-
1
-
-
78650683107
-
Interval set clustering
-
Chen M, Miao DQ (2011) Interval set clustering. Expert Syst Appl 38(4):2923–2932
-
(2011)
Expert Syst Appl
, vol.38
, Issue.4
, pp. 2923-2932
-
-
Chen, M.1
Miao, D.Q.2
-
2
-
-
84939887889
-
Double indices-induced FCM clustering and its integration with fuzzy subspace clustering
-
Wang J, Chung FL, Wang ST, Deng ZH (2013) Double indices-induced FCM clustering and its integration with fuzzy subspace clustering. Pattern Anal Appl 6:1433–7541
-
(2013)
Pattern Anal Appl
, vol.6
, pp. 1433-7541
-
-
Wang, J.1
Chung, F.L.2
Wang, S.T.3
Deng, Z.H.4
-
3
-
-
79958138920
-
A fuzzy K-means clustering algorithm using cluster center displacement
-
Chang CT, Lai JZ, Jeng MD (2011) A fuzzy K-means clustering algorithm using cluster center displacement. J Inf Sci Eng 27(3):995–1009
-
(2011)
J Inf Sci Eng
, vol.27
, Issue.3
, pp. 995-1009
-
-
Chang, C.T.1
Lai, J.Z.2
Jeng, M.D.3
-
4
-
-
84876899318
-
A powerful hybrid clustering method based on modified stem cells and Fuzzy C-means algorithms
-
Taherdangkoo M, Bagheri MH (2013) A powerful hybrid clustering method based on modified stem cells and Fuzzy C-means algorithms. Eng Appl Artif Intell 26(5–6):1493–1502
-
(2013)
Eng Appl Artif Intell
, vol.26
, Issue.5-6
, pp. 1493-1502
-
-
Taherdangkoo, M.1
Bagheri, M.H.2
-
5
-
-
78650267969
-
Using general regression with local tuning for learning mixture models from incomplete data sets
-
Abas AR (2010) Using general regression with local tuning for learning mixture models from incomplete data sets. Egypt Inform J 11(2):49–57
-
(2010)
Egypt Inform J
, vol.11
, Issue.2
, pp. 49-57
-
-
Abas, A.R.1
-
6
-
-
84866428315
-
Unsupervised learning of mixture models based on swarm intelligence and neural networks with optimal completion using incomplete data
-
Abas AR (2012) Unsupervised learning of mixture models based on swarm intelligence and neural networks with optimal completion using incomplete data. Egypt Inform J 13(2):103–109
-
(2012)
Egypt Inform J
, vol.13
, Issue.2
, pp. 103-109
-
-
Abas, A.R.1
-
7
-
-
84875402925
-
A selective Bayes classifier with meta-heuristics for incomplete data
-
Lin HC, Su CT (2013) A selective Bayes classifier with meta-heuristics for incomplete data. Neurocomputing 15(106):95–102
-
(2013)
Neurocomputing
, vol.15
, Issue.106
, pp. 95-102
-
-
Lin, H.C.1
Su, C.T.2
-
9
-
-
0018656141
-
Pattern recognition with partly missing data
-
Dixon JK (1979) Pattern recognition with partly missing data. IEEE Trans Syst Man Cybern 9(10):617–621
-
(1979)
IEEE Trans Syst Man Cybern
, vol.9
, Issue.10
, pp. 617-621
-
-
Dixon, J.K.1
-
10
-
-
79951578021
-
Missing data analysis with fuzzy C-means: a study of its application in a psychological scenario
-
Di Nuovo AG (2011) Missing data analysis with fuzzy C-means: a study of its application in a psychological scenario. Expert Syst Appl 38(6):6793–6797
-
(2011)
Expert Syst Appl
, vol.38
, Issue.6
, pp. 6793-6797
-
-
Di Nuovo, A.G.1
-
11
-
-
84875231751
-
A hybrid method for imputation of missing values using optimized fuzzy c-means with support vector regression and a genetic algorithm
-
Aydilek IB, Arslan A (2013) A hybrid method for imputation of missing values using optimized fuzzy c-means with support vector regression and a genetic algorithm. Inf Sci 233:25–35
-
(2013)
Inf Sci
, vol.233
, pp. 25-35
-
-
Aydilek, I.B.1
Arslan, A.2
-
12
-
-
84878866923
-
Clustering with missing values
-
