Discussion of "application of neural networks for estimation of concrete strength" by Jong-In Kim, Doo Kie Kim, Maria Q. Feng, and Frank Yazdani

Journal of Materials in Civil Engineering

Volumn 17, Issue 6, 2005, Pages 736-739

  Jain, Ashu ^a   Misra, Sudhir ^a   Jha, Sanjeev Kumar ^a   Kim, Jong In ^b   Kim, Doo Kie ^c   Feng, Maria Q ^d   Yazdani, Frank ^e  

^a INDIAN INSTITUTE OF TECHNOLOGY KANPUR   (India)

^b Daegu University   (South Korea)

^c Kunsan National University   (South Korea)

^d UNIVERSITY OF CALIFORNIA   (United States)

^e North Dakota State University   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 28844445258     PISSN: 08991561     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)0899-1561(2005)17:6(736)     Document Type: Note

References (15)

1. Cladera, A., and Mari, R. (2004). "Shear design procedures for reinforced normal and high-strength concrete beams using artificial neural networks. Part I: Beams without stirrups." Eng. Struct., 26(7), 917-926.
2. Garret, J. H., Jr., Ranjithan, S., and Eheart, J. W. (1992). "Application of neural network to groundwater remediation." Expert Systems for Civil Engineers: Knowledge Representation, R. H. Allen, ed., ASCE, New York, 259-269.
3. Ghaboussi, J., Garret, J. H., Jr., and Wu, X. (1991). "Neural networks and their application to civil engineering problems." Expert Systems for Civil Engineers: Knowledge Representation, R. H. Allen, ed., ASCE, New York, 104-143.
4. Jain, A., and Srinivasulu, S. (2004). "Development of effective and efficient rainfall-runoff models using integration of deterministic, realcoded genetic algorithms, and artificial neural network techniques." Water Resour Res., 40(4).
5. Jain, A., Sudheer, K. P., and Srinivasulu, S. (2004). "Identification of physical processes inherent in artificial neural network rainfall runoff models." Hydrolog. Process., 118(3). 571-581.
6. Ni, H. G., and Wang, J. Z. (2000). "Prediction of compressive strength of concrete by neural networks." Cem. Concr. Res., 30(8), 1245-1250.
7. Park, D. C., El-Sharkawi, M. A., Mark, R. J. II, Atlas, L. E., and Damborg, M. J. (1991). "Electric load forecasting using an artificial neural network." IEEE Trans. Power Syst., 6(2), 442-449.
8. Rajasekaran, S., and Lee, S. C. (2003). "Prediction of concrete strength using serial functional network model." Struct. Eng. Mech., 16(1), 83-99.
9. Rehak, D. R., Thewalt, C. R., and Doo, L. B. (1989). "Neural network approaches in structural mechanics computations." Proc., Structures Congress'89, ASCE, New York, pp. 168-176.
10. Sharda, R., and Patil, R. B. (1990). "Connectionist approach to time series prediction: An empirical test." Technical Rep. No. 90-26:11-90, College of Business Administration, Oklahoma State Univ., Stillwater, Oklahoma.
11. Sudheer, K. P., and Jain, A. (2004). "Explaining the internal behavior of artificial neural network river flow models." Hydrolog. Process., 118(4), 833-844.
12. Wang, J. Z., Ni, H. G., and He, J. Y. (1999). "Application of automatic acquisition of knowledge to mix design of concrete." Cem. Concr Res., 29(12), 1875-1880.
13. Wilby, R. L., Abrahart, R. J., and Dawson, C. W. (2003). "Detection of conceptual model rainfall-runoff processes inside an artificial neural network." Hydrol. Sci. J., 48(2), 163-181.
14. Zhao, Z. Y., and Ren, L. Q. (2002). "Failure criterion of concrete under triaxial stresses using neural networks." Comput. Aided Civ. Infrastruct. Eng., 17(1), 68-73.
15. Ni, H. G., and Wang, J. Z. (2000). "Prediction of compressive strength of concrete by neural networks." Cem. Concr. Res., 30(8), 1245-1250.