-
1
-
-
0030211964
-
Bagging predictors
-
Breiman L (1996) Bagging predictors. Mach Learn 24:123–140. doi:10.1007/BF00058655
-
(1996)
Mach Learn
, vol.24
, pp. 123-140
-
-
Breiman, L.1
-
2
-
-
0035478854
-
Random forests
-
Breiman L (2001) Random forests. Mach Learn 45:5–32. doi:10.1023/A:1010933404324
-
(2001)
Mach Learn
, vol.45
, pp. 5-32
-
-
Breiman, L.1
-
3
-
-
84906569541
-
Indoor localization in a hospital environment using random forest classifiers
-
Calderoni L, Ferrara M, Franco A, Maio D (2015) Indoor localization in a hospital environment using random forest classifiers. Expert Syst Appl 42:125–134
-
(2015)
Expert Syst Appl
, vol.42
, pp. 125-134
-
-
Calderoni, L.1
Ferrara, M.2
Franco, A.3
Maio, D.4
-
4
-
-
0034250160
-
An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization
-
Dietterich TG (2000) An experimental comparison of three methods for constructing ensembles of decision trees: bagging, boosting, and randomization. Mach Learn 40:139–157. doi:10.1023/A:1007607513941
-
(2000)
Mach Learn
, vol.40
, pp. 139-157
-
-
Dietterich, T.G.1
-
5
-
-
84896367715
-
-
Roke DA: Decision tree approach for soil liquefaction assessment. Sci World J
-
Gandomi AH, Fridline MM, Roke DA (2013) Decision tree approach for soil liquefaction assessment. Sci World J. doi:10.1155/2013/346285
-
(2013)
Fridline MM
-
-
Gandomi, A.H.1
-
6
-
-
0030403486
-
Neural-network modeling of CPT seismic liquefaction data
-
Goh AT (1996) Neural-network modeling of CPT seismic liquefaction data. J Geotech Eng 122:70–73. doi:10.1061/(ASCE)0733-9410(1996)122:1(70)
-
(1996)
J Geotech Eng
, vol.122
, pp. 70-73
-
-
Goh, A.T.1
-
7
-
-
34848870321
-
Support vector machines: their use in geotechnical engineering as illustrated using seismic liquefaction data
-
Goh AT, Goh S (2007) Support vector machines: their use in geotechnical engineering as illustrated using seismic liquefaction data. Comput Geotech 34:410–421. doi:10.1016/j.compgeo.2007.06.001
-
(2007)
Comput Geotech
, vol.34
, pp. 410-421
-
-
Goh, A.T.1
Goh, S.2
-
8
-
-
14644421528
-
Investigation of the random forest framework for classification of hyperspectral data
-
Ham J, Chen Y, Crawford MM, Ghosh J (2005) Investigation of the random forest framework for classification of hyperspectral data. IEEE Trans Geosci Remote Sens 43:492–501. doi:10.1109/TGRS.2004.842481
-
(2005)
IEEE Trans Geosci Remote Sens
, vol.43
, pp. 492-501
-
-
Ham, J.1
Chen, Y.2
Crawford, M.M.3
Ghosh, J.4
-
9
-
-
0032139235
-
The random subspace method for constructing decision forests
-
Ho TK (1998) The random subspace method for constructing decision forests. IEEE Trans Pattern Anal Mach Intell 20:832–844. doi:10.1109/34.709601
-
(1998)
IEEE Trans Pattern Anal Mach Intell
, vol.20
, pp. 832-844
-
-
Ho, T.K.1
-
10
-
-
84862148993
-
Modelling stress–strain and volume change behaviour of unsaturated soils using an evolutionary based data mining technique, an incremental approach
-
Javadi AA, Ahangar-Asr A, Johari A, Faramarzi A, Toll D (2012) Modelling stress–strain and volume change behaviour of unsaturated soils using an evolutionary based data mining technique, an incremental approach. Eng Appl Artif Intell 25:926–933
-
(2012)
Eng Appl Artif Intell
, vol.25
, pp. 926-933
-
-
Javadi, A.A.1
Ahangar-Asr, A.2
Johari, A.3
Faramarzi, A.4
Toll, D.5
-
11
-
-
39049121324
-
