-
1
-
-
0030476772
-
A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area
-
J. Yi, and V.R. Prybutok A neural network model forecasting for prediction of daily maximum ozone concentration in an industrialized urban area Environ. Pollut. 92 1996 349 357
-
(1996)
Environ. Pollut.
, vol.92
, pp. 349-357
-
-
Yi, J.1
Prybutok, V.R.2
-
2
-
-
0031172117
-
Comparing neural networks and regression models for ozone forecasting
-
A.C. Comrie Comparing neural networks and regression models for ozone forecasting J. Air Waste Manag. Assoc. 47 1997 653 663
-
(1997)
J. Air Waste Manag. Assoc.
, vol.47
, pp. 653-663
-
-
Comrie, A.C.1
-
3
-
-
0032146239
-
Artificial neural networks (the multilayer perceptron) a review of applications in the atmospheric sciences
-
M.W. Gardner, and S.R. Dorling Artificial neural networks (the multilayer perceptron) a review of applications in the atmospheric sciences Atmos. Environ. 32 1998 2627 2636
-
(1998)
Atmos. Environ.
, vol.32
, pp. 2627-2636
-
-
Gardner, M.W.1
Dorling, S.R.2
-
4
-
-
15544389367
-
Potential assessment of the support vector machine method in forecasting ambient air pollutant trends
-
W.Z. Lu, and W.J. Wang Potential assessment of the support vector machine method in forecasting ambient air pollutant trends Chemosphere 59 2005 693 701
-
(2005)
Chemosphere
, vol.59
, pp. 693-701
-
-
Lu, W.Z.1
Wang, W.J.2
-
5
-
-
57849159164
-
Neural network prediction models as a tool for air quality management in cities
-
J. Skrzypski, and E. Jach-Szakiel Neural network prediction models as a tool for air quality management in cities Environ. Prot. Eng. 34 4 2008 129 137
-
(2008)
Environ. Prot. Eng.
, vol.34
, Issue.4
, pp. 129-137
-
-
Skrzypski, J.1
Jach-Szakiel, E.2
-
6
-
-
60249092433
-
Forecasting of ozone episode days by cost-sensitive neural network methods
-
C.H. Tsai, L.C. Chang, and H.C. Chiang Forecasting of ozone episode days by cost-sensitive neural network methods Sci. Total Environ. 407 6 2009 2124 2135
-
(2009)
Sci. Total Environ.
, vol.407
, Issue.6
, pp. 2124-2135
-
-
Tsai, C.H.1
Chang, L.C.2
Chiang, H.C.3
-
8
-
-
79953031599
-
Improving the prediction of average total ozone in column over the Iberian Peninsula using neural networks banks
-
S. Salcedo-Sanz, J.L. Camacho, A.M. Perez-Bellido, E.G. Ortiz-Garcia, A. Portilla-Figueras, and E. Hernandez-Martin Improving the prediction of average total ozone in column over the Iberian Peninsula using neural networks banks Neurocomputing 74 9 2011 1492 1496
-
(2011)
Neurocomputing
, vol.74
, Issue.9
, pp. 1492-1496
-
-
Salcedo-Sanz, S.1
Camacho, J.L.2
Perez-Bellido, A.M.3
Ortiz-Garcia, E.G.4
Portilla-Figueras, A.5
Hernandez-Martin, E.6
-
9
-
-
76449085807
-
Prediction of daily maximum ground ozone concentration using support vector machine
-
A.B. Chelani Prediction of daily maximum ground ozone concentration using support vector machine Environ. Monit. Assess. 162 1-4 2010 169 176
-
(2010)
Environ. Monit. Assess.
