A Method for Predicting Inertial Navigation System Positioning Errors Using a Back Propagation Neural Network Based on a Particle Swarm Optimization Algorithm

In order to reduce the position errors of the Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) integrated navigation system during GPS denial, this paper proposes a method based on the Particle Swarm Optimization–Back Propagation Neural Network (PSO-BPNN) to replace the GPS...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Sensors (Basel, Switzerland) Ročník 24; číslo 12; s. 3722
Hlavní autoři: Wang, Yabo, Jiao, Ruihan, Wei, Tingxiao, Guo, Zhaoxing, Ben, Yueyang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland MDPI AG 07.06.2024
MDPI
Témata:
Accuracy
Algorithms
Artificial intelligence
backpropagation neural network
Fuzzy logic
GPS denial
GPS/SINS integrated navigation system
Kalman filters
Navigation systems
Neural networks
Optimization
particle swarm optimization
Propagation
Velocity
GPS/SINS integrated navigation system
backpropagation neural network
particle swarm optimization
GPS denial
ISSN:1424-8220, 1424-8220
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Abstract In order to reduce the position errors of the Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) integrated navigation system during GPS denial, this paper proposes a method based on the Particle Swarm Optimization–Back Propagation Neural Network (PSO-BPNN) to replace the GPS for positioning. The model relates the position information, velocity information, attitude information output by the SINS, and the navigation time to the position errors between the position information output by the SINS and the actual position information. The performance of the model is compared with the BPNN through an actual ship experiment. The results show that the PSO-BPNN can obviously reduce the position errors in the case of GPS signal denial.
AbstractList In order to reduce the position errors of the Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) integrated navigation system during GPS denial, this paper proposes a method based on the Particle Swarm Optimization–Back Propagation Neural Network (PSO-BPNN) to replace the GPS for positioning. The model relates the position information, velocity information, attitude information output by the SINS, and the navigation time to the position errors between the position information output by the SINS and the actual position information. The performance of the model is compared with the BPNN through an actual ship experiment. The results show that the PSO-BPNN can obviously reduce the position errors in the case of GPS signal denial.
In order to reduce the position errors of the Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) integrated navigation system during GPS denial, this paper proposes a method based on the Particle Swarm Optimization-Back Propagation Neural Network (PSO-BPNN) to replace the GPS for positioning. The model relates the position information, velocity information, attitude information output by the SINS, and the navigation time to the position errors between the position information output by the SINS and the actual position information. The performance of the model is compared with the BPNN through an actual ship experiment. The results show that the PSO-BPNN can obviously reduce the position errors in the case of GPS signal denial.In order to reduce the position errors of the Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) integrated navigation system during GPS denial, this paper proposes a method based on the Particle Swarm Optimization-Back Propagation Neural Network (PSO-BPNN) to replace the GPS for positioning. The model relates the position information, velocity information, attitude information output by the SINS, and the navigation time to the position errors between the position information output by the SINS and the actual position information. The performance of the model is compared with the BPNN through an actual ship experiment. The results show that the PSO-BPNN can obviously reduce the position errors in the case of GPS signal denial.
Author Jiao, Ruihan
Guo, Zhaoxing
Wang, Yabo
Ben, Yueyang
Wei, Tingxiao
AuthorAffiliation 2 School of Intelligent Science and Engineer, Harbin Engineering University, Harbin 150001, China; wtx15776482665@163.com (T.W.); gzx13946003678@outloook.com (Z.G.); byy@hrbeu.edu.cn (Y.B.)
1 Wuhan Second Ship Research and Design Institute, Wuhan 430205, China; 18007195551m@sina.cn
AuthorAffiliation_xml – name: 2 School of Intelligent Science and Engineer, Harbin Engineering University, Harbin 150001, China; wtx15776482665@163.com (T.W.); gzx13946003678@outloook.com (Z.G.); byy@hrbeu.edu.cn (Y.B.)
– name: 1 Wuhan Second Ship Research and Design Institute, Wuhan 430205, China; 18007195551m@sina.cn
Author_xml – sequence: 1
  givenname: Yabo
  surname: Wang
  fullname: Wang, Yabo
– sequence: 2
  givenname: Ruihan
  surname: Jiao
  fullname: Jiao, Ruihan
– sequence: 3
  givenname: Tingxiao
  surname: Wei
  fullname: Wei, Tingxiao
– sequence: 4
  givenname: Zhaoxing
  surname: Guo
  fullname: Guo, Zhaoxing
– sequence: 5
  givenname: Yueyang
  surname: Ben
  fullname: Ben, Yueyang
BackLink https://www.ncbi.nlm.nih.gov/pubmed/38931505$$D View this record in MEDLINE/PubMed
BookMark eNplks1u1DAUhSNURH9gwQsgS2xgMdSxnTheoaEqMFJpRypdWx77JuNpEk9tp1V5GJ4VZ2ZatWVl-95zPx0d38Nsr3c9ZNn7HH-hVODjQFhOKCfkVXaQM8ImFSF478l9PzsMYYUxoZRWb7J9WgmaF7g4yP5O0S-IS2dQ7TyaezBWR9s3aNaDj1a16Fzd2kZF63p0eR8idGjugh3fo-zUe-cDugrjQ6FvSl8nilur3cg5DH6EQLxz_jr1AxiU6grNVeLrFtDlnfIdulhH29k_26lp2zhv47J7m72uVRvg3e48yq6-n_4--Tk5u_gxO5meTTTjOE7AGEp5URvAtFYagDGhTcFrIByqktdYCFUKvCgLA4bpgtS45FpwBVCCKuhRNttyjVMrufa2U_5eOmXlpuB8I3d2ZWEEJ8wwkiJkC1aLslQsBY3rAkMOIrG-blnrYdGB0dDHFMEz6PNOb5eycbcyzwnmVcUT4dOO4N3NACHKzgYNbat6cEOQFHNS5bTMqyT9-EK6coPvU1YbFadYlCPww1NLj14e9iAJjrcC7V0IHmqpbdz8RXJoW5ljOW6afNy0NPH5xcQD9H_tP6BB1L0
CitedBy_id crossref_primary_10_3390_s25165214
crossref_primary_10_3390_jmse13061007
crossref_primary_10_3389_fbioe_2025_1619411
crossref_primary_10_1109_ACCESS_2025_3596116
crossref_primary_10_3390_electronics14051035
crossref_primary_10_3390_app14135849
crossref_primary_10_3390_e27060591
Cites_doi 10.1109/BigCom51056.2020.00036
10.1017/S0373463318000760
10.1016/S0925-2312(01)00702-0
10.1109/TVT.2015.2497713
10.1109/ITNEC48623.2020.9085154
10.3390/s18103470
10.1109/JSEN.2016.2642040
10.5081/jgps.4.1.192
10.3390/s21041149
10.3390/aerospace7080115
10.1088/1742-6596/1732/1/012189
10.1109/ACCESS.2019.2922212
ContentType Journal Article
Copyright 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
2024 by the authors. 2024
Copyright_xml – notice: 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
– notice: 2024 by the authors. 2024
DBID AAYXX
CITATION
NPM
3V.
7X7
7XB
88E
8FI
8FJ
8FK
ABUWG
AFKRA
AZQEC
BENPR
CCPQU
DWQXO
FYUFA
GHDGH
K9.
M0S
M1P
PHGZM
PHGZT
PIMPY
PJZUB
PKEHL
PPXIY
PQEST
PQQKQ
PQUKI
PRINS
7X8
5PM
DOA
DOI 10.3390/s24123722
DatabaseName CrossRef
PubMed
ProQuest Central (Corporate)
Health & Medical Collection (ProQuest)
ProQuest Central (purchase pre-March 2016)
Medical Database (Alumni Edition)
Hospital Premium Collection
Hospital Premium Collection (Alumni Edition)
ProQuest Central (Alumni) (purchase pre-March 2016)
ProQuest Central (Alumni)
ProQuest Central UK/Ireland
ProQuest Central Essentials
ProQuest Central
ProQuest One Community College
ProQuest Central Korea
Health Research Premium Collection
Health Research Premium Collection (Alumni)
ProQuest Health & Medical Complete (Alumni)
ProQuest Health & Medical Collection
Medical Database
ProQuest Central Premium
ProQuest One Academic (New)
Publicly Available Content Database
ProQuest Health & Medical Research Collection
ProQuest One Academic Middle East (New)
ProQuest One Health & Nursing
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
MEDLINE - Academic
PubMed Central (Full Participant titles)
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
PubMed
Publicly Available Content Database
ProQuest One Academic Middle East (New)
ProQuest Central Essentials
ProQuest Health & Medical Complete (Alumni)
ProQuest Central (Alumni Edition)
ProQuest One Community College
ProQuest One Health & Nursing
ProQuest Central China
ProQuest Central
ProQuest Health & Medical Research Collection
Health Research Premium Collection
Health and Medicine Complete (Alumni Edition)
ProQuest Central Korea
Health & Medical Research Collection
ProQuest Central (New)
ProQuest Medical Library (Alumni)
ProQuest One Academic Eastern Edition
ProQuest Hospital Collection
Health Research Premium Collection (Alumni)
ProQuest Hospital Collection (Alumni)
ProQuest Health & Medical Complete
ProQuest Medical Library
ProQuest One Academic UKI Edition
ProQuest One Academic
ProQuest One Academic (New)
ProQuest Central (Alumni)
MEDLINE - Academic
DatabaseTitleList

Publicly Available Content Database
PubMed
CrossRef
MEDLINE - Academic
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: NPM
  name: PubMed
  url: http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed
  sourceTypes: Index Database
– sequence: 3
  dbid: PIMPY
  name: Publicly Available Content Database
  url: http://search.proquest.com/publiccontent
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1424-8220
ExternalDocumentID oai_doaj_org_article_5d9724d429314b4f966a44240f50e1e9
PMC11207887
38931505
10_3390_s24123722
Genre Journal Article
GrantInformation_xml – fundername: Natural Science Foundation of Heilongjiang Province of China
  grantid: YQ2021E011
– fundername: Natural Science Foundation of Hubei Province of China
  grantid: 2022CFB865
– fundername: National Natural Science Foundation of China
  grantid: 51979047
GroupedDBID ---
123
2WC
53G
5VS
7X7
88E
8FE
8FG
8FI
8FJ
AADQD
AAHBH
AAYXX
ABDBF
ABUWG
ACUHS
ADBBV
ADMLS
AENEX
AFFHD
AFKRA
AFZYC
ALMA_UNASSIGNED_HOLDINGS
BENPR
BPHCQ
BVXVI
CCPQU
CITATION
CS3
D1I
DU5
E3Z
EBD
ESX
F5P
FYUFA
GROUPED_DOAJ
GX1
HH5
HMCUK
HYE
IAO
ITC
KQ8
L6V
M1P
M48
MODMG
M~E
OK1
OVT
P2P
P62
PHGZM
PHGZT
PIMPY
PJZUB
PPXIY
PQQKQ
PROAC
PSQYO
RNS
RPM
TUS
UKHRP
XSB
~8M
3V.
ABJCF
ALIPV
ARAPS
HCIFZ
KB.
M7S
NPM
PDBOC
7XB
8FK
AZQEC
DWQXO
K9.
PKEHL
PQEST
PQUKI
PRINS
7X8
5PM
ID FETCH-LOGICAL-c470t-edd3375fde03facee449cd57fe27e867f099a690b65ded4c52f067c97aee6ea53
IEDL.DBID DOA
ISICitedReferencesCount 10
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001256667900001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1424-8220
IngestDate Fri Oct 03 12:52:23 EDT 2025
Tue Nov 04 02:05:23 EST 2025
Sun Nov 09 13:41:50 EST 2025
Tue Oct 07 07:32:05 EDT 2025
Wed Feb 19 02:06:45 EST 2025
Sat Nov 29 07:10:22 EST 2025
Tue Nov 18 22:30:40 EST 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 12
Keywords GPS/SINS integrated navigation system
backpropagation neural network
particle swarm optimization
GPS denial
Language English
License Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c470t-edd3375fde03facee449cd57fe27e867f099a690b65ded4c52f067c97aee6ea53
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
OpenAccessLink https://doaj.org/article/5d9724d429314b4f966a44240f50e1e9
PMID 38931505
PQID 3072730967
PQPubID 2032333
ParticipantIDs doaj_primary_oai_doaj_org_article_5d9724d429314b4f966a44240f50e1e9
pubmedcentral_primary_oai_pubmedcentral_nih_gov_11207887
proquest_miscellaneous_3072813618
proquest_journals_3072730967
pubmed_primary_38931505
crossref_citationtrail_10_3390_s24123722
crossref_primary_10_3390_s24123722
PublicationCentury 2000
PublicationDate 20240607
PublicationDateYYYYMMDD 2024-06-07
PublicationDate_xml – month: 6
  year: 2024
  text: 20240607
  day: 7
PublicationDecade 2020
PublicationPlace Switzerland
PublicationPlace_xml – name: Switzerland
– name: Basel
PublicationTitle Sensors (Basel, Switzerland)
PublicationTitleAlternate Sensors (Basel)
PublicationYear 2024
Publisher MDPI AG
MDPI
Publisher_xml – name: MDPI AG
– name: MDPI
References Jaradat (ref_6) 2017; 17
Yan (ref_14) 2021; 1732
Badu (ref_3) 2005; 4
Li (ref_1) 2016; 65
Milad (ref_19) 2020; 7
Zhang (ref_9) 2019; 72
ref_10
ref_21
ref_20
Wang (ref_12) 2008; 5
Yang (ref_7) 2014; 4
Zhang (ref_11) 2003; 50
ref_2
ref_18
Chen (ref_4) 2020; 3
ref_16
ref_15
Liu (ref_17) 2021; 126
ref_5
Cao (ref_8) 2009; 30
Wang (ref_13) 2019; 7
References_xml – ident: ref_16
  doi: 10.1109/BigCom51056.2020.00036
– volume: 72
  start-page: 375
  year: 2019
  ident: ref_9
  article-title: A hybrid intelligent algorithm DGP-MLP for GNSS/INS integration during GNSS outages
  publication-title: Navigation
  doi: 10.1017/S0373463318000760
– volume: 50
  start-page: 159
  year: 2003
  ident: ref_11
  article-title: Time series forecasting using a hybrid ARIMA and neural network model
  publication-title: Neurocomputing
  doi: 10.1016/S0925-2312(01)00702-0
– volume: 65
  start-page: 7791
  year: 2016
  ident: ref_1
  article-title: Transversal strapdown INS based on reference ellipsoid for vehicle in the polar region
  publication-title: IEEE Trans. Veh. Technol.
  doi: 10.1109/TVT.2015.2497713
– ident: ref_10
– ident: ref_15
  doi: 10.1109/ITNEC48623.2020.9085154
– ident: ref_2
  doi: 10.3390/s18103470
– volume: 17
  start-page: 1105
  year: 2017
  ident: ref_6
  article-title: Non-linear autoregressive delay-dependent INS/GPS navigation system using neural networks
  publication-title: IEEE Sens.
  doi: 10.1109/JSEN.2016.2642040
– volume: 4
  start-page: 192
  year: 2005
  ident: ref_3
  article-title: Comparative study of interpolation techniques for ultra-tight integration of GPS/INS/PL sensors
  publication-title: J. Glob. Position. Syst.
  doi: 10.5081/jgps.4.1.192
– volume: 5
  start-page: 489
  year: 2008
  ident: ref_12
  article-title: Application of BP Neural Network in the Transfer Alignment of Inertial Navigation System
  publication-title: J. Nav. Aeronaut. Eng. Coll.
– ident: ref_5
  doi: 10.3390/s21041149
– volume: 7
  start-page: 115
  year: 2020
  ident: ref_19
  article-title: Unsupervised anomaly detection in flight data using convolutional variational auto-encoder
  publication-title: Aerospace
  doi: 10.3390/aerospace7080115
– ident: ref_18
– volume: 126
  start-page: 1
  year: 2021
  ident: ref_17
  article-title: Integrated navigation on vehicle based on low-cost SINS/GNSS using Deep Learning
  publication-title: Wirel. Pers. Commun.
– volume: 1732
  start-page: 012189
  year: 2021
  ident: ref_14
  article-title: Research on master-slave filtering of Celestial Navigation System/Inertial Navigation System
  publication-title: J. Phys. Conf. Ser.
  doi: 10.1088/1742-6596/1732/1/012189
– ident: ref_21
– ident: ref_20
– volume: 4
  start-page: 222
  year: 2014
  ident: ref_7
  article-title: Model Predictive Forward Neural Network Algorithm and Its Application in Integrated Navigation
  publication-title: J. Inert. Technol. China
– volume: 3
  start-page: 110
  year: 2020
  ident: ref_4
  article-title: Design of Strapdown Inertial Navigation System Based on MEMS
  publication-title: Acad. J. Comput. Inf. Sci.
– volume: 30
  start-page: 2231
  year: 2009
  ident: ref_8
  article-title: Research on the Error Feedback Correction Method of MEMS-SINS Based on Neural Network Prediction During GPS Signal Loss
  publication-title: J. Astronaut.
– volume: 7
  start-page: 82134
  year: 2019
  ident: ref_13
  article-title: A Novel BPNN-Based Method to Overcome the GPS Outages for INS/GPS System
  publication-title: IEEE Access
  doi: 10.1109/ACCESS.2019.2922212
SSID ssj0023338
Score 2.4960606
Snippet In order to reduce the position errors of the Global Positioning System/Strapdown Inertial Navigation System (GPS/SINS) integrated navigation system during GPS...
SourceID doaj
pubmedcentral
proquest
pubmed
crossref
SourceType Open Website
Open Access Repository
Aggregation Database
Index Database
Enrichment Source
StartPage 3722
SubjectTerms Accuracy
Algorithms
Artificial intelligence
backpropagation neural network
Fuzzy logic
GPS denial
GPS/SINS integrated navigation system
Kalman filters
Navigation systems
Neural networks
Optimization
particle swarm optimization
Propagation
Velocity
SummonAdditionalLinks – databaseName: Health & Medical Collection (ProQuest)
  dbid: 7X7
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwEB5B4QAH3oVAQQZx4BI160fsnNAWtQIJlpV4aG-RYzttRTcpybb8G34rY8ebdlHFhWvsRJP4y8w38eQbgNdZVSn0gUXKuLIpN1anyIqyVOmcUaExJwk7pt8_ytlMLRbFPH5w62NZ5donBkdtW-O_ke8iFjHSIuGWb09_pr5rlN9djS00rsMN3zbb41wuLhIuhvnXoCbEMLXf7TFaUSYp3YhBQar_Kn75d5nkpbhzcPd_Lb4HdyLjJNMBIvfhmmsewO1LOoQP4feUfAqdpAlSWDLv_OaNL4cmHxpfdo1nz_R50OJoGzJonJN5rPby0_a7ru16EsoPiCZ72vzAq2A6Hk_xCiD-IkPJOY73zhI8rsk8Ipd8-aW7JfmMDmwZ_wwl05NDvJ3V0fIRfDvY__rufRobN6SGy2yVOmsZk6K2LmO1xjDMeWGskLWj0iE0aqSlGtPyKhfWWW4ErTFomkJq53KnBduGraZt3BMgnAtOK1vkJleIJFXVSGCR0iokosJkVQJv1ktZmqhq7ptrnJSY3fhVL8dVT-DVOPV0kPK4atKex8M4watvhwNtd1jGR1IKW0jKLYZyNuEVrzFl1JwjN0Lj3MQVCeysEVFGl9CXF3BI4OU4jC-z36HRjWvPhjlqwvKJSuDxAL7REs8skb2LBNQGLDdM3Rxpjo-CYDhy6sxXjT79t13P4BZFyhYK4eQObK26M_ccbprz1XHfvQiv1h9wuDDg
  priority: 102
  providerName: ProQuest
Title A Method for Predicting Inertial Navigation System Positioning Errors Using a Back Propagation Neural Network Based on a Particle Swarm Optimization Algorithm
URI https://www.ncbi.nlm.nih.gov/pubmed/38931505
https://www.proquest.com/docview/3072730967
https://www.proquest.com/docview/3072813618
https://pubmed.ncbi.nlm.nih.gov/PMC11207887
https://doaj.org/article/5d9724d429314b4f966a44240f50e1e9
Volume 24
WOSCitedRecordID wos001256667900001&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 1424-8220
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0023338
  issn: 1424-8220
  databaseCode: DOA
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources (ISSN International Center)
  customDbUrl:
  eissn: 1424-8220
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0023338
  issn: 1424-8220
  databaseCode: M~E
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
– providerCode: PRVPQU
  databaseName: Health & Medical Collection (ProQuest)
  customDbUrl:
  eissn: 1424-8220
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0023338
  issn: 1424-8220
  databaseCode: 7X7
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: https://search.proquest.com/healthcomplete
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central Database Suite (ProQuest)
  customDbUrl:
  eissn: 1424-8220
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0023338
  issn: 1424-8220
  databaseCode: BENPR
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: Publicly Available Content Database
  customDbUrl:
  eissn: 1424-8220
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0023338
  issn: 1424-8220
  databaseCode: PIMPY
  dateStart: 20010101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/publiccontent
  providerName: ProQuest
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV1Lj9MwEB7BwoE9IN4ElsogDlyiTWM7do4t6oqVaIl4qZwix3bYim2ySrrLjZ_Cb2XspFGLVuLCxQd7HDmesecbefwZ4HVUFBL3wDSkTJqQaaNCREVRKFVCY64wJvEnpl_fi8VCLpdptvPUl8sJ6-iBu4k75iYVMTO4bdIxK1iJ8Fwxhn6o5JEdW391LxLpNpjqQy2KkVfHI0QxqD9u0U_FVMTxnvfxJP3XIcu_EyR3PM7JPbjbQ0Uy6YZ4H27Y6gEc7hAIPoTfEzL3T0ATxJ4ka9ypi8tjJqeVy5fG3gt15Uk06op05OQk69O0nNisaeqmJT5vgCgyVfoHfgXj6L6Lo-5wH-lyxbG9tYZgvSJZP3Pk00_VrMkH3HnW_ZVOMjn_Xjerzdn6EXw5mX1--y7sX1wINRPRJrTGUCp4aWxES4X-k7FUGy5KGwuLOi0RTyqMp4uEG2uY5nGJ3k6nQlmbWMXpYzio6so-BcIYZ3Fh0kQnEk1AFqgvgVhUIoLkOioCeLPVRK57OnL3KsZ5jmGJU1o-KC2AV4PoRcfBcZ3Q1KlzEHC02b4CjSnvpyT_lzEFcLQ1hrxfy22OuyBiPAz1RAAvh2Zche5oRVW2vuxk5JgmYxnAk852hpE4SIiwmwcg96xqb6j7LdXqzDN9IxiOXLrns__xc8_hToyIzOe5iSM42DSX9gXc1lebVduM4KZYCl_KEdyazhbZx5FfU1jOf82wLjudZ9_-AFPvJ88
linkProvider Directory of Open Access Journals
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3NbtQwEB5VBQk4lH8IFDAIJC5Rs7YTJweEttCqq26XlShob6ljO23VblKSbStehkfgGRk72bSLKm49cI0n0cj5ZuabeDID8DbIshh9YOIzHmufKy19ZEWBH8uI0VBiTuJOTL8PxWgUTybJeAl-z_-FsWWVc5_oHLUulf1GvoZYxEiLhFt8PPnh26lR9nR1PkKjgcW2-XmOKVv9YfAZ3-87Sjc3dj9t-e1UAV9xEcx8ozVjIsy1CVguMUZwnigditxQYVDvHDmTxJwxi0JtNFchzdGjq0RIYyIj7ZQIdPk30I8Lm-yJyUWCxzDfa7oXMZYEazVGR8oEpQsxz40GuIrP_l2WeSnObd7933boHqy0jJr0GxO4D0umeAB3LvVZfAi_-mTHTcomSNHJuLKHU7bcmwwKW1aOd4_kmes1Uhak6eFOxm01mxXbqKqyqokrryCSrEt1hE8p0Rc3t9gOJ_YhTUk9rtdGE7wuybi1TPL1XFZT8gUd9LT985X0j_dx-2YH00fw7Vo26DEsF2VhngLhPOQ000mkohgtJc5yJOhI2WMk2qEKMg_ez6GTqrZrux0ecpxi9mZRlnYo8-BNJ3rStCq5Smjd4q8TsN3F3YWy2k_bLUlDnQjKNUKc9XjGc0yJJefI_VA50zOJB6tzBKaty6vTC_h58LpbRmdlT6BkYcrTRibusagXe_CkAXuniWXOmJ2EHsQLZrCg6uJKcXjgGqJjzhDYqthn_9brFdza2t0ZpsPBaPs53KZIT13Rn1iF5Vl1al7ATXU2O6yrl86sCexdt5X8AeDhkUs
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1Lb9QwEB5VW4TgwPsRKGAQSFyizdrO64DQlnbFqu0SiYfaU3Bsp63oJiXZtuLP8EP4dYwTJ3RRxa0HrvEkcpx5fBN_ngF46WVZhD4wdhmPlMulEi6iIs-NRMCoLzAnaXZMv2yHs1m0uxsnK_CrOwtjaJWdT2wctSql-Uc-RF3ESIuAOxzmlhaRbEzeHn93TQcps9PatdNoVWRL_zjD9K1-M93Ab_2K0snmp3fvXdthwJU89BauVoqx0M-V9lguMF5wHkvlh7mmocZ3yBE_Ccwfs8BXWnHp0xy9u4xDoXWghekYge5_FSE5pwNYTaY7yV6f7jHM_tpaRozF3rDGWElZSOlSBGwaBVyEbv8maZ6LepOb__N63YIbFmuTcWsct2FFF3fg-rkKjHfh55jsND20CYJ3klRm28oQwcm0MIRzvHsmTpsqJGVB2uruJLE8NyO2WVVlVZOGeEEEWRfyGz6lRC_d3mJqn5iHtGR7HK-1InhdkMTaLPl4Jqo5-YCue27PxJLx0T4u3-Jgfg8-X8oC3YdBURb6IRDOfU4zFQcyiNCGoixH6I5gPkII7ksvc-B1p0aptPXcTVuRoxTzOqNxaa9xDrzoRY_bIiYXCa0bXewFTN3x5kJZ7ad2SVJfxSHlCkEMG_GM55gsC84RFeLk9EjHDqx12phaZ1inf1TRgef9MLoxszclCl2etDLRiAWjyIEHreL3MzGYGvMW34FoySSWpro8UhweNKXSMZvwDF_20b_n9QyuonGk29PZ1mO4RhG3NmzAcA0Gi-pEP4Er8nRxWFdPrY0T-HrZZvIbwnKbmg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=A+Method+for+Predicting+Inertial+Navigation+System+Positioning+Errors+Using+a+Back+Propagation+Neural+Network+Based+on+a+Particle+Swarm+Optimization+Algorithm&rft.jtitle=Sensors+%28Basel%2C+Switzerland%29&rft.au=Wang%2C+Yabo&rft.au=Jiao%2C+Ruihan&rft.au=Wei%2C+Tingxiao&rft.au=Guo%2C+Zhaoxing&rft.date=2024-06-07&rft.eissn=1424-8220&rft.volume=24&rft.issue=12&rft_id=info:doi/10.3390%2Fs24123722&rft_id=info%3Apmid%2F38931505&rft.externalDocID=38931505
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1424-8220&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1424-8220&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1424-8220&client=summon