Feature selection for morphological feature extraction using random forests
-
Joelsson SR, Benediktsson JA, Sveinsson JR (2006) Feature selection for morphological feature extraction using random forests. In: IEEE, proceedings of the 7th Nordic, signal processing symposium, 2006. NORSIG 2006, pp 10–13
-
(2006)
IEEE, proceedings of the 7th Nordic, signal processing symposium, 2006. NORSIG
, vol.2006
, pp. 10-13
-
-
Joelsson, S.R.1
Benediktsson, J.A.2
Sveinsson, J.R.3
-
12
-
-
0037239210
-
Simplified cone penetration test-based method for evaluating liquefaction resistance of soils
-
Juang CH, Yuan H, Lee D-H, Lin P-S (2003) Simplified cone penetration test-based method for evaluating liquefaction resistance of soils. J Geotech Geoenviron Eng 129:66–80. doi:10.1061/(ASCE)1090-0241(2003)129:1(66)
-
(2003)
J Geotech Geoenviron Eng
, vol.129
, pp. 66-80
-
-
Juang, C.H.1
Yuan, H.2
Lee, D.-H.3
Lin, P.-S.4
-
13
-
-
84954349767
-
Modeling the mechanical behavior of carbonate sands using artificial neural networks and support vector machines
-
Kohestani VR, Hassanlourad M (2015) Modeling the mechanical behavior of carbonate sands using artificial neural networks and support vector machines. Int J Geomech. doi:10.1061/(ASCE)GM.1943-5622.0000509
-
(2015)
Int J Geomech
-
-
Kohestani, V.R.1
Hassanlourad, M.2
-
14
-
-
84937752957
-
Regression models for evaluating liquefaction probability
-
Liao SS, Veneziano D, Whitman RV (1988) Regression models for evaluating liquefaction probability. J Geotech Eng 114:389–411. doi:10.1061/(ASCE)0733-9410(1988)114:4(389)
-
(1988)
J Geotech Eng
, vol.114
, pp. 389-411
-
-
Liao, S.S.1
Veneziano, D.2
Whitman, R.V.3
-
15
-
-
0345040873
-
Classification and regression by random forest
-
Liaw A, Wiener M (2002) Classification and regression by random forest. R News 2:18–22
-
(2002)
R News
, vol.2
, pp. 18-22
-
-
Liaw, A.1
Wiener, M.2
-
17
-
-
79959703102
-
Estimating residual variance in random forest regression
-
Mendez G, Lohr S (2011) Estimating residual variance in random forest regression. Comput Stat Data Anal 55:2937–2950
-
(2011)
Comput Stat Data Anal
, vol.55
, pp. 2937-2950
-
-
Mendez, G.1
Lohr, S.2
-
18
-
-
78349272696
-
Validation and application of empirical liquefaction models
-
Oommen T, Baise LG, Vogel R (2010) Validation and application of empirical liquefaction models. J Geotech Geoenviron Eng 136:1618–1633
-
(2010)
J Geotech Geoenviron Eng
, vol.136
, pp. 1618-1633
-
-
Oommen, T.1
Baise, L.G.2
Vogel, R.3
-
19
-
-
33746870002
-
Support vector machines-based modelling of seismic liquefaction potential
-
Pal M (2006) Support vector machines-based modelling of seismic liquefaction potential. Int J Numer Anal Meth Geomech 30:983–996. doi:10.1002/nag.509
-
(2006)
Int J Numer Anal Meth Geomech
, vol.30
, pp. 983-996
-
-
Pal, M.1
-
20
-
-
39349112156
-
Seismic liquefaction potential assessment by using relevance vector machine
-
Samui P (2007) Seismic liquefaction potential assessment by using relevance vector machine. Earthq Eng Eng Vib 6:331–336. doi:10.1007/s11803-007-0766-7
-
(2007)
Earthq Eng Eng Vib
, vol.6
, pp. 331-336
-
-
Samui, P.1
-
21
-
-
84921423491
-
The use of a relevance vector machine in predicting liquefaction potential
-
Samui P, Karthikeyan J (2014) The use of a relevance vector machine in predicting liquefaction potential. Indian Geotech J 44:458–467. doi:10.1007/s40098-013-0094-y
