level | 3 |
| concepts[1].score | 0.7632132768630981 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q5192379 |
| concepts[1].display_name | Cuckoo search |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.7020993828773499 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C739882 |
| concepts[3].level | 2 |
| concepts[3].score | 0.5431195497512817 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q3560506 |
| concepts[3].display_name | Anomaly detection |
| concepts[4].id | https://openalex.org/C154945302 |
| concepts[4].level | 1 |
| concepts[4].score | 0.49852538108825684 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[4].display_name | Artificial intelligence |
| concepts[5].id | https://openalex.org/C153180895 |
| concepts[5].level | 2 |
| concepts[5].score | 0.49689343571662903 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q7148389 |
| concepts[5].display_name | Pattern recognition (psychology) |
| concepts[6].id | https://openalex.org/C11413529 |
| concepts[6].level | 1 |
| concepts[6].score | 0.4805765151977539 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q8366 |
| concepts[6].display_name | Algorithm |
| concepts[7].id | https://openalex.org/C124101348 |
| concepts[7].level | 1 |
| concepts[7].score | 0.43553948402404785 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q172491 |
| concepts[7].display_name | Data mining |
| concepts[8].id | https://openalex.org/C85617194 |
| concepts[8].level | 2 |
| concepts[8].score | 0.0793662965297699 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q2072794 |
| concepts[8].display_name | Particle swarm optimization |
| keywords[0].id | https://openalex.org/keywords/outlier |
| keywords[0].score | 0.8000591993331909 |
| keywords[0].display_name | Outlier |
| keywords[1].id | https://openalex.org/keywords/cuckoo-search |
| keywords[1].score | 0.7632132768630981 |
| keywords[1].display_name | Cuckoo search |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.7020993828773499 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/anomaly-detection |
| keywords[3].score | 0.5431195497512817 |
| keywords[3].display_name | Anomaly detection |
| keywords[4].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[4].score | 0.49852538108825684 |
| keywords[4].display_name | Artificial intelligence |
| keywords[5].id | https://openalex.org/keywords/pattern-recognition |
| keywords[5].score | 0.49689343571662903 |
| keywords[5].display_name | Pattern recognition (psychology) |
| keywords[6].id | https://openalex.org/keywords/algorithm |
| keywords[6].score | 0.4805765151977539 |
| keywords[6].display_name | Algorithm |
| keywords[7].id | https://openalex.org/keywords/data-mining |
| keywords[7].score | 0.43553948402404785 |
| keywords[7].display_name | Data mining |
| keywords[8].id | https://openalex.org/keywords/particle-swarm-optimization |
| keywords[8].score | 0.0793662965297699 |
| keywords[8].display_name | Particle swarm optimization |
| language | en |
| locations[0].id | doi:10.3390/math12091345 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210192031 |
| locations[0].source.issn | 2227-7390 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2227-7390 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | True |
| locations[0].source.display_name | Mathematics |
| locations[0].source.host_organization | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| locations[0].source.host_organization_lineage | https://openalex.org/P4310310987 |
| locations[0].source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| locations[0].license | cc-by |
| locations[0].pdf_url | https://www.mdpi.com/2227-7390/12/9/1345/pdf?version=1714371082 |
| 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 | Mathematics |
| locations[0].landing_page_url | https://doi.org/10.3390/math12091345 |
| locations[1].id | pmh:oai:doaj.org/article:77e8a2a00c994e0294c80a411ce47ebd |
| locations[1].is_oa | False |
| locations[1].source.id | https://openalex.org/S4306401280 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | False |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | DOAJ (DOAJ: Directory of Open Access Journals) |
| locations[1].source.host_organization | |
| locations[1].source.host_organization_name | |
| locations[1].license | |
| locations[1].pdf_url | |