, vol.162
, Issue.14
, pp. 169-176
-
-
Chelani, A.B.1
-
11
-
-
29544432659
-
Accounting seasonal nonstationarity in time series models for short-term ozone level forecast
-
S.E. Kim, and A. Kumar Accounting seasonal nonstationarity in time series models for short-term ozone level forecast Stoch. Environ. Res. Risk A 19 2005 241 248
-
(2005)
Stoch. Environ. Res. Risk A
, vol.19
, pp. 241-248
-
-
Kim, S.E.1
Kumar, A.2
-
12
-
-
77949774686
-
Tree-based threshold modeling for short-term forecast of daily maximum ozone level
-
S.E. Kim Tree-based threshold modeling for short-term forecast of daily maximum ozone level Stoch. Environ. Res. Risk A 24 2010 19 28
-
(2010)
Stoch. Environ. Res. Risk A
, vol.24
, pp. 19-28
-
-
Kim, S.E.1
-
13
-
-
33745903481
-
Extreme learning machine: Theory and applications
-
G.B. Huang, Q.Y. Zhu, and C.K. Siew Extreme learning machine: theory and applications Neurocomputing 70 2006 489 501
-
(2006)
Neurocomputing
, vol.70
, pp. 489-501
-
-
Huang, G.B.1
Zhu, Q.Y.2
Siew, C.K.3
-
14
-
-
24644474838
-
Recognizing facial expression: Machine learning and application to spontaneous behavior
-
ISSN 1063-6919
-
M.S. Bartlett, G. Littlewort, M. Frank, C. Lainscsek, I. Fasel, and J. Movellan Recognizing facial expression: machine learning and application to spontaneous behavior Comput. Vis. Pattern Recogn. 2 2005 568 573 ISSN 1063-6919
-
(2005)
Comput. Vis. Pattern Recogn.
, vol.2
, pp. 568-573
-
-
Bartlett, M.S.1
Littlewort, G.2
Frank, M.3
Lainscsek, C.4
Fasel, I.5
Movellan, J.6
-
15
-
-
56049098499
-
Sales forecasting using extreme learning machine with applications in fashion retailing
-
Z.L. Sun, T.M. Choi, K.F. Au, and Y. Yu Sales forecasting using extreme learning machine with applications in fashion retailing Decis. Support Syst. 46 2008 411 419
-
(2008)
Decis. Support Syst.
, vol.46
, pp. 411-419
-
-
Sun, Z.L.1
Choi, T.M.2
Au, K.F.3
Yu, Y.4
-
16
-
-
84859007933
-
Extreme learning machine for regression and multiclass classification
-
G.B. Huang, H.M. Zhou, X.J. Ding, and R. Zhang Extreme learning machine for regression and multiclass classification IEEE Trans. Syst. Man Cybern. Part B: Cybern. 10 2 2012 513 529
-
(2012)
IEEE Trans. Syst. Man Cybern. Part B: Cybern.
, vol.10
, Issue.2
, pp. 513-529
-
-
Huang, G.B.1
Zhou, H.M.2
Ding, X.J.3
Zhang, R.4
-
17
-
-
0036530967
-
DENFIS: Dynamic evolving neural-fuzzy inference system and its application for time-series prediction
-
N. Kasabov DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction IEEE Trans. Fuzzy Syst. 10 2 2002 144 154
-
(2002)
IEEE Trans. Fuzzy Syst.
, vol.10
, Issue.2
, pp. 144-154
-
-
Kasabov, N.1
-
22
-
-
67650083264
-
Soft chemical analyzer development using adaptive least-squares support vector regression with selective pruning and variable moving window size
-
Y. Liu, N.P. Hu, H. Wang, and P. Li Soft chemical analyzer development using adaptive least-squares support vector regression with selective pruning and variable moving window size Ind. Eng. Chem. Res. 48 12 2009 5731 5741
-
(2009)
Ind. Eng. Chem. Res.
, vol.48
, Issue.12
, pp. 5731-5741
-
-
Liu, Y.1
Hu, N.P.2
Wang, H.3
Li, P.4
-
23
-
-
84863357539
-
Just-in-time kernel learning with adaptive parameter selection for soft sensor modeling of batch processes
-
Y. Liu, Z. Gao, P. Li, and H. Wang Just-in-time kernel learning with adaptive parameter selection for soft sensor modeling of batch processes Ind. Eng. Chem. Res. 51 11 2012 4313 4327
-
(2012)
Ind. Eng. Chem. Res.
, vol.51
, Issue.11
, pp. 4313-4327
-
-
Liu, Y.1
Gao, Z.2
Li, P.3
Wang, H.4
-
24
-
-
84879060636
-
Integrated soft sensor using just-in-time support vector regression and probabilistic analysis for quality prediction of multi-grade processes
-
Y. Liu, and J. Chen Integrated soft sensor using just-in-time support vector regression and probabilistic analysis for quality prediction of multi-grade processes J. Process Control 23 6 2013 793 804
-
(2013)
J. Process Control
, vol.23
, Issue.6
, pp. 793-804
-
-
Liu, Y.1
Chen, J.2
-
25
-
-
0032170668
-
The application of neural techniques to the modelling of time-series of atmospheric pollution data
-
G. Nunnari, A.F.M. Nucifora, and C. Randieri The application of neural techniques to the modelling of time-series of atmospheric pollution data Ecol. Model. 11 1998 187 205
-
(1998)
Ecol. Model.
, vol.11
, pp. 187-205
-
-
Nunnari, G.1
Nucifora, A.F.M.2
Randieri, C.3
-
26
-
-
0033120626
-
An application of artificial neural networks to the prediction of surface ozone concentrations in the United Kingdom
-
G. Spellman An application of artificial neural networks to the prediction of surface ozone concentrations in the United Kingdom Appl. Geogr. 19 1999 123 136
-
(1999)
Appl. Geogr.
, vol.19
, pp. 123-136
-
-
Spellman, G.1
-
27
-
-
0033880828
-
Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations
-
V.R. Prybutok, J.S. Yi, and D. Mitchell Comparison of neural network models with ARIMA and regression models for prediction of Houston's daily maximum ozone concentrations Eur. J. Oper. Res. 122 2000 31 40
-
(2000)
Eur. J. Oper. Res.
, vol.122
, pp. 31-40
-
-
Prybutok, V.R.1
Yi, J.S.2
Mitchell, D.3
-
28
-
-
0034109258
-
Ozone modeling using neural networks
-
R. Narasimhan, J. Keller, G. Subrarnaniam, E. Raasch, B. Croley, K. Duncan, and W.T. Potter Ozone modeling using neural networks J. Clim. Appl. Meteorol. 39 2000 291 296
-
(2000)
J. Clim. Appl. Meteorol.
, vol.39
, pp. 291-296
-
-
Narasimhan, R.1
Keller, J.2
Subrarnaniam, G.3
Raasch, E.4
Croley, B.5
Duncan, K.6
Potter, W.T.7
-
29
-
-
0036224943
-
Assessment and prediction of tropospheric ozone concentration levels using artificial neural networks
-
S.A. Abdul-Wahab, and S.M. Al-Alawi Assessment and prediction of tropospheric ozone concentration levels using artificial neural networks Environ. Model. Softw. 17 2002 219 228
-
(2002)
Environ. Model. Softw.
, vol.17
, pp. 219-228
-
-
Abdul-Wahab, S.A.1
Al-Alawi, S.M.2
-
30
-
-
0037107821
-
Effective 1-day ahead prediction of hourly surface ozone concentrations in eastern Spain using linear models and neural networks
-
E. Balaguer-Ballester, I. Camps, G. Valls, J.L. Carrasco-Rodriguez, E. Soria Olivas, and S. del Valle-Tascon Effective 1-day ahead prediction of hourly surface ozone concentrations in eastern Spain using linear models and neural networks Ecol. Model. 156 2002 27 41
-
(2002)
Ecol. Model.
, vol.156
, pp. 27-41
-
-
Balaguer-Ballester, E.1
Camps, I.2
Valls, G.3
Carrasco-Rodriguez, J.L.4
Soria Olivas, E.5
Del Valle-Tascon, S.6
-
31
-
-
0036468601
-
Atmospheric urban pollution: Applications of an artificial neural network (ANN) to the city of Perugia
-
P. Viotti, G. Liuti, and P. Di Genova Atmospheric urban pollution: applications of an artificial neural network (ANN) to the city of Perugia Ecol. Model. 148 2002 27 46
-
(2002)
Ecol. Model.
, vol.148
, pp. 27-46
-
-
Viotti, P.1
Liuti, G.2
Di Genova, P.3
-
32
-
-
11444255160
-
Unbiased sensitivity analysis and pruning techniques in neural networks for surface ozone modeling
-
O. Pastor-Barcenas, E. Soria-Olivas, J.D. Martin-Guerrero, G. Camps-Valls, J.L. Carrasco-Rodriguez, and S. Valle-Tascon Unbiased sensitivity analysis and pruning techniques in neural networks for surface ozone modeling Ecol. Model. 182 2005 149 158
-
(2005)
Ecol. Model.
, vol.182
, pp. 149-158
-
-
Pastor-Barcenas, O.1
Soria-Olivas, E.2
Martin-Guerrero, J.D.3
Camps-Valls, G.4
Carrasco-Rodriguez, J.L.5
Valle-Tascon, S.6
-
33
-
-
33748040101
-
Neural networks for analysing the relevance of input variables in the prediction of tropospheric ozone concentration
-
J. Gomez-Sanchis, J.D. MartIn-Guerrero, E. Soria-Olivas, J. Vila-Frances, J.L. Carrasco, and D.S. Valle-Tascon Neural networks for analysing the relevance of input variables in the prediction of tropospheric ozone concentration Atmos. Environ. 40 2006 6173 6180
-
(2006)
Atmos. Environ.
, vol.40
, pp. 6173-6180
-
-
Gomez-Sanchis, J.1
Martin-Guerrero, J.D.2
Soria-Olivas, E.3
Vila-Frances, J.4
Carrasco, J.L.5
Valle-Tascon, D.S.6
-
34
-
-
38949194253
-
Application of artificial neural networks to predict prevalence of building-related symptoms in office buildings
-
S.C. Sofuoglu Application of artificial neural networks to predict prevalence of building-related symptoms in office buildings Build. Environ. 43 6 2008 1121 1126
-
(2008)
Build. Environ.
, vol.43
, Issue.6
, pp. 1121-1126
-
-
Sofuoglu, S.C.1
-
36
-
-
0033990385
-
Meteorologically adjusted trends in UK daily maximum surface ozone concentrations
-
M.W. Gardner, and S.R. Dorling Meteorologically adjusted trends in UK daily maximum surface ozone concentrations Atmos. Environ. 34 2000 171 176
-
(2000)
Atmos. Environ.
, vol.34
, pp. 171-176
-
-
Gardner, M.W.1
Dorling, S.R.2
-
38
-
-
33745714336
-
Prediction of daily maximum ozone concentrations from meteorological conditions using a two-stage neural network
-
H.C. Lu, J.C. Hsieh, and T.S. Chang Prediction of daily maximum ozone concentrations from meteorological conditions using a two-stage neural network Atmos. Res. 81 2006 124 139
-
(2006)
Atmos. Res.
, vol.81
, pp. 124-139
-
-
Lu, H.C.1
Hsieh, J.C.2
Chang, T.S.3
-
39
-
-
0027205884
-
A scaled conjugate gradient algorithm for fast supervised learning
-
M.F. Moller A scaled conjugate gradient algorithm for fast supervised learning Neural Netw. 6 1993 525 533
-
(1993)
Neural Netw.
, vol.6
, pp. 525-533
-
-
Moller, M.F.1
-
40
-
-
0042061161
-
Comparative assessment of neural networks and regression models for forecasting summertime ozone in Athens
-
A. Chaloulakou, M. Saisana, and N. Spyrellisa Comparative assessment of neural networks and regression models for forecasting summertime ozone in Athens Sci. Total Environ. 313 2003 1 13
-
(2003)
Sci. Total Environ.
, vol.313
, pp. 1-13
-
-
Chaloulakou, A.1
Saisana, M.2
Spyrellisa, N.3
-
41
-
-
17644370689
-
Air quality prediction in Milan: Feed-forward neural networks, pruned neural networks and lazy learning
-
G. Corani Air quality prediction in Milan: feed-forward neural networks, pruned neural networks and lazy learning Ecol. Model. 185 2005 513 529
-
(2005)
Ecol. Model.
, vol.185
, pp. 513-529
-
-
Corani, G.1
-
42
-
-
0037899217
-
A rigorous inter-comparison of ground-level ozone predictions
-
U. Schlink, S. Dorling, E. Pelikan, G. Nunnari, G. Cawley, H. Junninen, A. Greig, R. Foxall, K. Eben, T. Chatterton, J. Vondracek, M. Richter, M. Dostac, L. Bertucco, M. Kolehmainen, and M. Doyle A rigorous inter-comparison of ground-level ozone predictions Atmos. Environ. 37 2003 3237 3253
-
(2003)
Atmos. Environ.
, vol.37
, pp. 3237-3253
-
-
Schlink, U.1
Dorling, S.2
Pelikan, E.3
Nunnari, G.4
Cawley, G.5
Junninen, H.6
Greig, A.7
Foxall, R.8
Eben, K.9
Chatterton, T.10
Vondracek, J.11
Richter, M.12
Dostac, M.13
Bertucco, L.14
Kolehmainen, M.15
Doyle, M.16
-
43
-
-
0001441372
-
Probable networks and plausible predictions - A review of practical Bayesian methods for supervised neural networks
-
D.J.C. MacKay Probable networks and plausible predictions - a review of practical Bayesian methods for supervised neural networks Netw. Comput. Neural Syst. 6 1995 469 505
-
(1995)
Netw. Comput. Neural Syst.
, vol.6
, pp. 469-505
-
-
Mackay, D.J.C.1
-
45
-
-
33644541501
-
Interval estimation of urban ozone level and selection of influential factors by employing automatic relevance determination model
-
D. Wang, and W.Z. Lu Interval estimation of urban ozone level and selection of influential factors by employing automatic relevance determination model Chemosphere 62 2006 1600 1611
-
(2006)
Chemosphere
, vol.62
, pp. 1600-1611
-
-
Wang, D.1
Lu, W.Z.2
-
48
-
-
0037382121
-
Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong
-
W.Z. Lu, H.Y. Fan, and S.M. Lo Application of evolutionary neural network method in predicting pollutant levels in downtown area of Hong Kong Neurocomputing 51 2003 387 400
-
(2003)
Neurocomputing
, vol.51
, pp. 387-400
-
-
Lu, W.Z.1
Fan, H.Y.2
Lo, S.M.3
-
49
-
-
33748783344
-
Ground-level ozone prediction using multilayer perceptron trained with an innovative hybrid approach
-
D. Wang, and W.Z. Lu Ground-level ozone prediction using multilayer perceptron trained with an innovative hybrid approach Ecol. Model. 198 2006 332 340
-
(2006)
Ecol. Model.
, vol.198
, pp. 332-340
-
-
Wang, D.1
Lu, W.Z.2
-
50
-
-
29844455331
-
Forecasting of ozone level in time series using MLP model with a novel hybrid training algorithm
-
D. Wang, and W.Z. Lu Forecasting of ozone level in time series using MLP model with a novel hybrid training algorithm Atmos. Environ. 40 2006 913 924
-
(2006)
Atmos. Environ.
, vol.40
, pp. 913-924
-
-
Wang, D.1
Lu, W.Z.2
-
51
-
-
0036882622
-
A preliminary study of ozone trend and its impact on environment in Hong Kong
-
W.Z. Lu, X.K. Wang, W.J. Wang, A.Y.T. Leung, and K.K. Yuen A preliminary study of ozone trend and its impact on environment in Hong Kong Environ. Int. 28 6 2002 503 512
-
(2002)
Environ. Int.
, vol.28
, Issue.6
, pp. 503-512
-
-
Lu, W.Z.1
Wang, X.K.2
Wang, W.J.3
Leung, A.Y.T.4
Yuen, K.K.5
-
53
-
-
34249753618
-
Support-vector networks
-
10.1007/BF00994018
-
C. Cortes, and V.N. Vapnik Support-vector networks Machi. Learn. 20 3 1995 273 10.1007/BF00994018
-
(1995)
Machi. Learn.
, vol.20
, Issue.3
, pp. 273
-
-
Cortes, C.1
Vapnik, V.N.2
-
57
-
-
66449136989
-
Time series prediction using support vector machines: A survey
-
N.L. Sapankevych, and R. Sankar Time series prediction using support vector machines: a survey IEEE Comput. Intell. Mag. 4 2 2009 24 38
-
(2009)
IEEE Comput. Intell. Mag.
, vol.4
, Issue.2
, pp. 24-38
-
-
Sapankevych, N.L.1
Sankar, R.2
-
58
-
-
76649131245
-
Greek long-term energy consumption prediction using artificial neural networks
-
L. Ekonomou Greek long-term energy consumption prediction using artificial neural networks Energy 35 2 2010 512 517
-
(2010)
Energy
, vol.35
, Issue.2
, pp. 512-517
-
-
Ekonomou, L.1
-
59
-
-
78649523121
-
A novel interpolation method based on differential evolution-simplex algorithm optimized parameters for support vector regression
-
D.M. Zhang, W. Liu, X. Xu, and Q.A. Deng A novel interpolation method based on differential evolution-simplex algorithm optimized parameters for support vector regression Adv. Comput. Intell. 6382 2010 64 75
-
(2010)
Adv. Comput. Intell.
, vol.6382
, pp. 64-75
-
-
Zhang, D.M.1
Liu, W.2
Xu, X.3
Deng, Q.A.4
-
60
-
-
41549103711
-
Ground-level ozone prediction by support vector machine approach with a cost-sensitive classification scheme
-
W.Z. Lu, and D. Wang Ground-level ozone prediction by support vector machine approach with a cost-sensitive classification scheme Sci. Total Environ. 395 2008 109 116
-
(2008)
Sci. Total Environ.
, vol.395
, pp. 109-116
-
-
Lu, W.Z.1
Wang, D.2
-
61
-
-
79955578106
-
Artificial neural network models for daily PM10 air pollution index prediction in the urban area of Wuhan, China
-
S.J. Wu, Q. Feng, Y. Du, and X.D. Li Artificial neural network models for daily PM10 air pollution index prediction in the urban area of Wuhan, China Environ. Eng. Sci. 28 5 2011 357 363
-
(2011)
Environ. Eng. Sci.
, vol.28
, Issue.5
, pp. 357-363
-
-
Wu, S.J.1
Feng, Q.2
Du, Y.3
Li, X.D.4
-
62
-
-
38849202538
-
Online prediction model based on support vector machine
-
W.J. Wang, C.Q. Men, and W.Z. Lu Online prediction model based on support vector machine Neurocomputing 71 2008 550 558
-
(2008)
Neurocomputing
, vol.71
, pp. 550-558
-
-
Wang, W.J.1
Men, C.Q.2
Lu, W.Z.3
-
63
-
-
1642276856
-
A meta-learning method to select the kernel width in support vector regression
-
C. Soares, P.B. Brazdil, and P. Kuba A meta-learning method to select the kernel width in support vector regression Mach. Lear. 54 3 2004 195 209
-
(2004)
Mach. Lear.
, vol.54
, Issue.3
, pp. 195-209
-
-
Soares, C.1
Brazdil, P.B.2
Kuba, P.3
-
64
-
-
0345688978
-
Determination of the spread parameter in the Gaussian kernel for classification and regression
-
W.J. Wang, W.Z. Xu Zongben Lu, and X.Y. Zhang Determination of the spread parameter in the Gaussian kernel for classification and regression Neurocomputing 55 2003 643 663
-
(2003)
Neurocomputing
, vol.55
, pp. 643-663
-
-
Wang, W.J.1
Xu Zongben Lu, W.Z.2
Zhang, X.Y.3
-
65
-
-
67649255836
-
Assessing the relative importance of surface ozone influential variables in regional-scale analysis
-
W.Z. Lu, and D. Wang Assessing the relative importance of surface ozone influential variables in regional-scale analysis Atmos. Environ. 44 22 2009 3621 3629
-
(2009)
Atmos. Environ.
, vol.44
, Issue.22
, pp. 3621-3629
-
-
Lu, W.Z.1
Wang, D.2
-
66
-
-
0038201778
-
Prediction of maximum daily ozone level using combined neural network and statistical characteristics
-
W.J. Wang, W.Z. Lu, X.K. Wang, and A.Y.T. Leung Prediction of maximum daily ozone level using combined neural network and statistical characteristics Environ. Int. 29 2003 555 562
-
(2003)
Environ. Int.
, vol.29
, pp. 555-562
-
-
Wang, W.J.1
Lu, W.Z.2
Wang, X.K.3
Leung, A.Y.T.4
|