Performance evaluation of prototype‐based clustering algorithms combined MDL index

Clustering algorithms are used to group data depending on a distance. Best clustering analysis should be resisting the presence of outliers, less sensitive to initialization as well as the input sequence ordering. This article compares the performance among three of prototype‐based unsupervised clus...

Full description

Saved in:
Bibliographic Details
Published inComputer applications in engineering education Vol. 25; no. 4; pp. 642 - 654
Main Authors Aljobouri, Hadeel K., Jaber, Hussain A., Çankaya, Ilyas
Format Journal Article
LanguageEnglish
Published Hoboken Wiley Subscription Services, Inc 01.07.2017
Subjects
Online AccessGet full text
ISSN1061-3773
1099-0542
DOI10.1002/cae.21824

Cover

Abstract Clustering algorithms are used to group data depending on a distance. Best clustering analysis should be resisting the presence of outliers, less sensitive to initialization as well as the input sequence ordering. This article compares the performance among three of prototype‐based unsupervised clustering algorithms: Neural Gas (NG), Growing Neural Gas (GNG) and Robust Growing Neural Gas (RGNG). Based on NG and GNG, there are different clustering algorithms proposed and suggested in different literatures. So, in this work a comparison between the two basic clustering algorithms NG and GNG have presented using the performance evaluation of these techniques, in contrast to the RGNG which was proposed within the GNG. Another comparison due to the MDL criterion between RGNG that used MDL value as the clustering validity index, versus GNG and NG combined with MDL. Statistical estimations are applied to explain the meaning of the output results when these algorithms fed to the synthetic 2D dataset. Moreover, a simple software package is designed and implemented as an automatic clustering model for any dataset to use as a part of the neural network course. NG, GNG and RGNG algorithms are performed in the same package using a MATLAB‐based Graphical User Interface (GUI) tool. This visual tool lets the students/ researchers visualize the desired results using plots also clicking a few buttons.
AbstractList Clustering algorithms are used to group data depending on a distance. Best clustering analysis should be resisting the presence of outliers, less sensitive to initialization as well as the input sequence ordering. This article compares the performance among three of prototype-based unsupervised clustering algorithms: Neural Gas (NG), Growing Neural Gas (GNG) and Robust Growing Neural Gas (RGNG). Based on NG and GNG, there are different clustering algorithms proposed and suggested in different literatures. So, in this work a comparison between the two basic clustering algorithms NG and GNG have presented using the performance evaluation of these techniques, in contrast to the RGNG which was proposed within the GNG. Another comparison due to the MDL criterion between RGNG that used MDL value as the clustering validity index, versus GNG and NG combined with MDL. Statistical estimations are applied to explain the meaning of the output results when these algorithms fed to the synthetic 2D dataset. Moreover, a simple software package is designed and implemented as an automatic clustering model for any dataset to use as a part of the neural network course. NG, GNG and RGNG algorithms are performed in the same package using a MATLAB-based Graphical User Interface (GUI) tool. This visual tool lets the students/ researchers visualize the desired results using plots also clicking a few buttons.
Author Jaber, Hussain A.
Çankaya, Ilyas
Aljobouri, Hadeel K.
Author_xml – sequence: 1
  givenname: Hadeel K.
  orcidid: 0000-0003-1792-9230
  surname: Aljobouri
  fullname: Aljobouri, Hadeel K.
  email: hadeel_bme77@yahoo.com
  organization: Al‐Nahrain University
– sequence: 2
  givenname: Hussain A.
  surname: Jaber
  fullname: Jaber, Hussain A.