-
(2014)
Indian Geotech J
, vol.44
, pp. 458-467
-
-
Samui, P.1
Karthikeyan, J.2
-
22
-
-
78650915977
-
Machine learning modelling for predicting soil liquefaction susceptibility
-
Samui P, Sitharam T (2011) Machine learning modelling for predicting soil liquefaction susceptibility. Nat Hazards Earth Syst Sci 11:1–9. doi:10.5194/nhess-11-1-2011
-
(2011)
Nat Hazards Earth Syst Sci
, vol.11
, pp. 1-9
-
-
Samui, P.1
Sitharam, T.2
-
23
-
-
0015128601
-
Simplified procedure for evaluating soil liquefaction potential
-
Seed HB, Idriss IM (1971) Simplified procedure for evaluating soil liquefaction potential. J Soil Mech Found Div 97:1249–1273
-
(1971)
J Soil Mech Found Div
, vol.97
, pp. 1249-1273
-
-
Seed, H.B.1
Idriss, I.M.2
-
24
-
-
77958064179
-
Mining data with random forests: a survey and results of new tests
-
Verikas A, Gelzinis A, Bacauskiene M (2011) Mining data with random forests: a survey and results of new tests. Pattern Recogn 44:330–349. doi:10.1016/j.patcog.2010.08.011
-
(2011)
Pattern Recogn
, vol.44
, pp. 330-349
-
-
Verikas, A.1
Gelzinis, A.2
Bacauskiene, M.3
-
25
-
-
79953029215
-
Application of a random forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy
-
Vincenzi S, Zucchetta M, Franzoi P, Pellizzato M, Pranovi F, De Leo GA, Torricelli P (2011) Application of a random forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy. Ecol Model 222:1471–1478. doi:10.1016/j.ecolmodel.2011.02.007
-
(2011)
Ecol Model
, vol.222
, pp. 1471-1478
-
-
Vincenzi, S.1
Zucchetta, M.2
Franzoi, P.3
Pellizzato, M.4
Pranovi, F.5
De Leo, G.A.6
Torricelli, P.7
-
26
-
-
84949116428
-
A random forest algorithm applied to condition-based wastewater deterioration modeling and forecasting
-
Vitorino D, Coelho S, Santos P, Sheets S, Jurkovac B, Amado C (2014) A random forest algorithm applied to condition-based wastewater deterioration modeling and forecasting. Procedia Eng 89:401–410
-
(2014)
Procedia Eng
, vol.89
, pp. 401-410
-
-
Vitorino, D.1
Coelho, S.2
Santos, P.3
Sheets, S.4
Jurkovac, B.5
Amado, C.6
-
27
-
-
67651115922
-
Monitoring of cropland practices for carbon sequestration purposes in north central Montana by Landsat remote sensing
-
Watts JD, Lawrence RL, Miller PR, Montagne C (2009) Monitoring of cropland practices for carbon sequestration purposes in north central Montana by Landsat remote sensing. Remote Sens Environ 113:1843–1852. doi:10.1016/j.rse.2009.04.015
-
(2009)
Remote Sens Environ
, vol.113
, pp. 1843-1852
-
-
Watts, J.D.1
Lawrence, R.L.2
Miller, P.R.3
Montagne, C.4
-
29
-
-
84877018780
-
Application of the adaptive neuro-fuzzy inference system for prediction of soil liquefaction
-
Xue X, Yang X (2013) Application of the adaptive neuro-fuzzy inference system for prediction of soil liquefaction. Nat Hazards 67:901–917
-
(2013)
Nat Hazards
, vol.67
, pp. 901-917
-
-
Xue, X.1
Yang, X.2
-
30
-
-
0035474671
-
Liquefaction resistance of soils: summary report from the 1996 NCEER and 1998 NCEER/NSF workshops on evaluation of liquefaction resistance of soils
-
Youd T et al (2001) Liquefaction resistance of soils: summary report from the 1996 NCEER and 1998 NCEER/NSF workshops on evaluation of liquefaction resistance of soils. J Geotech Geoenviron Eng 127:817–833. doi:10.1061/(ASCE)1090-0241(2001)127:10(817)
-
(2001)
J Geotech Geoenviron Eng
, vol.127
, pp. 817-833
-
-
Youd, T.1
|