Simiński K (2013) Clustering with missing values. Fundam Inform 123(3):331–350
-
(2013)
Fundam Inform
, vol.123
, Issue.3
, pp. 331-350
-
-
Simiński, K.1
-
13
-
-
77950217758
-
On classification with missing data using rough-neuro-fuzzy systems
-
Nowicki RK (2010) On classification with missing data using rough-neuro-fuzzy systems. Int J Appl Math Comput Sci 20(1):55–67
-
(2010)
Int J Appl Math Comput Sci
, vol.20
, Issue.1
, pp. 55-67
-
-
Nowicki, R.K.1
-
14
-
-
79960846725
-
A parametric GP model dealing with incomplete information for group decision-making
-
Dopazo E, Ruiz-Tagle M (2011) A parametric GP model dealing with incomplete information for group decision-making. Appl Math Comput 218(2):514–519
-
(2011)
Appl Math Comput
, vol.218
, Issue.2
, pp. 514-519
-
-
Dopazo, E.1
Ruiz-Tagle, M.2
-
15
-
-
84870066498
-
Rational decision making models with incomplete weight information for production line assessment
-
Pei Z (2012) Rational decision making models with incomplete weight information for production line assessment. Inf Sci 222(10):696–716
-
(2012)
Inf Sci
, vol.222
, Issue.10
, pp. 696-716
-
-
Pei, Z.1
-
16
-
-
77954868298
-
Fuzzy clustering of incomplete data based on cluster dispersion
-
Himmelspach L, Conrad S (2010) Fuzzy clustering of incomplete data based on cluster dispersion. Comput Intell Knowl Based Syst Des 6178:59–68
-
(2010)
Comput Intell Knowl Based Syst Des
, vol.6178
, pp. 59-68
-
-
Himmelspach, L.1
Conrad, S.2
-
17
-
-
78951483757
-
Missing data imputation by utilizing information within incomplete instances
-
Zhang SC, Jin Z, Zhu XF (2011) Missing data imputation by utilizing information within incomplete instances. J Syst Softw 84(3):452–459
-
(2011)
J Syst Softw
, vol.84
, Issue.3
, pp. 452-459
-
-
Zhang, S.C.1
Jin, Z.2
Zhu, X.F.3
-
18
-
-
79955463762
-
A new imputation method for incomplete binary data
-
Subasi MM, Subasi E, Anthony M, Hammer PL (2011) A new imputation method for incomplete binary data. Discrete Appl Math 159(10):1040–1047
-
(2011)
Discrete Appl Math
, vol.159
, Issue.10
, pp. 1040-1047
-
-
Subasi, M.M.1
Subasi, E.2
Anthony, M.3
Hammer, P.L.4
-
19
-
-
0036132613
-
Clustering incomplete relational data using the non-Euclidean relational fuzzy c-means algorithm
-
Hathaway RJ, Bezdek JC (2002) Clustering incomplete relational data using the non-Euclidean relational fuzzy c-means algorithm. Pattern Recogn Lett 23(1):151–160
-
(2002)
Pattern Recogn Lett
, vol.23
, Issue.1
, pp. 151-160
-
-
Hathaway, R.J.1
Bezdek, J.C.2
-
20
-
-
34547399424
-
An analysis of how training data complexity affects the nearest neighbor classifiers
-
Sánchez JS, Mollineda RA, Sotoca JM (2007) An analysis of how training data complexity affects the nearest neighbor classifiers. Pattern Anal Appl 10(3):189–201
-
(2007)
Pattern Anal Appl
, vol.10
, Issue.3
, pp. 189-201
-
-
Sánchez, J.S.1
Mollineda, R.A.2
Sotoca, J.M.3
-
21
-
-
78049231842
-
Data pre-processing through reward–punishment editing
-
Franco A, Maltoni D, Nanni L (2010) Data pre-processing through reward–punishment editing. Pattern Anal Appl 13(4):367–381
-
(2010)
Pattern Anal Appl
, vol.13
, Issue.4
, pp. 367-381
-
-
Franco, A.1
Maltoni, D.2
Nanni, L.3
-
22
-
-
84860237900
-
Feature selection with missing data using mutual information estimators
-
Doquire G, Verleysen M (2012) Feature selection with missing data using mutual information estimators. Neurocomputing 90:3–11
-
(2012)
Neurocomputing
, vol.90
, pp. 3-11
-
-
Doquire, G.1
Verleysen, M.2