  organization: Ankara Yıldırım Beyazıt University
– sequence: 3
  givenname: Ilyas
  surname: Çankaya
  fullname: Çankaya, Ilyas
  organization: Ankara Yıldırım Beyazıt University
BookMark eNp9kEtOwzAQhi1UJNrCghtEYsUirR9xkyyrUh5SESzK2nKccXGV2MVOgO44AmfkJKQtKyRYzUjz_TOjb4B61llA6JzgEcGYjpWEESUZTY5Qn-A8jzFPaG_XT0jM0pSdoEEIa4xxPmF5Hy0fwWvna2kVRPAqq1Y2xtnI6WjjXeOa7Qa-Pj4LGaCMVNWGBryxq0hWK-dN81yHSLm6MLYb318tImNLeD9Fx1pWAc5-6hA9Xc-Xs9t48XBzN5suYkXzNIklB1VqJbWUqkh0ynKpQOepZLJUmeaYU655ynXCICNFxoCXVHGtcKK0LjgboovD3u7VlxZCI9au9bY7KUhOccJTnO6oywOlvAvBgxYbb2rpt4JgsZMmOmliL61jx79YZZq9kcZLU_2XeDMVbP9eLWbT-SHxDW5ggvA
CitedBy_id crossref_primary_10_1016_j_jneumeth_2018_02_007
Cites_doi 10.1109/72.238311
10.1145/331499.331504
10.1016/j.patcog.2004.12.007
10.1109/ICSMC.1996.569812
10.1109/3477.678640
10.1007/978-1-4471-2063-6_104
10.1016/S0893-6080(04)00166-2
10.1007/978-3-642-56927-2
10.1017/CBO9780511812651
10.1007/b106267
10.1109/72.728377
10.1007/978-3-319-11179-7_12
10.1016/0893-6080(94)90091-4
10.1016/S0893-6080(03)00102-3
10.1007/BF01908075
10.1016/j.neunet.2006.05.018
ContentType Journal Article
Copyright 2017 Wiley Periodicals, Inc.
Copyright_xml – notice: 2017 Wiley Periodicals, Inc.
DBID AAYXX
CITATION
7SC
7TB
8FD
FR3
JQ2
KR7
L7M
L~C
L~D
DOI 10.1002/cae.21824
DatabaseName CrossRef
Computer and Information Systems Abstracts
Mechanical & Transportation Engineering Abstracts
Technology Research Database
Engineering Research Database
ProQuest Computer Science Collection
Civil Engineering Abstracts
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
DatabaseTitle CrossRef
Civil Engineering Abstracts
Technology Research Database
Computer and Information Systems Abstracts – Academic
Mechanical & Transportation Engineering Abstracts
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
Engineering Research Database
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts Professional
DatabaseTitleList Civil Engineering Abstracts

DeliveryMethod fulltext_linktorsrc
Discipline Engineering
EISSN 1099-0542
EndPage 654
ExternalDocumentID 10_1002_cae_21824
CAE21824
Genre reviewArticle
GroupedDBID .3N
.DC
.GA
.Y3
05W
0R~
10A
1L6
1OB
1OC
31~
33P
3SF
3WU
4.4
50Y
50Z
51W
51X
52M
52N
52O
52P
52S
52T
52U
52W
52X
5GY
5VS
66C
6TJ
702
7PT
8-0
8-1
8-3
8-4
8-5
8UM
930
A03
AAESR
AAEVG
AAHQN
AAHSB
AAMMB
AAMNL
AANHP
AANLZ
AAONW
AASGY
AAXRX
AAYCA
AAZKR
ABCQN
ABCUV
ABEML
ABIJN
ABJNI
ABPVW
ACAHQ
ACBWZ
ACCZN
ACGFS
ACIWK
ACPOU
ACRPL
ACSCC
ACXBN
ACXQS
ACYXJ
ADBBV
ADEOM
ADIZJ
ADKYN
ADMGS
ADMLS
ADNMO
ADOZA
ADXAS
ADZMN
AEFGJ
AEIGN
AEIMD
AENEX
AEUYR
AEYWJ
AFBPY
AFFNX
AFFPM
AFGKR
AFWVQ
AFZJQ
AGHNM
AGQPQ
AGXDD
AGYGG
AHBTC
AIDQK
AIDYY
AIQQE
AITYG
AIURR
AJXKR
ALAGY
ALMA_UNASSIGNED_HOLDINGS
ALUQN
ALVPJ
AMBMR
AMYDB
ASPBG
ATUGU
AUFTA
AVWKF
AZBYB
AZFZN
AZVAB
