Dynamic modeling and performance evaluation of piezoelectric impact drive system based on neural network Article Swipe
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1088/1361-6501/ace63e
In metrology and industrial design, the evaluation of measurement uncertainty and error is crucial to the measurement process. The Guide to the Expression of Uncertainty in Measurement and its supplementary documents have established a unified framework and standard for evaluating measurement uncertainty. However, a reasonable method for evaluating dynamic measurement uncertainty has not yet been proposed. By analyzing the dynamic measurement system, and using the long short-term memory time neural network to model the nonlinear dynamics represented by a piezoelectric drive platform, this paper evaluates the system’s dynamic measurement uncertainty through deep integration methods. Bayesian theory is used to propagate probability densities, and experimental results demonstrate the effectiveness of this method for assessing dynamic measurement uncertainty.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1088/1361-6501/ace63e
- OA Status
- hybrid
- Cited By
- 4
- References
- 67
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4383894968
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4383894968Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1088/1361-6501/ace63eDigital Object Identifier
- Title
-
Dynamic modeling and performance evaluation of piezoelectric impact drive system based on neural networkWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-07-11Full publication date if available
- Authors
-
Wenhao Chen, Haojie Xia, Rencheng Song, Chengliang PanList of authors in order
- Landing page
-
https://doi.org/10.1088/1361-6501/ace63ePublisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.1088/1361-6501/ace63eDirect OA link when available
- Concepts
-
Measurement uncertainty, Computer science, Metrology, Artificial neural network, Dynamic Bayesian network, Nonlinear system, System of measurement, Process (computing), Bayesian probability, Uncertainty analysis, Expression (computer science), Sensitivity analysis, Observational error, Machine learning, Artificial intelligence, Simulation, Mathematics, Statistics, Astronomy, Physics, Quantum mechanics, Programming language, Operating systemTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2024: 1Per-year citation counts (last 5 years)
- References (count)
-
67Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4383894968 |
|---|---|
| doi | https://doi.org/10.1088/1361-6501/ace63e |
| ids.doi | https://doi.org/10.1088/1361-6501/ace63e |
| ids.openalex | https://openalex.org/W4383894968 |
| fwci | 1.75820917 |
| type | article |
| title | Dynamic modeling and performance evaluation of piezoelectric impact drive system based on neural network |
| biblio.issue | 10 |
| biblio.volume | 34 |
| biblio.last_page | 105021 |
| biblio.first_page | 105021 |
| topics[0].id | https://openalex.org/T12564 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9930999875068665 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1705 |
| topics[0].subfield.display_name | Computer Networks and Communications |
| topics[0].display_name | Sensor Technology and Measurement Systems |
| topics[1].id | https://openalex.org/T10876 |
| topics[1].field.id | https://openalex.org/fields/22 |
| topics[1].field.display_name | Engineering |
| topics[1].score | 0.9878000020980835 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2207 |
| topics[1].subfield.display_name | Control and Systems Engineering |
| topics[1].display_name | Fault Detection and Control Systems |
| topics[2].id | https://openalex.org/T12111 |
| topics[2].field.id | https://openalex.org/fields/22 |
| topics[2].field.display_name | Engineering |
| topics[2].score | 0.9865999817848206 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/2209 |
| topics[2].subfield.display_name | Industrial and Manufacturing Engineering |
| topics[2].display_name | Industrial Vision Systems and Defect Detection |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C137209882 |
| concepts[0].level | 2 |
| concepts[0].score | 0.7014986276626587 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q1403517 |