-
23
-
-
84939923951
-
Incomplete-case nearest neighbor imputation in software measurement data. In: Proceedings of Information Sciences
-
Van Hulse J, Khoshgoftaar TM (2011) Incomplete-case nearest neighbor imputation in software measurement data. In: Proceedings of Information Sciences, pp 1–15
-
(2011)
pp 1–15
-
-
Van Hulse, J.1
Khoshgoftaar, T.M.2
-
24
-
-
78649930585
-
A fuzzy c-means clustering algorithm based on nearest-neighbor intervals for incomplete data
-
Li D, Gu H, Zhang L (2010) A fuzzy c-means clustering algorithm based on nearest-neighbor intervals for incomplete data. Expert Syst Appl 37(10):6942–6947
-
(2010)
Expert Syst Appl
, vol.37
, Issue.10
, pp. 6942-6947
-
-
Li, D.1
Gu, H.2
Zhang, L.3
-
25
-
-
78049527645
-
Fuzzy C-means and fuzzy swarm for fuzzy clustering problem
-
Izakian H, Abraham A (2011) Fuzzy C-means and fuzzy swarm for fuzzy clustering problem. Expert Syst Appl 38(3):1835–1838
-
(2011)
Expert Syst Appl
, vol.38
, Issue.3
, pp. 1835-1838
-
-
Izakian, H.1
Abraham, A.2
-
26
-
-
84882453404
-
Improved spatial fuzzy c-means clustering for image segmentation using PSO initialization, Mahalanobis distance and post-segmentation correction
-
Benaichouche AN, Oulhadj H, Siarry P (2013) Improved spatial fuzzy c-means clustering for image segmentation using PSO initialization, Mahalanobis distance and post-segmentation correction. Digit Signal Process 23(5):1390–1400
-
(2013)
Digit Signal Process
, vol.23
, Issue.5
, pp. 1390-1400
-
-
Benaichouche, A.N.1
Oulhadj, H.2
Siarry, P.3
-
27
-
-
84055224176
-
2 emissions in China: an improved fuzzy clustering analysis based on particle swarm optimization
-
2 emissions in China: an improved fuzzy clustering analysis based on particle swarm optimization. Appl Energy 92:552–562
-
(2012)
Appl Energy
, vol.92
, pp. 552-562
-
-
Yu, S.W.1
Wei, Y.M.2
Fan, J.L.3
Zhang, X.4
Wang, K.5
-
28
-
-
31944437793
-
Dynamic clustering using particle swarm optimization with application in image segmentation
-
Omran MG, Salman A, Engelbrecht AP (2006) Dynamic clustering using particle swarm optimization with application in image segmentation. Pattern Anal Appl 8(4):332–344
-
(2006)
Pattern Anal Appl
, vol.8
, Issue.4
, pp. 332-344
-
-
Omran, M.G.1
Salman, A.2
Engelbrecht, A.P.3
-
29
-
-
84866149200
-
Modeling global solar radiation using particle swarm optimization (PSO)
-
Mohandes MA (2012) Modeling global solar radiation using particle swarm optimization (PSO). Sol Energy 86(11):3137–3145
-
(2012)
Sol Energy
, vol.86
, Issue.11
, pp. 3137-3145
-
-
Mohandes, M.A.1
-
30
-
-
84861005503
-
Hybrid mutation particle swarm optimization method for available transfer capability enhancement
-
Farahmand H, Rashidinejad M, Mousavi A, Gharaveisi AA, Irving MR, Taylor GA (2012) Hybrid mutation particle swarm optimization method for available transfer capability enhancement. Int J Electr Power Energy Syst 42(1):240–249
-
(2012)
Int J Electr Power Energy Syst
, vol.42
, Issue.1
, pp. 240-249
-
-
Farahmand, H.1
Rashidinejad, M.2
Mousavi, A.3
Gharaveisi, A.A.4
Irving, M.R.5
Taylor, G.A.6
-
31
-
-
84889255337
-
Study of a new improved PSO-BP neural network algorithm
-
Zhang L, Zhao JQ, Zhang XN, Zhang SL (2013) Study of a new improved PSO-BP neural network algorithm. J Harbin Inst Technol 20(5):99–105
-
(2013)
J Harbin Inst Technol
, vol.20
, Issue.5
, pp. 99-105
-
-
Zhang, L.1
Zhao, J.Q.2
Zhang, X.N.3
Zhang, S.L.4
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