-
1
-
-
0008071910
-
Time series prediction with neural nets application to airborne pollen forecasting
-
Arizmendi C.M., Sanchez J.R., Ramos N.E., and Ramos G.I. Time series prediction with neural nets application to airborne pollen forecasting. Int. J. Biometeorol. 37 3 (1993) 139-144
-
(1993)
Int. J. Biometeorol.
, vol.37
, Issue.3
, pp. 139-144
-
-
Arizmendi, C.M.1
Sanchez, J.R.2
Ramos, N.E.3
Ramos, G.I.4
-
3
-
-
0030130753
-
Designing a neural network for forecasting financial and economic time series
-
Kaastra I., and Boyd M. Designing a neural network for forecasting financial and economic time series. Neurocomputing 10 3 (1996) 215-236
-
(1996)
Neurocomputing
, vol.10
, Issue.3
, pp. 215-236
-
-
Kaastra, I.1
Boyd, M.2
-
4
-
-
0030269901
-
Sales forecasting using time series and neural networks
-
Ansuj A.P., Camargo M.E., Radharamanan R., and Petry D.G. Sales forecasting using time series and neural networks. Comput. Ind. Eng. 31 1-2 (1996) 421-424
-
(1996)
Comput. Ind. Eng.
, vol.31
, Issue.1-2
, pp. 421-424
-
-
Ansuj, A.P.1
Camargo, M.E.2
Radharamanan, R.3
Petry, D.G.4
-
5
-
-
0032133950
-
Neural network forecasting of the British pound US dollar exchange rate
-
Zhang G., and Hu M.Y. Neural network forecasting of the British pound US dollar exchange rate. Omega-Int. J. Manage. Sci. 26 4 (1998) 495-506
-
(1998)
Omega-Int. J. Manage. Sci.
, vol.26
, Issue.4
, pp. 495-506
-
-
Zhang, G.1
Hu, M.Y.2
-
6
-
-
0033104431
-
Radial basis function neural networks for the characterization of heart rate variability dynamics
-
Bezerianos A., Papadimitriou S., and Alexopoulos D. Radial basis function neural networks for the characterization of heart rate variability dynamics. Artif. Intell. Med. 15 3 (1999) 215-234
-
(1999)
Artif. Intell. Med.
, vol.15
, Issue.3
, pp. 215-234
-
-
Bezerianos, A.1
Papadimitriou, S.2
Alexopoulos, D.3
-
7
-
-
0034075622
-
Damping in buildings: its neural network model and AR model
-
Li Q.S., Liu D.K., Fang J.Q., Jeary A.P., and Wong C.K. Damping in buildings: its neural network model and AR model. Eng. Struct. 22 9 (2000) 1216-1223
-
(2000)
Eng. Struct.
, vol.22
, Issue.9
, pp. 1216-1223
-
-
Li, Q.S.1
Liu, D.K.2
Fang, J.Q.3
Jeary, A.P.4
Wong, C.K.5
-
8
-
-
2342458952
-
Multiple neural networks for a long term time series forecast
-
Nguyen H.H., and Chan C.W. Multiple neural networks for a long term time series forecast. Neural Comput. Appl. 13 1 (2004) 90-98
-
(2004)
Neural Comput. Appl.
, vol.13
, Issue.1
, pp. 90-98
-
-
Nguyen, H.H.1
Chan, C.W.2
-
9
-
-
0031191950
-
Neural networks and traditional time series methods: a synergistic combination in state economic forecasts
-
Hansen J.V., and Nelson R.D. Neural networks and traditional time series methods: a synergistic combination in state economic forecasts. IEEE Trans. Neural Networks 8 4 (1997) 863-873
-
(1997)
IEEE Trans. Neural Networks
, vol.8
, Issue.4
, pp. 863-873
-
-
Hansen, J.V.1
Nelson, R.D.2
-
10
-
-
0037191007
-
Short-term load forecasting based on artificial neural networks parallel implementation
-
Kalaitzakis K., Stavrakakis G.S., and Anagnostakis E.M. Short-term load forecasting based on artificial neural networks parallel implementation. Electr. Power Syst. Res. 63 3 (2002) 185-196
-
(2002)
Electr. Power Syst. Res.
, vol.63
, Issue.3
, pp. 185-196
-
-
Kalaitzakis, K.1
Stavrakakis, G.S.2
Anagnostakis, E.M.3
-
11
-
-
0037243071
-
Time series forecasting using hybrid ARIMA and neural network models
-
Zhang G.P. Time series forecasting using hybrid ARIMA and neural network models. Neurocomputing 50 (2003) 159-175
-
(2003)
Neurocomputing
, vol.50
, pp. 159-175
-
-
Zhang, G.P.1
-
12
-
-
11244305511
-
NARMAX time series model prediction: feed-forward and recurrent fuzzy neural network approaches
-
Gao Y., and Er M.J. NARMAX time series model prediction: feed-forward and recurrent fuzzy neural network approaches. Fuzzy Sets Syst. 150 2 (2005) 331-350
-
(2005)
Fuzzy Sets Syst.
, vol.150
, Issue.2
, pp. 331-350
-
-
Gao, Y.1
Er, M.J.2
-
13
-
-
0034100712
-
Prediction of watershed runoff using bayesian concepts and modular neural networks
-
Zhang B., and Govindaraju S. Prediction of watershed runoff using bayesian concepts and modular neural networks. Water Resour. Res. 36 3 (2000) 753-762
-
(2000)
Water Resour. Res.
, vol.36
, Issue.3
, pp. 753-762
-
-
Zhang, B.1
Govindaraju, S.2
-
14
-
-
0027038056
-
Physically based hydrologic modelling. 2. Is the concept realistic
-
Grayson R.B., Moore I.D., and McMahon T.A. Physically based hydrologic modelling. 2. Is the concept realistic. Water Resour. Res. 28 10 (1992) 2659-2666
-
(1992)
Water Resour. Res.
, vol.28
, Issue.10
, pp. 2659-2666
-
-
Grayson, R.B.1
Moore, I.D.2
McMahon, T.A.3
-
15
-
-
0026954346
-
Forecasting the behaviour of the multivariate time series using neural networks
-
Chakraborty K., Mehrotra K., Mohan C.K., and Ranka S. Forecasting the behaviour of the multivariate time series using neural networks. Neural Networks 5 (1992) 961-970
-
(1992)
Neural Networks
, vol.5
, pp. 961-970
-
-
Chakraborty, K.1
Mehrotra, K.2
Mohan, C.K.3
Ranka, S.4
-
16
-
-
0000413739
-
Application of neural networks to runoff prediction
-
Hippel K.W., et al. (Ed), Kluwer Academic, Norwell, MA
-
Zhu M.L., Fujita M., and Hashimoto N. Application of neural networks to runoff prediction. In: Hippel K.W., et al. (Ed). Stochastic and Statistical Methods in Hydrology and Environmental Engineering (1994), Kluwer Academic, Norwell, MA 205-216
-
(1994)
Stochastic and Statistical Methods in Hydrology and Environmental Engineering
, pp. 205-216
-
-
Zhu, M.L.1
Fujita, M.2
Hashimoto, N.3
-
17
-
-
0029416249
-
Neural network models of the rainfall runoff process
-
Smith J., and Eli R.N. Neural network models of the rainfall runoff process. J. Water Resour. Plan. Manage. ASCE 121 (1995) 499-508
-
(1995)
J. Water Resour. Plan. Manage.
, vol.ASCE 121
, pp. 499-508
-
-
Smith, J.1
Eli, R.N.2
-
18
-
-
0030159380
-
Artificial neural networks as rainfall runoff models
-
Minns A.W., and Hall M.J. Artificial neural networks as rainfall runoff models. Hydrol. Sci. J. 41 3 (1996) 399-417
-
(1996)
Hydrol. Sci. J.
, vol.41
, Issue.3
, pp. 399-417
-
-
Minns, A.W.1
Hall, M.J.2
-
19
-
-
0342506462
-
Application of neural network technique to rainfall-runoff modelling
-
Shamseldin A.Y. Application of neural network technique to rainfall-runoff modelling. J. Hydrol. 199 (1997) 272-294
-
(1997)
J. Hydrol.
, vol.199
, pp. 272-294
-
-
Shamseldin, A.Y.1
-
20
-
-
0032005702
-
An artificial neural network approach to rainfall-runoff modelling
-
Dawson D.W., and Wilby R. An artificial neural network approach to rainfall-runoff modelling. Hydrol. Sci. J. 43 1 (1998) 47-65
-
(1998)
Hydrol. Sci. J.
, vol.43
, Issue.1
, pp. 47-65
-
-
Dawson, D.W.1
Wilby, R.2
-
21
-
-
0032722662
-
Forecasting river flow rate during low-flow periods using neural networks
-
Campolo M., Soldati A., and Andreussi P. Forecasting river flow rate during low-flow periods using neural networks. Water Resour. Res. 35 11 (1999) 3547-3552
-
(1999)
Water Resour. Res.
, vol.35
, Issue.11
, pp. 3547-3552
-
-
Campolo, M.1
Soldati, A.2
Andreussi, P.3
-
22
-
-
2442639370
-
Development of effective and efficient rainfall-runoff models using integration of deterministic, real-coded genetic algorithms, and artificial neural network techniques
-
10.1029/2003WR002355
-
Jain A., and Srinivasulu S. Development of effective and efficient rainfall-runoff models using integration of deterministic, real-coded genetic algorithms, and artificial neural network techniques. Water Resour. Res. 40 4 (2004) W04302 10.1029/2003WR002355
-
(2004)
Water Resour. Res.
, vol.40
, Issue.4
-
-
Jain, A.1
Srinivasulu, S.2
-
23
-
-
0001855442
-
Mathematical synthesis of streamflow sequences for the analysis of river basin by simulation
-
Mass A., et al. (Ed), Harvard University Press, Cambridge, MA
-
Thomas H.A., and Fiering M.B. Mathematical synthesis of streamflow sequences for the analysis of river basin by simulation. In: Mass A., et al. (Ed). Design of Water Resources Systems (1962), Harvard University Press, Cambridge, MA 459-493
-
(1962)
Design of Water Resources Systems
, pp. 459-493
-
-
Thomas, H.A.1
Fiering, M.B.2
-
26
-
-
0000649310
-
Application of linear models to four annual streamflow series
-
Carlson R.F., MacCormick A.J.A., and Watts D.G. Application of linear models to four annual streamflow series. Water Resour. Res. 6 4 (1970) 1070-1078
-
(1970)
Water Resour. Res.
, vol.6
, Issue.4
, pp. 1070-1078
-
-
Carlson, R.F.1
MacCormick, A.J.A.2
Watts, D.G.3
-
27
-
-
0016047730
-
Application of seasonal parametric stochastic models for monthly flow data
-
McKerchar A.I., and Delleur J.W. Application of seasonal parametric stochastic models for monthly flow data. Water Resour. Res. (1974) 246-255
-
(1974)
Water Resour. Res.
, pp. 246-255
-
-
McKerchar, A.I.1
Delleur, J.W.2
-
28
-
-
85024429815
-
A new approach to linear filtering and prediction problems
-
Kalman R.E. A new approach to linear filtering and prediction problems. ASME Trans. Basic Eng. 82 2 (1960) 35-45
-
(1960)
ASME Trans. Basic Eng.
, vol.82
, Issue.2
, pp. 35-45
-
-
Kalman, R.E.1
-
29
-
-
0019039869
-
Adaptive real-time forecast of river flow rates from rainfall data
-
Bolzern P.M., Ferrario G., and Fronza G. Adaptive real-time forecast of river flow rates from rainfall data. J. Hydrol. 47 (1980) 251-267
-
(1980)
J. Hydrol.
, vol.47
, pp. 251-267
-
-
Bolzern, P.M.1
Ferrario, G.2
Fronza, G.3
-
30
-
-
0021639809
-
Synthetic streamflow forecast generation
-
Lettenmaier D.P. Synthetic streamflow forecast generation. J. Hydraul. Eng. ASCE 110 3 (1984) 277-289
-
(1984)
J. Hydraul. Eng.
, vol.ASCE 110
, Issue.3
, pp. 277-289
-
-
Lettenmaier, D.P.1
-
31
-
-
0022266166
-
River flow forecasting model for Sturgeon River
-
Burn D.H., and McBean E.A. River flow forecasting model for Sturgeon River. J. Hydraul. Eng. ASCE 111 2 (1985) 316-333
-
(1985)
J. Hydraul. Eng.
, vol.ASCE 111
, Issue.2
, pp. 316-333
-
-
Burn, D.H.1
McBean, E.A.2
-
32
-
-
0028667119
-
Time series modeling for long-range streamflow forecasting
-
Bender M., and Simonivic S. Time series modeling for long-range streamflow forecasting. J. Water Resour. Plan. Manage. ASCE 118 6 (1992) 857-869
-
(1992)
J. Water Resour. Plan. Manage.
, vol.ASCE 118
, Issue.6
, pp. 857-869
-
-
Bender, M.1
Simonivic, S.2
-
34
-
-
0033097707
-
A comparison between neural network forecasting techniques-case study: river flow forecasting
-
Atiya A.F., El-Shoura S.M., Shaheen S.I., and El-Sherif M.S. A comparison between neural network forecasting techniques-case study: river flow forecasting. IEEE Trans. Neural Networks 10 2 (1999) 402-409
-
(1999)
IEEE Trans. Neural Networks
, vol.10
, Issue.2
, pp. 402-409
-
-
Atiya, A.F.1
El-Shoura, S.M.2
Shaheen, S.I.3
El-Sherif, M.S.4
-
35
-
-
0035494446
-
Short-term water demand forecast modeling at IIT Kanpur using artificial neural networks
-
Jain A., Varshney A.K., and Joshi U.C. Short-term water demand forecast modeling at IIT Kanpur using artificial neural networks. Water Resour. Manage. 15 5 (2001) 299-321
-
(2001)
Water Resour. Manage.
, vol.15
, Issue.5
, pp. 299-321
-
-
Jain, A.1
Varshney, A.K.2
Joshi, U.C.3
-
36
-
-
0036640826
-
Evaluation of short-term water demand forecast modeling techniques: conventional v/s artificial intelligence
-
Jain A., and Ormsbee L.E. Evaluation of short-term water demand forecast modeling techniques: conventional v/s artificial intelligence. J. Am. Water Works Assoc. 94 7 (2002) 64-72
-
(2002)
J. Am. Water Works Assoc.
, vol.94
, Issue.7
, pp. 64-72
-
-
Jain, A.1
Ormsbee, L.E.2
-
37
-
-
0037340658
-
Comparative analysis of event based rainfall-runoff modeling techniques-deterministic, statistical, and artificial neural networks
-
Jain A., and Indurthy S.K.V.P. Comparative analysis of event based rainfall-runoff modeling techniques-deterministic, statistical, and artificial neural networks. J. Hydrol. Eng. ASCE 8 2 (2003) 93-98
-
(2003)
J. Hydrol. Eng.
, vol.ASCE 8
, Issue.2
, pp. 93-98
-
-
Jain, A.1
Indurthy, S.K.V.P.2
-
38
-
-
0035450182
-
Multivariate reservoir inflow forecasting using temporal neural networks
-
Coulibaly P., Anctil F., and Bobee B. Multivariate reservoir inflow forecasting using temporal neural networks. J. Hydrol. Eng. ASCE 6 5 (2001) 367-376
-
(2001)
J. Hydrol. Eng.
, vol.ASCE 6
, Issue.5
, pp. 367-376
-
-
Coulibaly, P.1
Anctil, F.2
Bobee, B.3
-
39
-
-
0003604539
-
-
Water Resources Publications, Littleton, CO, USA
-
Salas J.D., Delleur J.W., Yevjevich V., and Lane W.L. Applied Modeling of Hydrologic Time Series (1997), Water Resources Publications, Littleton, CO, USA
-
(1997)
Applied Modeling of Hydrologic Time Series
-
-
Salas, J.D.1
Delleur, J.W.2
Yevjevich, V.3
Lane, W.L.4
-
40
-
-
0022471098
-
Learning representations by back-propagating errors
-
Rumelhart D.E., Hinton G.E., and Williams R.J. Learning representations by back-propagating errors. Nature 323 (1986) 533-536
-
(1986)
Nature
, vol.323
, pp. 533-536
-
-
Rumelhart, D.E.1
Hinton, G.E.2
Williams, R.J.3
-
41
-
-
12244280869
-
An evaluation of the available techniques for estimating missing fecal coliform data
-
Jain A., and Ormsbee L.E. An evaluation of the available techniques for estimating missing fecal coliform data. J. Am. Water Resour. Assoc. 40 6 (2004) 1617-1630
-
(2004)
J. Am. Water Resour. Assoc.
, vol.40
, Issue.6
, pp. 1617-1630
-
-
Jain, A.1
Ormsbee, L.E.2
-
42
-
-
33644655239
-
An evaluation of artificial neural network technique for the determination of infiltration model parameters
-
Jain A., and Kumar A. An evaluation of artificial neural network technique for the determination of infiltration model parameters. J. Appl. Soft Comput. 6 3 (2006) 272-282
-
(2006)
J. Appl. Soft Comput.
, vol.6
, Issue.3
, pp. 272-282
-
-
Jain, A.1
Kumar, A.2
-
43
-
-
33644636765
-
A comparative analysis of training methods for artificial neural network rainfall-runoff modeling
-
Srinivasulu S., and Jain A. A comparative analysis of training methods for artificial neural network rainfall-runoff modeling. J. Appl. Soft Comput. 6 3 (2006) 295-306
-
(2006)
J. Appl. Soft Comput.
, vol.6
, Issue.3
, pp. 295-306
-
-
Srinivasulu, S.1
Jain, A.2
|