BAFTC
BDRZF
BFHJK
BHBCM
BMNLL
BMXJE
BNHUX
BROTX
BRXPI
BY8
CMOOK
CS3
D-E
D-F
DCZOG
DPXWK
DR2
DRFUL
DRSTM
DU5
EBS
EJD
F00
F01
F04
FEDTE
G-S
G.N
GNP
GODZA
H.T
H.X
HF~
HGLYW
HVGLF
HZ~
IX1
J0M
JPC
KQQ
LATKE
LAW
LC2
LC3
LEEKS
LH4
LITHE
LOXES
LP6
LP7
LUTES
LW6
LYRES
MEWTI
MK4
MRFUL
MRSTM
MSFUL
MSSTM
MXFUL
MXSTM
N04
N05
N9A
NF~
O66
O9-
OIG
P2P
P2W
P2X
P4D
PALCI
PQQKQ
Q.N
Q11
QB0
QRW
R.K
RIWAO
RJQFR
ROL
RX1
RYL
SAMSI
SUPJJ
TN5
UB1
W8V
W99
WBKPD
WIH
WIK
WLBEL
WOHZO
WQJ
WXSBR
WYISQ
XG1
XPP
XV2
ZZTAW
~IA
~WT
AAYXX
CITATION
7SC
7TB
8FD
FR3
JQ2
KR7
L7M
L~C
L~D
ID FETCH-LOGICAL-c2974-a5ecdfcafaacb4f739acef97a3adc8f50525f575f43e81b83e5d2c5fc04cffb53
IEDL.DBID DR2
ISSN 1061-3773
IngestDate Sun Jul 13 04:42:55 EDT 2025
Thu Apr 24 22:51:16 EDT 2025
Wed Oct 01 06:00:17 EDT 2025
Sun Sep 21 06:21:15 EDT 2025
IsPeerReviewed true
IsScholarly true
Issue 4
Language English
License http://onlinelibrary.wiley.com/termsAndConditions#vor
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c2974-a5ecdfcafaacb4f739acef97a3adc8f50525f575f43e81b83e5d2c5fc04cffb53
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ORCID 0000-0003-1792-9230
PQID 1920457075
PQPubID 2045172
PageCount 13
ParticipantIDs proquest_journals_1920457075
crossref_primary_10_1002_cae_21824
crossref_citationtrail_10_1002_cae_21824
wiley_primary_10_1002_cae_21824_CAE21824
ProviderPackageCode CITATION
AAYXX
PublicationCentury 2000
PublicationDate July 2017
2017-07-00
20170701
PublicationDateYYYYMMDD 2017-07-01
PublicationDate_xml – month: 07
  year: 2017
  text: July 2017
PublicationDecade 2010
PublicationPlace Hoboken
PublicationPlace_xml – name: Hoboken
PublicationTitle Computer applications in engineering education
PublicationYear 2017
Publisher Wiley Subscription Services, Inc
Publisher_xml – name: Wiley Subscription Services, Inc
References 2015; 1
1998; 28
2015; 5
1985; 2
1998
1997
1996
2006; 19
2003; 16
1993
2003
2002
1991
1993; 4
1999
1995; 7
2016; 4
2001
2000
2004; 17
2007; 4
1999; 31
1996; 1
2014
2005; 38
1998; 9
1994; 7
e_1_2_6_10_1
e_1_2_6_31_1
e_1_2_6_30_1
e_1_2_6_19_1
Martinetz T. (e_1_2_6_23_1) 1991
e_1_2_6_13_1
e_1_2_6_14_1
Ignazio L. (e_1_2_6_18_1) 2007; 4
e_1_2_6_17_1
e_1_2_6_15_1
Haykin S. (e_1_2_6_16_1) 1998
e_1_2_6_21_1
e_1_2_6_20_1
Alziarjawey H. A. J. (e_1_2_6_4_1) 2016; 4
e_1_2_6_8_1
e_1_2_6_5_1
Fritzke B. (e_1_2_6_11_1) 1995
e_1_2_6_7_1
Alziarjawey H. A. (e_1_2_6_3_1) 2015; 5
e_1_2_6_6_1
e_1_2_6_25_1
e_1_2_6_24_1
e_1_2_6_2_1
Duda R. O. (e_1_2_6_9_1) 2000
e_1_2_6_22_1
e_1_2_6_29_1
e_1_2_6_28_1
e_1_2_6_27_1
Fritzke B. (e_1_2_6_12_1) 1997
e_1_2_6_26_1
References_xml – volume: 5
  start-page: 311
  year: 2015
  end-page: 316
  article-title: Heart rate monitoring and PQRST detection based on graphical user interface with Matlab
  publication-title: IJIEE.