| concepts[0].display_name | Measurement uncertainty |
| concepts[1].id | https://openalex.org/C41008148 |
| concepts[1].level | 0 |
| concepts[1].score | 0.6871848702430725 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[1].display_name | Computer science |
| concepts[2].id | https://openalex.org/C195766429 |
| concepts[2].level | 2 |
| concepts[2].score | 0.6548768281936646 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q394 |
| concepts[2].display_name | Metrology |
| concepts[3].id | https://openalex.org/C50644808 |
| concepts[3].level | 2 |
| concepts[3].score | 0.6149744987487793 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q192776 |
| concepts[3].display_name | Artificial neural network |
| concepts[4].id | https://openalex.org/C82142266 |
| concepts[4].level | 3 |
| concepts[4].score | 0.5748682022094727 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q3456604 |
| concepts[4].display_name | Dynamic Bayesian network |
| concepts[5].id | https://openalex.org/C158622935 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5645906329154968 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q660848 |
| concepts[5].display_name | Nonlinear system |
| concepts[6].id | https://openalex.org/C37649242 |
| concepts[6].level | 2 |
| concepts[6].score | 0.5582903027534485 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q932268 |
| concepts[6].display_name | System of measurement |
| concepts[7].id | https://openalex.org/C98045186 |
| concepts[7].level | 2 |
| concepts[7].score | 0.5481749176979065 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q205663 |
| concepts[7].display_name | Process (computing) |
| concepts[8].id | https://openalex.org/C107673813 |
| concepts[8].level | 2 |
| concepts[8].score | 0.4709666073322296 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q812534 |
| concepts[8].display_name | Bayesian probability |
| concepts[9].id | https://openalex.org/C177803969 |
| concepts[9].level | 2 |
| concepts[9].score | 0.4605267643928528 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q29205 |
| concepts[9].display_name | Uncertainty analysis |
| concepts[10].id | https://openalex.org/C90559484 |
| concepts[10].level | 2 |
| concepts[10].score | 0.43766695261001587 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q778379 |
| concepts[10].display_name | Expression (computer science) |
| concepts[11].id | https://openalex.org/C176147448 |
| concepts[11].level | 3 |
| concepts[11].score | 0.42841485142707825 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q1889114 |
| concepts[11].display_name | Sensitivity analysis |
| concepts[12].id | https://openalex.org/C19619285 |
| concepts[12].level | 2 |
| concepts[12].score | 0.41657111048698425 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q196372 |
| concepts[12].display_name | Observational error |
| concepts[13].id | https://openalex.org/C119857082 |
| concepts[13].level | 1 |
| concepts[13].score | 0.27946290373802185 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[13].display_name | Machine learning |
| concepts[14].id | https://openalex.org/C154945302 |
| concepts[14].level | 1 |
| concepts[14].score | 0.23289573192596436 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[14].display_name | Artificial intelligence |
| concepts[15].id | https://openalex.org/C44154836 |
| concepts[15].level | 1 |
| concepts[15].score | 0.21055510640144348 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q45045 |
| concepts[15].display_name | Simulation |
| concepts[16].id | https://openalex.org/C33923547 |
| concepts[16].level | 0 |
| concepts[16].score | 0.10348665714263916 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[16].display_name | Mathematics |
| concepts[17].id | https://openalex.org/C105795698 |
| concepts[17].level | 1 |
| concepts[17].score | 0.09809896349906921 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[17].display_name | Statistics |
| concepts[18].id | https://openalex.org/C1276947 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q333 |
| concepts[18].display_name | Astronomy |
| concepts[19].id | https://openalex.org/C121332964 |
| concepts[19].level | 0 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q413 |
| concepts[19].display_name | Physics |