| locations[1].version | submittedVersion |
| locations[1].raw_type | article |
| locations[1].license_id | |
| locations[1].is_accepted | False |
| locations[1].is_published | False |
| locations[1].raw_source_name | Mathematics, Vol 12, Iss 9, p 1345 (2024) |
| locations[1].landing_page_url | https://doaj.org/article/77e8a2a00c994e0294c80a411ce47ebd |
| locations[2].id | pmh:oai:infoscience.epfl.ch:311397 |
| locations[2].is_oa | True |
| locations[2].source.id | https://openalex.org/S4306400487 |
| locations[2].source.issn | |
| locations[2].source.type | repository |
| locations[2].source.is_oa | True |
| locations[2].source.issn_l | |
| locations[2].source.is_core | False |
| locations[2].source.is_in_doaj | False |
| locations[2].source.display_name | Infoscience (Ecole Polytechnique Fédérale de Lausanne) |
| locations[2].source.host_organization | |
| locations[2].source.host_organization_name | |
| locations[2].license | cc-by-nc-nd |
| locations[2].pdf_url | |
| locations[2].version | submittedVersion |
| locations[2].raw_type | research article |
| locations[2].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[2].is_accepted | False |
| locations[2].is_published | False |
| locations[2].raw_source_name | WoS |
| locations[2].landing_page_url | http://infoscience.epfl.ch/record/311397 |
| indexed_in | crossref, doaj |
| authorships[0].author.id | https://openalex.org/A5020838311 |
| authorships[0].author.orcid | https://orcid.org/0000-0002-3497-0254 |
| authorships[0].author.display_name | Zhenzhu Meng |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I4210160030 |
| authorships[0].affiliations[0].raw_affiliation_string | School of Water Conservancy and Environment Engineering & Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China |
| authorships[0].institutions[0].id | https://openalex.org/I4210160030 |
| authorships[0].institutions[0].ror | https://ror.org/04dg5b632 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I4210160030 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Zhejiang University of Water Resource and Electric Power |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Zhenzhu Meng |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | School of Water Conservancy and Environment Engineering & Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China |
| authorships[1].author.id | https://openalex.org/A5100723437 |
| authorships[1].author.orcid | https://orcid.org/0000-0001-6757-5923 |
| authorships[1].author.display_name | Yiren Wang |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I2799850029 |
| authorships[1].affiliations[0].raw_affiliation_string | School of Environment and Civil Engineering, Dongguan University of Technology & Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, Dongguan 523808, China |
| authorships[1].institutions[0].id | https://openalex.org/I2799850029 |
| authorships[1].institutions[0].ror | https://ror.org/01m8p7q42 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I2799850029 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Dongguan University of Technology |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Yiren Wang |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | School of Environment and Civil Engineering, Dongguan University of Technology & Guangdong Provincial Key Laboratory of Intelligent Disaster Prevention and Emergency Technologies for Urban Lifeline Engineering, Dongguan 523808, China |
| authorships[2].author.id | https://openalex.org/A5031822427 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-1527-8235 |
| authorships[2].author.display_name | Sen Zheng |
| authorships[2].countries | CH |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I5124864 |
| authorships[2].affiliations[0].raw_affiliation_string | Laboratory of Environmental Hydraulics, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland |
| authorships[2].institutions[0].id | https://openalex.org/I5124864 |
| authorships[2].institutions[0].ror | https://ror.org/02s376052 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I2799323385, https://openalex.org/I5124864 |
| authorships[2].institutions[0].country_code | CH |
| authorships[2].institutions[0].display_name | École Polytechnique Fédérale de Lausanne |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Sen Zheng |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Laboratory of Environmental Hydraulics, Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland |
| authorships[3].author.id | https://openalex.org/A5100411438 |
| authorships[3].author.orcid | https://orcid.org/0000-0001-8139-4192 |
| authorships[3].author.display_name | Xiao Wang |
| authorships[3].affiliations[0].raw_affiliation_string | Huai'an Hydraulic Surcey and Design Research Institute Co., Ltd., Huaian 223500, China |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Xiao Wang |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Huai'an Hydraulic Surcey and Design Research Institute Co., Ltd., Huaian 223500, China |
| authorships[4].author.id | https://openalex.org/A5101983108 |
| authorships[4].author.orcid | https://orcid.org/0000-0003-4408-7964 |
| authorships[4].author.display_name | Dan Liu |
| authorships[4].countries | CN |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I4210160030 |
| authorships[4].affiliations[0].raw_affiliation_string | School of Water Conservancy and Environment Engineering & Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China |
| authorships[4].institutions[0].id | https://openalex.org/I4210160030 |
| authorships[4].institutions[0].ror | https://ror.org/04dg5b632 |
| authorships[4].institutions[0].type | education |
| authorships[4].institutions[0].lineage | https://openalex.org/I4210160030 |
| authorships[4].institutions[0].country_code | CN |
| authorships[4].institutions[0].display_name | Zhejiang University of Water Resource and Electric Power |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Dan Liu |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | School of Water Conservancy and Environment Engineering & Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China |
| authorships[5].author.id | https://openalex.org/A5100741696 |
| authorships[5].author.orcid | https://orcid.org/0000-0003-0293-7262 |
| authorships[5].author.display_name | Jinxin Zhang |
| authorships[5].countries | CN |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I4210160030 |
| authorships[5].affiliations[0].raw_affiliation_string | School of Water Conservancy and Environment Engineering & Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China |
| authorships[5].institutions[0].id | https://openalex.org/I4210160030 |
| authorships[5].institutions[0].ror | https://ror.org/04dg5b632 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I4210160030 |
| authorships[5].institutions[0].country_code | CN |
| authorships[5].institutions[0].display_name | Zhejiang University of Water Resource and Electric Power |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Jinxin Zhang |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | School of Water Conservancy and Environment Engineering & Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China |
| authorships[6].author.id | https://openalex.org/A5040696546 |
| authorships[6].author.orcid | https://orcid.org/0000-0001-9625-0124 |
| authorships[6].author.display_name | Yiting Shao |
| authorships[6].countries | CN |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I4210160030 |
| authorships[6].affiliations[0].raw_affiliation_string | School of Water Conservancy and Environment Engineering & Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China |
| authorships[6].institutions[0].id | https://openalex.org/I4210160030 |
| authorships[6].institutions[0].ror | https://ror.org/04dg5b632 |
| authorships[6].institutions[0].type | education |
| authorships[6].institutions[0].lineage | https://openalex.org/I4210160030 |
| authorships[6].institutions[0].country_code | CN |
| authorships[6].institutions[0].display_name | Zhejiang University of Water Resource and Electric Power |
| authorships[6].author_position | last |
| authorships[6].raw_author_name | Yiting Shao |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | School of Water Conservancy and Environment Engineering & Nanxun Innovation Institute, Zhejiang University of Water Resources and Electric Power, Hangzhou 310018, China |
| has_content.pdf | True |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.mdpi.com/2227-7390/12/9/1345/pdf?version=1714371082 |
| open_access.oa_status | gold |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Abnormal Monitoring Data Detection Based on Matrix Manipulation and the Cuckoo Search Algorithm |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T11512 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9984999895095825 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Anomaly Detection Techniques and Applications |
| related_works | https://openalex.org/W1978568284, https://openalex.org/W2102833174, https://openalex.org/W2753354457, https://openalex.org/W2742451303, https://openalex.org/W2499612753, https://openalex.org/W3111802945, https://openalex.org/W2946096271, https://openalex.org/W2295423552, https://openalex.org/W1598471830, https://openalex.org/W3107369729 |
| cited_by_count | 27 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 9 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 18 |
| locations_count | 3 |
| best_oa_location.id | doi:10.3390/math12091345 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210192031 |
| best_oa_location.source.issn | 2227-7390 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2227-7390 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | Mathematics |
| best_oa_location.source.host_organization | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| best_oa_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | https://www.mdpi.com/2227-7390/12/9/1345/pdf?version=1714371082 |
| 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 | Mathematics |
| best_oa_location.landing_page_url | https://doi.org/10.3390/math12091345 |
| primary_location.id | doi:10.3390/math12091345 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210192031 |
| primary_location.source.issn | 2227-7390 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2227-7390 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | Mathematics |
| primary_location.source.host_organization | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_name | Multidisciplinary Digital Publishing Institute |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310310987 |
| primary_location.source.host_organization_lineage_names | Multidisciplinary Digital Publishing Institute |
| primary_location.license | cc-by |
| primary_location.pdf_url | https://www.mdpi.com/2227-7390/12/9/1345/pdf?version=1714371082 |
| 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 | Mathematics |
| primary_location.landing_page_url | https://doi.org/10.3390/math12091345 |
| publication_date | 2024-04-29 |
| publication_year | 2024 |
| referenced_works | https://openalex.org/W2008448036, https://openalex.org/W2006005267, https://openalex.org/W1503596152, https://openalex.org/W2003285904, https://openalex.org/W2082524457, https://openalex.org/W1972333006, https://openalex.org/W2012211646, https://openalex.org/W2005161317, https://openalex.org/W2767681036, https://openalex.org/W2584696667, https://openalex.org/W2610434510, https://openalex.org/W4200457408, https://openalex.org/W4206622111, https://openalex.org/W4393254038, https://openalex.org/W2004914514, https://openalex.org/W3040956604, https://openalex.org/W3114932221, https://openalex.org/W4393940601, https://openalex.org/W2791957585, https://openalex.org/W2760451156, https://openalex.org/W1996073420, https://openalex.org/W4376869077, https://openalex.org/W4200410798, https://openalex.org/W4313593865, https://openalex.org/W4206395781, https://openalex.org/W2496836423, https://openalex.org/W2240552610, https://openalex.org/W2153107582, https://openalex.org/W1669383326, https://openalex.org/W2753354457 |
| referenced_works_count | 30 |
| abstract_inverted_index.a | 37, 52, 75, 177, 188 |
| abstract_inverted_index.In | 47 |
| abstract_inverted_index.To | 149 |
| abstract_inverted_index.We | 72, 126 |
| abstract_inverted_index.an | 4, 17 |
| abstract_inverted_index.by | 165, 170 |
| abstract_inverted_index.in | 191 |
| abstract_inverted_index.is | 3, 16, 36 |
| abstract_inverted_index.of | 12, 24, 44, 65, 78, 86, 92, 99, 103, 109, 137, 141, 153 |
| abstract_inverted_index.on | 62 |
| abstract_inverted_index.to | 7, 40, 54, 133, 144 |
| abstract_inverted_index.we | 50, 159 |
| abstract_inverted_index.The | 89, 106 |
| abstract_inverted_index.and | 68, 82, 101, 139, 169 |
| abstract_inverted_index.are | 112, 121 |
| abstract_inverted_index.dam | 58 |
| abstract_inverted_index.has | 187 |
| abstract_inverted_index.the | 9, 22, 29, 42, 45, 56, 63, 79, 84, 87, 118, 129, 135, 146, 151, 154, 162, 166, 171, 184, 196 |
| abstract_inverted_index.use | 128 |
| abstract_inverted_index.3-σ | 174, 197 |
| abstract_inverted_index.Ostu | 124 |
| abstract_inverted_index.also | 160 |
| abstract_inverted_index.data | 26, 32, 34, 61, 81, 94, 156, 163 |
| abstract_inverted_index.gray | 107 |
| abstract_inverted_index.plot | 77, 91 |
| abstract_inverted_index.step | 39 |
| abstract_inverted_index.that | 183 |
| abstract_inverted_index.then | 127 |
| abstract_inverted_index.this | 48 |
| abstract_inverted_index.used | 173 |
| abstract_inverted_index.with | 195 |
| abstract_inverted_index.Then, | 117 |
| abstract_inverted_index.basis | 64 |
| abstract_inverted_index.blur. | 116 |
| abstract_inverted_index.dams. | 13 |
| abstract_inverted_index.error | 15 |
| abstract_inverted_index.first | 73 |
| abstract_inverted_index.line. | 148 |
| abstract_inverted_index.using | 114, 123, 176 |
| abstract_inverted_index.which | 20 |
| abstract_inverted_index.Cuckoo | 69, 130 |
| abstract_inverted_index.Search | 70, 131 |
| abstract_inverted_index.before | 33 |
| abstract_inverted_index.better | 189 |
| abstract_inverted_index.ensure | 41 |
| abstract_inverted_index.factor | 19 |
| abstract_inverted_index.fitted | 161 |
| abstract_inverted_index.health | 1 |
| abstract_inverted_index.image. | 88 |
| abstract_inverted_index.matrix | 66, 85 |
| abstract_inverted_index.method | 6, 53, 168, 175, 186 |
| abstract_inverted_index.model, | 179 |
| abstract_inverted_index.normal | 104, 142 |
| abstract_inverted_index.paper, | 49 |
| abstract_inverted_index.points | 143 |
| abstract_inverted_index.safety | 10 |
| abstract_inverted_index.scales | 108 |
| abstract_inverted_index.status | 11 |
| abstract_inverted_index.Results | 181 |
| abstract_inverted_index.affects | 21 |
| abstract_inverted_index.isolate | 96 |
| abstract_inverted_index.method, | 158 |
| abstract_inverted_index.method. | 198 |
| abstract_inverted_index.points. | 105 |
| abstract_inverted_index.process | 55, 147 |
| abstract_inverted_index.reduced | 113 |
| abstract_inverted_index.scatter | 76, 90 |
| abstract_inverted_index.Gaussian | 115 |
| abstract_inverted_index.abnormal | 30, 57, 192 |
| abstract_inverted_index.accuracy | 23 |
| abstract_inverted_index.analysis | 35 |
| abstract_inverted_index.clusters | 98, 102, 136, 140 |
| abstract_inverted_index.commonly | 172 |
| abstract_inverted_index.compared | 194 |
| abstract_inverted_index.evaluate | 8, 150 |
| abstract_inverted_index.exported | 83 |
| abstract_inverted_index.generate | 74 |
| abstract_inverted_index.identify | 145 |
| abstract_inverted_index.includes | 95 |
| abstract_inverted_index.indicate | 182 |
| abstract_inverted_index.isolated | 110, 119 |
| abstract_inverted_index.outliers | 111, 120, 138 |
| abstract_inverted_index.proposed | 51, 155, 167, 185 |
| abstract_inverted_index.algorithm | 132 |
| abstract_inverted_index.analysis. | 46 |
| abstract_inverted_index.detection | 193 |
| abstract_inverted_index.effective | 5 |
| abstract_inverted_index.important | 18 |
| abstract_inverted_index.modeling. | 27 |
| abstract_inverted_index.necessary | 38 |
| abstract_inverted_index.outliers, | 97, 100 |
| abstract_inverted_index.processed | 164 |
| abstract_inverted_index.Processing | 28 |
| abstract_inverted_index.Structural | 0 |
| abstract_inverted_index.algorithm. | 71 |
| abstract_inverted_index.eliminated | 122 |
| abstract_inverted_index.monitoring | 2, 25, 31, 60, 80, 93 |
| abstract_inverted_index.processing | 157 |
| abstract_inverted_index.regression | 178 |
| abstract_inverted_index.Measurement | 14 |
| abstract_inverted_index.distinguish | 134 |
| abstract_inverted_index.performance | 152, 190 |
| abstract_inverted_index.reliability | 43 |
| abstract_inverted_index.displacement | 59 |
| abstract_inverted_index.manipulation | 67 |
| abstract_inverted_index.binarization. | 125 |
| abstract_inverted_index.respectively. | 180 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 99 |
| corresponding_author_ids | https://openalex.org/A5100723437 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 7 |
| corresponding_institution_ids | https://openalex.org/I2799850029 |
| citation_normalized_percentile.value | 0.98950903 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |