Adaptive neurofuzzy computing technique for evapotranspiration estimation

Journal of Irrigation and Drainage Engineering

Volumn 133, Issue 4, 2007, Pages 368-379

  Kişi, Özgür ^a   Öztürk, Özgür ^a  

^a ERCIYES UNIVERSITY   (Turkey)

Author keywords

California; Computation; Evapotranspiration; Fuzzy sets; Models; Neural networks

Indexed keywords

ADAPTIVE NEUROFUZZY COMPUTING TECHNIQUE; PENMAN-MONTEITH EQUATION;

ADAPTIVE SYSTEMS; FUZZY NEURAL NETWORKS; FUZZY SETS; IRRIGATION; MATHEMATICAL MODELS; STATISTICS;

EVAPOTRANSPIRATION;

ADAPTIVE SYSTEMS; EVAPOTRANSPIRATION; FUZZY NEURAL NETWORKS; FUZZY SETS; IRRIGATION; MATHEMATICAL MODELS; STATISTICS;

ACCURACY ASSESSMENT; ARTIFICIAL NEURAL NETWORK; DATA SET; EMPIRICAL ANALYSIS; EVAPOTRANSPIRATION; FUZZY MATHEMATICS; IRRIGATION; NUMERICAL MODEL;

CALIFORNIA; NORTH AMERICA; UNITED STATES;

EID: 34547116654     PISSN: 07339437     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)0733-9437(2007)133:4(368)     Document Type: Article

References (50)

1. Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. (1998). "Crop evapotranspiration guidelines for computing crop water requirements." Proc., FAO Irrigation and Drainage, Paper No. 56, Food and Agriculture Organization of the United Nations, Rome.
2. Allen, R. G., Smith, M., Perrier, A., and Pereira, L. S. (1994). "An update for the calculation of reference evapotranspiration." ICID Bull. IIDBAS0300-2810, 43(2), 35-92.
3. ASCE Task Committee. (2000a). "Artificial neural networks in hydrology I." J. Hydrol. Eng. JHYEFF1084-069910.1061/ (ASCE)1084-0699(2000)5:2(115), 5(2), 115-123.
4. ASCE Task Committee. (2000b). "Artificial neural networks in hydrology II." J. Hydrol. Eng. JHYEFF1084-069910.1061/ (ASCE)1084-0699(2000)5:2(124), 5(2), 124-132.
5. Brutsaert, W. H. (1982). Evaporation into the atmosphere, Reidel, Dordrecht, Holland.
6. Cancelliere, A., Giuşiano, G., Ancarani, A., and Rossi, G. (2002). "A neural networks for deriving irrigation reservoir operating rules." Water Resour. Manage. WRMAEJ0920-4741, 16, 71-88.
7. Chen, J., and Adams, B. J. (2006). "Integration of artificial neural networks with conceptual models in rainfall-runoff modeling." J. Hydrol. JHYDA70022-1694, 318, 232-249.
8. Cigizoglu, H. K. (2003). "Estimation, forecasting, and extrapolation of flow data by artificial neural networks." Hydrol. Sci. J. HSJODN0262-666710.1623/hysj.48.3.349.45288, 48(3), 349-361.
9. Cigizoglu, H. K. (2004). "Estimation and forecasting of daily suspended sediment data by multi layer perceptrons." Adv. Water Resour. AWREDI0309-170810.1016/j.advwatres.2003.10.003, 27, 185-195.
10. Cigizoglu, H. K. (2005). "Application of the generalized regression neural networks to intermittent flow forecasting and estimation." J. Hydrol. Eng. JHYEFF1084-069910.1061/(ASCE)1084-0699(2005)10:4(336), 10(4), 336-341.
11. Cigizoglu, H. K., and Kisi, O. (2005). "Flow prediction by three back propagation techniques using k-fold partitioning of neural network training data." Nord. Hydrol. NOHYBB0029-1277, 36(1), 49-64.
12. Cigizoglu, H. K., and Kisi, O. (2006). "Methods to improve the neural network performance in suspended sediment estimation." J. Hydrol. JHYDA70022-1694, 317, 221-238.
13. Drake, J. T. (2000). "Communications phase synchronization using the adaptive network fuzzy inference system." Ph.D. thesis, New Mexico State Univ., Las Cruces, N.M.
14. Hargreaves, G. H., and Samani, Z. A. (1985). "Reference crop evapotranspiration from temperature." Appl. Eng. Agric. ZZZZZZ0883-8542, 1(2), 96-99.
15. Haykin, S. (1998). Neural networks-A comprehensive foundation, 2nd Ed., Prentice-Hall, Upper Saddle River, N.J., 26-32.
16. Hidalgo, H. G., Cayan, D. R., and Dettinger, M. D. (2005). "Sources of variability of evapotranspiration in California." J. Hydroeteorol., 6, 3-19.
17. Jain, S. K., Das, D., and Srivastava, D. K. (1999). "Application of ANN for reservoir inflow prediction and operation." J. Water Resour. Plann. Manage. JWRMD50733-949610.1061/ (ASCE)0733-9496(1999)125:5(263), 125(5), 263-271.
18. Jang, J.-S. R. (1993). "ANFIS: Adaptive-network-based fuzzy inference system." IEEE Trans. Syst. Man Cybern. ISYMAW0018-947210.1109/21.256541, 23(3), 665-685.
19. Jang, J.-S. R., Sun, C.-T., and Mizutani, E. (1997). Neurofuzzy and soft computing: A computational approach to learning and machine intelligence, Prentice-Hall, Upper Saddle River, N.J.
20. Jensen, M. E., Burman, R. D., and Allen, R. G. (1990). Evapotranspiration and Irrigation Water Requirements. ASCE Manuals and Reports on Engineering Practices No. 70, ASCE, New York.
21. Jones, J. W., and Ritchie, J. T. (1990). "Crop growth models." Management of farm irrigation system, G. J. Hoffman, T. A. Howel, and K. H. Solomon, eds., ASAE Monograph No. 9, ASAE, St. Joseph, Mich., 63-89.
22. Karunanithi, N., Grenney, W. J., Whitley, D., and Bovee, K. (1994). "Neural networks for river flow prediction." J. Comput. Civ. Eng. JCCEE50887-380110.1061/(ASCE)0887-3801(1994)8:2(201), 8(2), 201-220.
23. Kisi, O. (2004a). "River flow modeling using artificial neural networks." J. Hydrol. Eng. JHYEFF1084-069910.1061/ (ASCE)1084-0699(2004)9:1(60), 9(1), 60-63.
24. Kisi, O. (2004b). "Multilayer perceptrons with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation." Hydrol. Sci. J. HSJODN0262-666710.1623/ hysj.49.6.1025.55720, 49(6), 1025-1040.
25. Kisi, O. (2005a). "Suspended sediment estimation using neurofuzzy and neural network approaches." Hydrol. Sci. J. HSJODN0262-666710.1623/hysj.2005.50.4.683, 50(4), 683-696.
26. Kisi, O. (2005b). "Daily river flow forecasting using artificial neural networks and auto regressive models." Turk. J. Eng. Environ. Sci. TJESEC1300-0160, 29, 9-20.
27. Kisi, O. (2006). "Evapotranspiration estimation using feed-forward neural networks." Nord. Hydrol. NOHYBB0029-1277, 37(3), 247-260.
28. Kisi, O., and Yildirim, G. (2005a). "Discussion of 'Estimating actual evapotranspiration from limited climatic data using neural computing technique.'" J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/(ASCE)0733-9437(2005)131:2(219), 131(2), 219-220.
29. Kisi, O., and Yildirim, G. (2005b). "Discussion of 'Forecasting of reference evapotranspiration by artificial neural networks.'" J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/ (ASCE)0733-9437(2005)131:4(390), 131(4), 390-391.
30. Kumar, D. N., Raju, K. S., and Sathish, T. (2004). "River flow forecasting using recurrent neural networks." Water Resour. Manage. WRMAEJ0920-4741, 18, 143-161.
31. Kumar, M., Raghuwanshi, N. S., Singh, R., Wallender, W. W., and Pruitt, W. O. (2002). "Estimating evapotranspiration using artificial neural network." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/ (ASCE)0733-9437(2002)128:4(224), 128(4), 224-233.
32. Lippman, R. (1987). "An introduction to computing with neural nets." IEEE ASSP Mag. ZZZZZZ0740-7467., 4, 4-22.
33. Maier, H. R., and Dandy, G. C. (2000). "Neural network for the prediction and forecasting of water resources variables: A review of modeling issues and applications." Environ. Modell. Software EMSOFT1364-815210.1016/S1364-8152(99)00007-9, 15, 101-124.
34. Minnes, A. W., and Hall, M. J. (1996). "Artificial neural networks as rainfall-runoff models." Hydrol. Sci. J. HSJODN0262-6667, 41(3), 399-416.
35. Naoum, S., and Tsanis, I. K. (2003). "Hydroinformatics in evapotranspiration estimation." Environ. Modell. Software EMSOFT1364-8152, 18, 261-271.
36. Pruitt, W. O., and Doorenbos, J. (1977). "Empirical calibration, a requisite for evapotranspiration formulae based on daily or longer mean climatic data." Proc., Int. Round Table Conf. on Evapotranspiration, Budapest, Hungary, International Commission on Irrigation and Drainage.
37. Raghuwanshi, N. S., Singh, R., and Reddy, L. S. (2006). "Runoff and sediment yield modeling using artificial neural networks: Upper Siwane River, India." J. Hydrol. Eng. JHYEFF1084-069910.1061/ (ASCE)1084-0699(2006)11:1(71), 11(1), 71-79.
38. Rumelhart, D. E., Hinton, G. E., and Williams, R. J. (1986). "Learning internal representation by error propagation." Parallel distributed processing, D. E. Rumelhart and J. L. McClelland, eds., Vol. 1, MIT, Cambridge, Mass.
39. Russel, S. O., and Campbell, P. F. (1996). "Reservoir operating rules with fuzzy programming." J. Water Resour. Plann. Manage. JWRMD50733-949610.1061/(ASCE)0733-9496(1996)122:3(165), 122(3), 165-170.
40. Sahoo, G. B., and Ray, C. (2006). "Flow forecasting for a Hawaii stream using rating curves and neural networks." J. Hydrol. JHYDA70022-1694, 317, 63-80.
41. Smith, M., Allen, R., and Pereira, L. (1997). Revised FAO methodology for crop water requirements, Land and Water Development Division, FAO, Rome.
42. Snyder, R., and Pruitt, W. (1985). "Estimating reference evapotranspiration with hourly data." California Irrigation Management Information System Final Rep., Land, Air and Water Resources Paper #10013, Univ. of California at Davis, Davis, Calif.
43. Sobrino, J. A., Gomez, M., Munoz, J. C. J., Olioso, A., and Chehbouni, G. (2005). "A simple algorithm to estimate evapotranspiration from DAIS data: Application to the DAISEX campaigns." J. Hydrol. JHYDA70022-1694, 315, 117-125.
44. Sudheer, K. P., Gosain, A. K., and Ramasastri, K. S. (2003b). "Estimating actual evapotranspiration from limited climatic data using neural computing technique." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/(ASCE)0733-9437(2003)129:3(214), 129(3), 214-218.
45. Sudheer, K. P., Nayak, P. C., and Ramasastri, K. S. (2003a). "Improving peak flow estimates in artificial neural network." Hydrolog. Process. HYPRE30885-608710.1002/hyp.5103, 17, 677-686.
46. Supharatid, S. (2003). "Application of a neural network model in establishing a stage-discharge relationship for a tidal river." Hydrolog. Process. HYPRE30885-608710.1002/hyp.1278, 17, 3085-3099.
47. Tayfur, G. (2002). "Artificial neural networks for sheet sediment transport." Hydrol. Sci. J. HSJODN0262-6667, 47(6), 879-892.
48. Trajkovic, S. (2005). "Temperature-based approaches for estimating reference evapotranspiration." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/(ASCE)0733-9437(2005)131:4(316), 131(4), 316-323.
49. Trajkovic, S., Todorovic, B., and Stankovic, M. (2003). "Forecasting reference evapotranspiration by artificial neural networks." J. Irrig. Drain. Eng. JIDEDH0733-943710.1061/ (ASCE)0733-9437(2003)129:6(454), 129(6), 454-457.
50. Vernieuwe, H., Georgieva, O., Baets, B. D., Pauwels, V. R. N., Verhoest, N. E. C., and Troch, F. P. D. (2005). "Comparison of data-driven Takagi-Sugeno models of rainfall-discharge dynamics." J. Hydrol. JHYDA70022-169410.1016/j.jhydrol.2004.07.001, 302, 173-186.