| concepts[20].id | https://openalex.org/C62520636 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q944 |
| concepts[20].display_name | Quantum mechanics |
| concepts[21].id | https://openalex.org/C199360897 |
| concepts[21].level | 1 |
| concepts[21].score | 0.0 |
| concepts[21].wikidata | https://www.wikidata.org/wiki/Q9143 |
| concepts[21].display_name | Programming language |
| concepts[22].id | https://openalex.org/C111919701 |
| concepts[22].level | 1 |
| concepts[22].score | 0.0 |
| concepts[22].wikidata | https://www.wikidata.org/wiki/Q9135 |
| concepts[22].display_name | Operating system |
| keywords[0].id | https://openalex.org/keywords/measurement-uncertainty |
| keywords[0].score | 0.7014986276626587 |
| keywords[0].display_name | Measurement uncertainty |
| keywords[1].id | https://openalex.org/keywords/computer-science |
| keywords[1].score | 0.6871848702430725 |
| keywords[1].display_name | Computer science |
| keywords[2].id | https://openalex.org/keywords/metrology |
| keywords[2].score | 0.6548768281936646 |
| keywords[2].display_name | Metrology |
| keywords[3].id | https://openalex.org/keywords/artificial-neural-network |
| keywords[3].score | 0.6149744987487793 |
| keywords[3].display_name | Artificial neural network |
| keywords[4].id | https://openalex.org/keywords/dynamic-bayesian-network |
| keywords[4].score | 0.5748682022094727 |
| keywords[4].display_name | Dynamic Bayesian network |
| keywords[5].id | https://openalex.org/keywords/nonlinear-system |
| keywords[5].score | 0.5645906329154968 |
| keywords[5].display_name | Nonlinear system |
| keywords[6].id | https://openalex.org/keywords/system-of-measurement |
| keywords[6].score | 0.5582903027534485 |
| keywords[6].display_name | System of measurement |
| keywords[7].id | https://openalex.org/keywords/process |
| keywords[7].score | 0.5481749176979065 |
| keywords[7].display_name | Process (computing) |
| keywords[8].id | https://openalex.org/keywords/bayesian-probability |
| keywords[8].score | 0.4709666073322296 |
| keywords[8].display_name | Bayesian probability |
| keywords[9].id | https://openalex.org/keywords/uncertainty-analysis |
| keywords[9].score | 0.4605267643928528 |
| keywords[9].display_name | Uncertainty analysis |
| keywords[10].id | https://openalex.org/keywords/expression |
| keywords[10].score | 0.43766695261001587 |
| keywords[10].display_name | Expression (computer science) |
| keywords[11].id | https://openalex.org/keywords/sensitivity-analysis |
| keywords[11].score | 0.42841485142707825 |
| keywords[11].display_name | Sensitivity analysis |
| keywords[12].id | https://openalex.org/keywords/observational-error |
| keywords[12].score | 0.41657111048698425 |
| keywords[12].display_name | Observational error |
| keywords[13].id | https://openalex.org/keywords/machine-learning |
| keywords[13].score | 0.27946290373802185 |
| keywords[13].display_name | Machine learning |
| keywords[14].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[14].score | 0.23289573192596436 |
| keywords[14].display_name | Artificial intelligence |
| keywords[15].id | https://openalex.org/keywords/simulation |
| keywords[15].score | 0.21055510640144348 |
| keywords[15].display_name | Simulation |
| keywords[16].id | https://openalex.org/keywords/mathematics |
| keywords[16].score | 0.10348665714263916 |
| keywords[16].display_name | Mathematics |
| keywords[17].id | https://openalex.org/keywords/statistics |
| keywords[17].score | 0.09809896349906921 |
| keywords[17].display_name | Statistics |
| language | en |
| locations[0].id | doi:10.1088/1361-6501/ace63e |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S109302362 |
| locations[0].source.issn | 0957-0233, 1361-6501 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | 0957-0233 |
| locations[0].source.is_core | True |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | Measurement Science and Technology |
| 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-nc-nd |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by-nc-nd |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | Measurement Science and Technology |
| locations[0].landing_page_url | https://doi.org/10.1088/1361-6501/ace63e |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5016509762 |
| authorships[0].author.orcid | https://orcid.org/0000-0001-9031-9266 |
| authorships[0].author.display_name | Wenhao Chen |
| authorships[0].countries | CN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I16365422 |
| authorships[0].affiliations[0].raw_affiliation_string | Hefei University of Technology, Rm 309, Keji Building, 193 Tunxi Road, Hefei, Anhui, China, Hefei, Anhui, 230009, CHINA |
| authorships[0].institutions[0].id | https://openalex.org/I16365422 |
| authorships[0].institutions[0].ror | https://ror.org/02czkny70 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I16365422 |
| authorships[0].institutions[0].country_code | CN |
| authorships[0].institutions[0].display_name | Hefei University of Technology |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Wenhao Chen |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Hefei University of Technology, Rm 309, Keji Building, 193 Tunxi Road, Hefei, Anhui, China, Hefei, Anhui, 230009, CHINA |
| authorships[1].author.id | https://openalex.org/A5015159167 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-4214-7233 |
| authorships[1].author.display_name | Haojie Xia |
| authorships[1].countries | CN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I16365422 |
| authorships[1].affiliations[0].raw_affiliation_string | School of Instrumental Science and Optoelectronic Engineering, Hefei University of Technology, Rm 309, Keji Building, 193 Tunxi Road, Hefei, Anhui, China, Hefei, Anhui, 230009, CHINA |
| authorships[1].institutions[0].id | https://openalex.org/I16365422 |
| authorships[1].institutions[0].ror | https://ror.org/02czkny70 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I16365422 |
| authorships[1].institutions[0].country_code | CN |
| authorships[1].institutions[0].display_name | Hefei University of Technology |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Haojie Xia |
| authorships[1].is_corresponding | True |
| authorships[1].raw_affiliation_strings | School of Instrumental Science and Optoelectronic Engineering, Hefei University of Technology, Rm 309, Keji Building, 193 Tunxi Road, Hefei, Anhui, China, Hefei, Anhui, 230009, CHINA |
| authorships[2].author.id | https://openalex.org/A5082889047 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-7760-7562 |
| authorships[2].author.display_name | Rencheng Song |
| authorships[2].countries | CN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I16365422 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Biomedical Engineering, Hefei University of Technology, Rm 309, Keji Building, 193 Tunxi Road, Hefei, Anhui, China, Hefei, 230009, CHINA |
| authorships[2].institutions[0].id | https://openalex.org/I16365422 |
| authorships[2].institutions[0].ror | https://ror.org/02czkny70 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I16365422 |
| authorships[2].institutions[0].country_code | CN |
| authorships[2].institutions[0].display_name | Hefei University of Technology |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Rencheng Song |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Biomedical Engineering, Hefei University of Technology, Rm 309, Keji Building, 193 Tunxi Road, Hefei, Anhui, China, Hefei, 230009, CHINA |
| authorships[3].author.id | https://openalex.org/A5101952144 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-6785-5842 |
| authorships[3].author.display_name | Chengliang Pan |
| authorships[3].countries | CN |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I16365422 |
| authorships[3].affiliations[0].raw_affiliation_string | School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Rm 309, Keji Building, 193 Tunxi Road, Hefei, Anhui, China, Hefei, Anhui, 230009, CHINA |
| authorships[3].institutions[0].id | https://openalex.org/I16365422 |
| authorships[3].institutions[0].ror | https://ror.org/02czkny70 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I16365422 |
| authorships[3].institutions[0].country_code | CN |
| authorships[3].institutions[0].display_name | Hefei University of Technology |
| authorships[3].author_position | last |
| authorships[3].raw_author_name | Chengliang Pan |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | School of Instrument Science and Opto-Electronics Engineering, Hefei University of Technology, Rm 309, Keji Building, 193 Tunxi Road, Hefei, Anhui, China, Hefei, Anhui, 230009, 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/10.1088/1361-6501/ace63e |