– volume: 4
  start-page: 558
  year: 1993
  end-page: 569
  article-title: “Neural gas” network for vector quantization and its application to time series prediction
  publication-title: IEEE Trans. Neural. Netw.
– volume: 19
  start-page: 762
  year: 2006
  end-page: 771
  article-title: Batch and median neural gas
  publication-title: Neural. Netw.
– volume: 17
  start-page: 1135
  year: 2004
  end-page: 1148
  article-title: Robust growing neural gas algorithm with application in cluster analysis
  publication-title: Neural. Netw., Elsevier Ltd.
– start-page: 89
  year: 2014
  end-page: 96
– year: 2001
– year: 2003
– volume: 1
  start-page: 432
  year: 1996
  end-page: 437
– year: 2000
– year: 1996
– volume: 2
  start-page: 193
  year: 1985
  end-page: 218
  article-title: Comparing partitions
  publication-title: J. Class.
– start-page: 137
  year: 1999
  end-page: 143
– year: 1998
– volume: 9
  start-page: 1279
  year: 1998
  end-page: 1291
  article-title: Comparing neural networks: A benchmark on growing neural gas, growing cell structures, and fuzzy ARTMAP
  publication-title: IEEE Trans. Neural. Netw.
– volume: 7
  start-page: 1441
  year: 1994
  end-page: 1460
  article-title: Growing cells structures—A self‐organizing network for unsupervised and supervised learning
  publication-title: Neural. Netw.
– volume: 16
  start-page: 633
  year: 2003
  end-page: 640
  article-title: Adaptive double self‐organizing maps for clustering gene expression profiles
  publication-title: Neural. Netw.
– volume: 1
  start-page: 2380
  year: 2015
  end-page: 8128
– volume: 7
  start-page: 625
  year: 1995
  end-page: 632
– volume: 4
  start-page: 31
  year: 2007
  end-page: 50
  article-title: Evolutionary Neural Gas (ENG): A model of self organizing network from input categorization
  publication-title: EJTP.
– year: 2002
– year: 1997
– volume: 31
  start-page: 264
  year: 1999
  end-page: 323
  article-title: Data clustering: A Review
  publication-title: ACM Comput. Surv. (CSUR)
– volume: 28
  start-page: 427
  year: 1998
  end-page: 436
  article-title: Conceptual clustering in information retrieval
  publication-title: IEEE Trans. Syst. Man. Cybern. Part B
– year: 1991
– volume: 38
  start-page: 1275
  year: 2005
  end-page: 1288
  article-title: Enhanced neural gas network for prototype‐based clustering
  publication-title: Pattern Recognition, Elsevier Ltd.
– start-page: 427
  year: 1993
  end-page: 434
– volume: 4
  start-page: 428
  year: 2016
  end-page: 433
  article-title: Design graphical user interface of linear algebra system package by using MATLAB
  publication-title: IJRITCC.
– year: 1999
– volume: 4
  start-page: 428
  year: 2016
  ident: e_1_2_6_4_1
  article-title: Design graphical user interface of linear algebra system package by using MATLAB
  publication-title: IJRITCC.
– ident: e_1_2_6_25_1
  doi: 10.1109/72.238311
– volume: 5
  start-page: 311
  year: 2015
  ident: e_1_2_6_3_1
  article-title: Heart rate monitoring and PQRST detection based on graphical user interface with Matlab
  publication-title: IJIEE.
– ident: e_1_2_6_31_1
– ident: e_1_2_6_19_1
  doi: 10.1145/331499.331504
– ident: e_1_2_6_27_1
  doi: 10.1016/j.patcog.2004.12.007
– volume-title: Pattern Classification
  year: 2000
  ident: e_1_2_6_9_1
– ident: e_1_2_6_20_1
  doi: 10.1109/ICSMC.1996.569812
– ident: e_1_2_6_28_1
– volume-title: A “neural gas“ network learns topologies
  year: 1991
  ident: e_1_2_6_23_1
– start-page: 625
  volume-title: A Growing Neural Gas Network Learns Topologies
  year: 1995
  ident: e_1_2_6_11_1
– ident: e_1_2_6_7_1
  doi: 10.1109/3477.678640
– volume: 4
  start-page: 31
  year: 2007
  ident: e_1_2_6_18_1
  article-title: Evolutionary Neural Gas (ENG): A model of self organizing network from input categorization
  publication-title: EJTP.
– ident: e_1_2_6_24_1
  doi: 10.1007/978-1-4471-2063-6_104
– ident: e_1_2_6_26_1
  doi: 10.1016/S0893-6080(04)00166-2
– volume-title: Neural Networks: A Comprehensive Foundation
  year: 1998
  ident: e_1_2_6_16_1
– ident: e_1_2_6_5_1
– ident: e_1_2_6_21_1
  doi: 10.1007/978-3-642-56927-2
– ident: e_1_2_6_2_1
– ident: e_1_2_6_30_1
  doi: 10.1017/CBO9780511812651
– ident: e_1_2_6_6_1
  doi: 10.1007/b106267
– ident: e_1_2_6_13_1
– ident: e_1_2_6_8_1
  doi: 10.1109/72.728377
– ident: e_1_2_6_14_1
  doi: 10.1007/978-3-319-11179-7_12
– ident: e_1_2_6_10_1
  doi: 10.1016/0893-6080(94)90091-4
– ident: e_1_2_6_29_1
  doi: 10.1016/S0893-6080(03)00102-3
– volume-title: Some Competitive Learning Methods (Draft)
  year: 1997
  ident: e_1_2_6_12_1
– ident: e_1_2_6_17_1
  doi: 10.1007/BF01908075
– ident: e_1_2_6_15_1
– ident: e_1_2_6_22_1
  doi: 10.1016/j.neunet.2006.05.018
SSID ssj0009639
Score 2.0623758
SecondaryResourceType review_article
Snippet Clustering algorithms are used to group data depending on a distance. Best clustering analysis should be resisting the presence of outliers, less sensitive to...
SourceID proquest
crossref
wiley
SourceType Aggregation Database
Enrichment Source
Index Database
Publisher
StartPage 642
SubjectTerms Algorithms
Cluster analysis
Clustering
clustering techniques
Data analysis
Graphical user interface
Graphical User Interface (GUI)
Growing Neural Gas (GNG)
Neural Gas (NG)
Neural networks
Outliers (statistics)
Performance evaluation
Robust Growing Neural Gas (RGNG)
Title Performance evaluation of prototype‐based clustering algorithms combined MDL index
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fcae.21824
https://www.proquest.com/docview/1920457075
Volume 25
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVEBS
  databaseName: Inspec with Full Text
  customDbUrl:
  eissn: 1099-0542
  dateEnd: 20241105
  omitProxy: false
  ssIdentifier: ssj0009639
  issn: 1061-3773
  databaseCode: ADMLS
  dateStart: 19940101
  isFulltext: true
  titleUrlDefault: https://www.ebsco.com/products/research-databases/inspec-full-text
  providerName: EBSCOhost
– providerCode: PRVWIB
  databaseName: Wiley Online Library - Core collection (SURFmarket)
  issn: 1061-3773
  databaseCode: DR2
  dateStart: 19960101
  customDbUrl:
  isFulltext: true
  eissn: 1099-0542
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0009639
  providerName: Wiley-Blackwell
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ1NS8MwGMfD8KQH38XplCAevHTrmqYveBpzY4gTkQ12EEqaFxXnKlt38eRH8DP6SXyStusUBfFW2qRN8yTN_0nz_ILQaaxYwKTXtGjs2ZYbwhHjMbEEZRqnTgPP1oHC_WuvN3QvR3RUQedFLEzGh1hMuOmeYb7XuoOzeNYooaGcybrGj2sWaJN4xp26LdFR0LBC86dTz6_4PimoQrbTWOT8OhaVAnNZpppxpruB7ooSZstLnurzNK7z12_wxn--wiZaz_UnbmUNZgtV5GQbrS1RCXfQ4KYMJsAlDRwnCmuqQ6JnbT_e3vX4JzAfzzVqATJiNr5Ppo_pw_MMQ0HA44bL_YsrbICMu2jY7QzaPSvffMHiDvgYFqOSC8WZYmA7V_kkZFyq0GeECR4os_-dAq2nXCJB-gZEUuFwqrjtcqViSvbQyiSZyH2EacyUB-fBe-KuECFjkro6hjcUgjhUVNFZYYaI52RyvUHGOMqYyk4EFRWZiqqik0XSlwzH8VOiWmHLKO-RswiULKhXHxQSPM4Y5fcbRO1Wxxwc_D3pIVp19IhvVvLW0Eo6ncsj0CtpfGwa5ieugukv
linkProvider Wiley-Blackwell
linkToHtml http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ1NT8IwGMefIB7Ug-9GfG2MBy9D3NqNJV6MQlCBGAOJF7N0fVEjgkG4ePIj-Bn9JD7tGEOjifG2bO3W9WnXf5_1-RVgP9a8zJV_5LDYLzk0xCMuYs-RjBucOiv7JRMo3Gj6tTa9uGE3OThOY2ESPsTY4WZ6hv1emw5uHNKHGTVUcFU0_HE6BdPUx3mKkUTXGTwKm1Zo_3UaD0sQeClXqOQejrN-HY0yiTkpVO1IU12A27SMyQKTx-JwEBfF6zd8439fYhHmRxKUnCRtZglyqrsMcxNgwhVoXWXxBCQDgpOeJgbs0DOO24-3dzMESiI6Q0NbwIyEd-56_YfB_dMLwZLgpBsvN87qxDIZV6FdrbROa85o_wVHuDjNcDhTQmrBNUfzUR14IRdKhwH3uBRlbbfA0yj3NPUUqt-yp5h0BdOiRIXWMfPWIN_tddU6EBZz7eN5nEAJKmXIuWLUhPGGUnoukwU4SO0QiRGc3OyR0YkSrLIbYUVFtqIKsDdO-pwQOX5KtJUaMxp1ypcIxSwK2ABFEj7OWuX3G0SnJxV7sPH3pLswU2s16lH9vHm5CbOuEQB2Ye8W5Af9odpG-TKId2wr_QRHH-1Q
linkToPdf http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ1bS8MwFMcPOkH0wbs4nRrEB186Z5v0Ar4M5_CyicgGvkhJc1FxbuK2F5_8CH5GP4kn6bqqKIhvpU3aNCfp-SfN-QVgN9E85Mo_cFjiVxwa4REXiedIxg1OnYV-xQQKNy_8kzY9u2bXE3CYxcKkfIjxhJvpGfZ7bTq4epJ6P6eGCq7Khj9OJ2GKsig0C_pqVzk8CptWZP91mhmWIPAyrlDF3R9n_eqNcon5WahaT1Ofh5usjOkCk4fycJCUxcs3fON_X2IB5kYSlFTTNrMIE6q7BLOfwITL0LrM4wlIDgQnPU0M2KFnJm7fX9-MC5REdIaGtoAZCe_c9p7vB3ePfYIlwUE3Xm7WGsQyGVegXT9uHZ04o_0XHOHiMMPhTAmpBdcczUd14EVcKB0F3ONShNpugadR7mnqKVS_oaeYdAXTokKF1gnzVqHQ7XXVGhCWcO3jeRxACSplxLli1ITxRlJ6LpNF2MvsEIsRnNzskdGJU6yyG2NFxbaiirAzTvqUEjl-SlTKjBmPOmU_RjGLAjZAkYSPs1b5_QbxUfXYHqz_Pek2TF_W6nHj9OJ8A2Zc4__tut4SFAbPQ7WJ6mWQbNlG-gEJnOzU
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=Performance+evaluation+of+prototype%E2%80%90based+clustering+algorithms+combined+MDL+index&rft.jtitle=Computer+applications+in+engineering+education&rft.au=Aljobouri%2C+Hadeel+K.&rft.au=Jaber%2C+Hussain+A.&rft.au=%C3%87ankaya%2C+Ilyas&rft.date=2017-07-01&rft.issn=1061-3773&rft.eissn=1099-0542&rft.volume=25&rft.issue=4&rft.spage=642&rft.epage=654&rft_id=info:doi/10.1002%2Fcae.21824&rft.externalDBID=10.1002%252Fcae.21824&rft.externalDocID=CAE21824
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1061-3773&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1061-3773&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1061-3773&client=summon