Modeling of dissolved oxygen concentration using different neural network techniques in Foundation Creek, El Paso County, Colorado

Journal of Environmental Engineering (United States)

Volumn 138, Issue 6, 2012, Pages 654-662

  Ay, Murat ^a   Kisi, Ozgur ^b,c  

^a BOZOK UNIVERSITY   (Turkey)

^b CANIK BASARI UNIVERSITY   (Turkey)

^c ERCIYES UNIVERSITY   (Turkey)

Author keywords

Colorado; Dissolved oxygen; Neural networks; Regression models

Indexed keywords

COLORADO; COMPARISON RESULT; DETERMINATION COEFFICIENTS; DISSOLVED OXYGEN CONCENTRATIONS; ELECTRICAL CONDUCTIVITY; INPUT PARAMETER; INPUT VARIABLES; MEAN ABSOLUTE ERROR; MULTI LAYER PERCEPTRON; MULTILINEAR REGRESSION; NEURAL NETWORK MODEL; NEURAL NETWORK TECHNIQUES; RADIAL BASIS NEURAL NETWORKS; REGRESSION MODEL; ROOT MEAN SQUARE ERRORS; UPSTREAM STATIONS;

DISSOLVED OXYGEN; ELECTRIC CONDUCTIVITY; MEAN SQUARE ERROR; NEURAL NETWORKS; REGRESSION ANALYSIS;

RIVERS;

ARTIFICIAL NEURAL NETWORK; CONCENTRATION (COMPOSITION); DATA SET; DISSOLVED OXYGEN; ELECTRICAL CONDUCTIVITY; EXPERIMENTAL STUDY; NUMERICAL METHOD; NUMERICAL MODEL; PH; REGRESSION ANALYSIS; TEMPERATURE EFFECT;

COLORADO; EL PASO COUNTY [COLORADO]; UNITED STATES;

EID: 84868601226     PISSN: 07339372     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)EE.1943-7870.0000511     Document Type: Article

References (45)

1. Akkoyunlu, A., Altun, H., and Cigizoglu, H. K. (2011). " Depth-integrated estimation of dissolved oxygen in a lake." J. Environ. Eng., 137 (10), 961-967.
2. Brenner, A., Shacham, M., and Cutlip, B. M. (2005). " Applications of mathematical software packages for modelling and simulations in environmental engineering education." Environ. Modell. Softw. 1364-8152, 20 (10), 1307-1313. 10.1016/j.envsoft.2004.09.007
3. Brodnjak-Vonina, D., Dobnik, D., Novi, M., and Zupan, J. (2002). " Chemometrics characterisation of the quality of river water." Anal. Chim. Acta ACACAM 0003-2670, 462 (1), 87-100. 10.1016/S0003-2670(02)00298-2
4. Broomhead, D., and Lowe, D. (1988). " Multivariable functional interpolation and adaptive networks." Complex Syst. CPSYEN 0891-2513, 2 (6), 321-355.
5. Chatterjee, S., and Hadi, A. S. (1986). " Influential observations, high leverage points, and outliers in linear regression." Stat. Sci. STSCEP 0883-4237, 1 (3), 379-416. 10.1214/ss/1177013622
6. Cigizoglu, H. K., and Kisi, O. (2006). " Methods to improve the neural network performance in suspended sediment estimation." J. Hydrol. (Amsterdam) JHYDA7 0022-1694, 317 (3-4), 221-238. 10.1016/j.jhydrol.2005.05.019
7. Cox, B. A. (2003). " A review of dissolved oxygen modeling techniques for lowland rivers." Sci. Total Environ. STENDL 0048-9697, 314-316, 303-334.
8. Dogan, E., Sengorur, B., and Koklu, R. (2009). " Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique." J. Environ. Manage. JEVMAW 0301-4797, 90 (2), 1229-1235. 10.1016/j.jenvman.2008.06.004
9. Hagan, M. T., and Menhaj, M. B. (1994). " Training feed forward networks with the marquardt algorithm." IEEE Trans. Neural Netw. ITNNEP 1045-9227, 5 (6), 989. 10.1109/72.329697
10. Hanbay, D., Turkoglu, I., and Demir, Y. (2008). " Prediction of wastewater treatment plant performance based on wavelet packet decomposition and neural networks." Expert Syst. Appl. ESAPEH 0957-4174, 34 (2), 1038-1043. 10.1016/j.eswa.2006.10.030
11. Haykin, S. (1994). Neural network: A comprehensive foundation, MacMillan, New York.
12. Haykin, S. (1998). Neural networks: A comprehensive foundation, 2nd Ed., Prentice-Hall, Upper Saddle River, NJ.
13. Hem, J. D. (1989). " Study and interpretation of the chemical characteristic of natural water." Techniques of Water-Supply paper, 2254, U.S. Geological Survey, Washington, DC.
14. Kalff, J. (2002). Limnology: Inland water ecosystems, Prentice-Hall, Upper Saddle River, NJ.
15. Kisi, O. (2004). " Multi-layer perceptrons with Levenberg-Marquardt training algorithm for suspended sediment concentration prediction and estimation." Hydrol. Sci. J. HSJODN 0262-6667, 49 (6), 1025-1040. 10.1623/hysj.49.6.1025.55720
16. Kisi, O. (2005). " Suspended sediment estimation using neuro-fuzzy and neural network approaches." Hydrol. Sci. J. HSJODN 0262-6667, 50 (4), 683-696.
17. Kisi, O. (2007). " Streamflow forecasting using different artificial neural network algorithms." J. Hydrol. Eng. JHYEFF 1084-0699, 12 (5), 532-539. 10.1061/(ASCE)1084-0699(2007)12:5(532)
18. Kisi, O. (2009). " Modeling monthly evaporation using two different neural computing techniques." Irrig. Sci. IRSCD2 0342-7188, 27 (5), 417-430. 10.1007/s00271-009-0158-z
19. Kisi, O., and Ay, M. (2011). " Modeling dissolved oxygen (DO) concentration using different neural network technique." Int. Balkans Conf. on Challenges of Civil Engineering, BCCCE, EPOKA Univ., Tirana, Albania.
20. Kuo, J. T., Hsieh, M. H., Lung, W. S., and She, N. (2007). " Using artificial neural network for reservoir eutrophication prediction." Ecol. Model ECMODT 0304-3800, 200 (1-2), 171-177. 10.1016/j.ecolmodel.2006.06.018
21. Lee, G. C., and Chang, S. H. (2003). " Radial basis function networks applied to DNBR calculation in digital core protection systems." Ann. Nucl. Eng. ANENDJ 0306-4549, 30 (15), 1516-1572.
22. Lerner, B., Levinstein, M., Rosenberg, B., Guterman, H., Dinsteun, I., and Romen, Y. (1994). "Feature selection and chromosomes classification using a multilayer perceptron neural network." IEEE Int. Conf. on Neural Networks, Orlando, FL, 3540-3545.
23. Lower Great Miami Watershed Enhancement Program (WEP). 1996. Miami valley index, Miami Valley Regional Planning Commission (MVRPC), Dayton, OH.
24. Marquardt, D. (1963). " An algorithm for least squares estimation of non-linear parameters." J. Soc. Ind. Appl. Maths. JSIMAV 0368-4245, 11 (2), 431-441.
25. Mullholand, P. J., Houser, J. N., and Maloney, O. K. (2005). " Stream diurnal dissolved oxygen profiles as indicators of in-stream metabolism and disturbance effects: Fort Benning as a case study." Ecol. Indic. EICNBG 1470-160X, 5 (3), 243-252. 10.1016/j.ecolind.2005.03.004
26. Noble, R. T., and Fuhrman, J. A. (2001). " Enteroviruses detected by reverse transcriptase polymerase chain reaction from the coastal waters of Santa Monica Bay, California: Low correlation to bacterial indicator levels." Hydrobiologia HYDRB8 0018-8158, 460 (1-3), 175-184. 10.1023/A:1013121416891
27. Official Gazette. (2004). Water pollution control regulation, No. 25687, Prime Ministry Office of Turkey, Ankara, Turkey (in Turkish).
28. Ozkan, O., Ozdemir, O., and Azgin, S. T. (2009). " Prediction of Biochemical oxygen demand in a wastewater treatment plant by artificial neural networks." Asian J. Chem. AJCHEW, 21 (6), 4821-4830.
29. Palani, S., Liong, S. Y., and Tkalich, P. (2008). " An ANN application for water quality forecasting." Mar. Pollut. Bull. MPNBAZ 0025-326X, 56 (9), 1586-1597. 10.1016/j.marpolbul.2008.05.021
30. Poggio, T., and Girosi, F. (1990). " Regularization algorithms for learning that are equivalent to multilayer networks." Science SCIEAS 0036-8075, 247 (4945), 978-982. 10.1126/science.247.4945.978
31. Quinn, N. T. W., Jacobs, K., Chen, K. W., and Stringfellow, W. T. (2005). " Elements of decision support system for real-time management of dissolved oxygen in the San Joaquin River deep water ship channel." Environ. Model. Software EMSOFT 1364-8152, 20 (12), 1495-1504. 10.1016/j.envsoft.2004.08.014
32. Radtke, D. B., Kurklin, J. K., and Wilde, F. D., eds. (2003). " pH (version 1.2)." Chapter A6, Section 6.4, Techniques of water-resources investigations, book 9, U.S. Geological Survey, Reston, VA.
33. Radtke, D. B. Busenberg, E., Wilde, F. D., and Kurklin, J. K., eds. (2004). " Temperature (version 1.2)." Chapter A6, Section 6.1, Techniques of water-resources investigations, book 9, U.S. Geological Survey, Reston, VA.
34. Radtke, D. B., Davis, J. V., and Wilde, F. D., eds. (2005). " Specific electrical conductance (version 1.2)." Chapter A6, Section 6.3, Techniques of water-resources investigations, book 9, U.S. Geological Survey, Reston, VA.
35. Ranković, V., Ranković, J., Ranković, I., Ostojić, A., and Ćomić, L. (2010). " Neural network modeling of dissolved oxygen in the Gruza reservoir, Serbia." Ecol. Modell., 221 (8), 1239-1244.
36. Reeves, R. L., Grant, S. B., Mrse, R. D., Copil Oancea, C. M., Sanders, B. F., and Boehm, A. B. (2004). " Scaling and management of fecal indicator bacteria in runoff from a coastal urban watershed in Southern California." Environ. Sci. Technol. ESTHAG 0013-936X, 38 (9), 2637-2648. 10.1021/es034797g
37. Strategic Assessment of Florida's Environment (SAFE). (1995). Florida stream water quality index, statewide summary, Florida Department of Environmental Protection, Tallahassee, FL.
38. Schmid, B. H., and Koskiaho, J. (2006). " Artificial neural network modeling of dissolved oxygen in a Wetland Pond: The case of Hovi, Finland." J. Hydrol. Eng. JHYEFF 1084-0699, 11 (2), 188-192. 10.1061/(ASCE)1084- 0699(2006)11:2(188)
39. Sengorur, B., Dogan, E., Koklu, R., and Samandar, A. (2006). " Dissolved oxygen estimation using artificial neural network for water quality control." Fresen. Environ. Bull. FENBEL 1018-4619, 15 (9a), 1064-1067.
40. Singh, K. P., Basant, A., Malik, A., and Jain, G. (2009). " Artificial neural network modeling of the river water quality'a case study." Ecol. Model. ECMODT 0304-3800, 220 (6), 888-895. 10.1016/j.ecolmodel.2009.01.004
41. Soyupak, S., Karaer, F., Gürbüz, H., Kivrak, E., Sentürk, E., and Yazici, A. (2003). " A neural network-based approach for calculating dissolved oxygen profiles in reservoirs." Neural Comput. Appl. 0941-0643, 12 (3-4), 166-172. 10.1007/s00521-003-0378-8
42. Spanou, M., and Chen, D. (1999). " An object-oriented tool for the control of point-source pollution in river systems." Environ. Modell. Softw. 1364-8152, 15 (1), 35-54. 10.1016/S1364-8152(99)00021-3
43. United States Environmental Protection Agency (EPA). (1994). Water quality standards handbook, 2nd Ed., U.S. Environmental Protection Agency, Office of Water, Washington, DC.
44. Williams, R. J., White, C., Harrow, M. L., and Neal, C. (2000). " Temporal and small-scale spatial variations of dissolved oxygen in the Rivers Thames, Pang and Kennet, UK." Sci. Total Environ., 251-252, 497-510.
45. Ying, Z., Jun, N., Fuyi, C., and Liang, G. (2007). " Water quality forecast through application of BP neural network at Yuqiao reservoir." J. Zheijang Univ. Sci. A 1673-565X, 8 (9), 1482-1487.