| open_access.oa_status | hybrid |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Dynamic modeling and performance evaluation of piezoelectric impact drive system based on neural network |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12564 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9930999875068665 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1705 |
| primary_topic.subfield.display_name | Computer Networks and Communications |
| primary_topic.display_name | Sensor Technology and Measurement Systems |
| related_works | https://openalex.org/W4205181462, https://openalex.org/W3212153563, https://openalex.org/W2376953431, https://openalex.org/W4312671192, https://openalex.org/W2387053421, https://openalex.org/W2607177949, https://openalex.org/W4386584851, https://openalex.org/W2037453698, https://openalex.org/W2143770134, https://openalex.org/W1973084747 |
| cited_by_count | 4 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 3 |
| counts_by_year[1].year | 2024 |
| counts_by_year[1].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1088/1361-6501/ace63e |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S109302362 |
| best_oa_location.source.issn | 0957-0233, 1361-6501 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | 0957-0233 |
| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | Measurement Science and Technology |
| 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-nc-nd |
| 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-nc-nd |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | Measurement Science and Technology |
| best_oa_location.landing_page_url | https://doi.org/10.1088/1361-6501/ace63e |
| primary_location.id | doi:10.1088/1361-6501/ace63e |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S109302362 |
| primary_location.source.issn | 0957-0233, 1361-6501 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | 0957-0233 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | Measurement Science and Technology |
| 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-nc-nd |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by-nc-nd |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | Measurement Science and Technology |
| primary_location.landing_page_url | https://doi.org/10.1088/1361-6501/ace63e |
| publication_date | 2023-07-11 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W2301797350, https://openalex.org/W4391197160, https://openalex.org/W4398234980, https://openalex.org/W4226174253, https://openalex.org/W2238304350, https://openalex.org/W2088199580, https://openalex.org/W6798726245, https://openalex.org/W4220766707, https://openalex.org/W4323645038, https://openalex.org/W2018862569, https://openalex.org/W3001499077, https://openalex.org/W3217347337, https://openalex.org/W2964231206, https://openalex.org/W3006587156, https://openalex.org/W3131408648, https://openalex.org/W3019166713, https://openalex.org/W3046973519, https://openalex.org/W3137041295, https://openalex.org/W4283065713, https://openalex.org/W3156461423, https://openalex.org/W3012107403, https://openalex.org/W6838745333, https://openalex.org/W4205941964, https://openalex.org/W3093963267, https://openalex.org/W4292065146, https://openalex.org/W4210470089, https://openalex.org/W4313480672, https://openalex.org/W4321523753, https://openalex.org/W3199010298, https://openalex.org/W3036979535, https://openalex.org/W4281249352, https://openalex.org/W3199699713, https://openalex.org/W4322737601, https://openalex.org/W6767628997, https://openalex.org/W6752745768, https://openalex.org/W6754205108, https://openalex.org/W6764715812, https://openalex.org/W6763120240, https://openalex.org/W6730042731, https://openalex.org/W6767433472, https://openalex.org/W6795941766, https://openalex.org/W2080451948, https://openalex.org/W4361272213, https://openalex.org/W2168434855, https://openalex.org/W2151052089, https://openalex.org/W3171782203, https://openalex.org/W2014044259, https://openalex.org/W2045810824, https://openalex.org/W3014596384, https://openalex.org/W2064675550, https://openalex.org/W4210912956, https://openalex.org/W6737664043, https://openalex.org/W6674914833, https://openalex.org/W3163993681, https://openalex.org/W3171029090, https://openalex.org/W2950338985, https://openalex.org/W4284712117, https://openalex.org/W2969913432, https://openalex.org/W2952816888, https://openalex.org/W4287083725, https://openalex.org/W4287167695, https://openalex.org/W3035711539, https://openalex.org/W2963238274, https://openalex.org/W2806471870, https://openalex.org/W3134774296, https://openalex.org/W4297775537, https://openalex.org/W2097117768 |
| referenced_works_count | 67 |
| abstract_inverted_index.a | 34, 44, 79 |
| abstract_inverted_index.By | 57 |
| abstract_inverted_index.In | 1 |
| abstract_inverted_index.by | 78 |
| abstract_inverted_index.in | 26 |
| abstract_inverted_index.is | 13, 97 |
| abstract_inverted_index.of | 8, 24, 109 |
| abstract_inverted_index.to | 15, 21, 72, 99 |
| abstract_inverted_index.The | 19 |
| abstract_inverted_index.and | 3, 11, 28, 37, 63, 103 |
| abstract_inverted_index.for | 39, 47, 112 |
| abstract_inverted_index.has | 52 |
| abstract_inverted_index.its | 29 |
| abstract_inverted_index.not | 53 |
| abstract_inverted_index.the | 6, 16, 22, 59, 65, 74, 86, 107 |
| abstract_inverted_index.yet | 54 |
| abstract_inverted_index.been | 55 |
| abstract_inverted_index.deep | 92 |
| abstract_inverted_index.have | 32 |
| abstract_inverted_index.long | 66 |
| abstract_inverted_index.this | 83, 110 |
| abstract_inverted_index.time | 69 |
| abstract_inverted_index.used | 98 |
| abstract_inverted_index.Guide | 20 |
| abstract_inverted_index.drive | 81 |
| abstract_inverted_index.error | 12 |
| abstract_inverted_index.model | 73 |
| abstract_inverted_index.paper | 84 |
| abstract_inverted_index.using | 64 |
| abstract_inverted_index.memory | 68 |
| abstract_inverted_index.method | 46, 111 |
| abstract_inverted_index.neural | 70 |
| abstract_inverted_index.theory | 96 |
| abstract_inverted_index.crucial | 14 |
| abstract_inverted_index.design, | 5 |
| abstract_inverted_index.dynamic | 49, 60, 88, 114 |
| abstract_inverted_index.network | 71 |
| abstract_inverted_index.results | 105 |
| abstract_inverted_index.system, | 62 |
| abstract_inverted_index.through | 91 |
| abstract_inverted_index.unified | 35 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.Bayesian | 95 |
| abstract_inverted_index.However, | 43 |
| abstract_inverted_index.dynamics | 76 |
| abstract_inverted_index.methods. | 94 |
| abstract_inverted_index.process. | 18 |
| abstract_inverted_index.standard | 38 |
| abstract_inverted_index.analyzing | 58 |
| abstract_inverted_index.assessing | 113 |
| abstract_inverted_index.documents | 31 |
| abstract_inverted_index.evaluates | 85 |
| abstract_inverted_index.framework | 36 |
| abstract_inverted_index.metrology | 2 |
| abstract_inverted_index.nonlinear | 75 |
| abstract_inverted_index.platform, | 82 |
| abstract_inverted_index.propagate | 100 |
| abstract_inverted_index.proposed. | 56 |
| abstract_inverted_index.Expression | 23 |
| abstract_inverted_index.densities, | 102 |
| abstract_inverted_index.evaluating | 40, 48 |
| abstract_inverted_index.evaluation | 7 |
| abstract_inverted_index.industrial | 4 |
| abstract_inverted_index.reasonable | 45 |
| abstract_inverted_index.short-term | 67 |
| abstract_inverted_index.system’s | 87 |
| abstract_inverted_index.Measurement | 27 |
| abstract_inverted_index.Uncertainty | 25 |
| abstract_inverted_index.demonstrate | 106 |
| abstract_inverted_index.established | 33 |
| abstract_inverted_index.integration | 93 |
| abstract_inverted_index.measurement | 9, 17, 41, 50, 61, 89, 115 |
| abstract_inverted_index.probability | 101 |
| abstract_inverted_index.represented | 77 |
| abstract_inverted_index.uncertainty | 10, 51, 90 |
| abstract_inverted_index.experimental | 104 |
| abstract_inverted_index.uncertainty. | 42, 116 |
| abstract_inverted_index.effectiveness | 108 |
| abstract_inverted_index.piezoelectric | 80 |
| abstract_inverted_index.supplementary | 30 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5015159167 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 4 |
| corresponding_institution_ids | https://openalex.org/I16365422 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.4300000071525574 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.75651087 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |