Retraction Notice to Computer-aided prediction of physical and mechanical properties of high strength concrete containing Fe2O3 nanoparticles
1
Department of Materials Science, Saveh Branch, Islamic Azad University, Saveh, Iran
Publication date: 2012-09-01
Cement Wapno Beton 17(5) 265-285 (2012)
ABSTRACT
Retraction Notice to 17(5) (2012) 265-285 Concerns: A. Nazari, Cement Wapno Beton 17(5) (2012) 265-285. By the decision of the Editor-in-Chief, article has been withdrawn from Issue 5 Volume 17 (2012) of the Cement Wapno Beton journal. The withdrawn article contains content borrowed without citation. We would like to apologize to the Readers of Cement Wapno Beton for this situation. We assure You that the Editorial Board makes every effort to avoid such situations. The authors did not respond to messages regarding the withdrawal of the article sent to them by the Editorial Office.
REFERENCES (31)
1.
G. Ye, P. Lura, K. van Breugel, Modeling of water permeability in cementitious materials. Mat. and Struct., 39, 877 (2006).
2.
N. Hong-Guang, W. Ji-Zong, Prediction of compressive strength of concrete by neural networks. Cem. Concr. Res., 30, 8, 1245 (2000).
3.
M. Pala, O. Ozbay, A. Oztas, M. I. Yuce, Appraisal of long-term effects of fl y ash and silica fume on compressive strength of concrete by neural networks. Constr. Build. Mat., 21, 2, 384 (2005).
4.
S. Akkurt, G. Tayfur, S. Can, Fuzzy logic model for prediction of cement compressive strength. Cem. Concr. Res., 34, 8, 1429 (2004).
5.
A. Baykasog˘lu, T. Dereli, S. Tanıs, Prediction of cement strength using soft computing techniques. Cem. Concr. Res., 34, 11, 2083 (2004).
6.
S. Akkurt, S. Ozdemir, G. Tayfur, B. Akyol, The use of GA-ANNs in the modelling of compressive strength of cement mortar. Cem. Concr. Res., 33, 7, 973 (2003).
7.
A. Cevik, M. Sonebi, Genetic programming based formulation for fresh and hardened properties of self-compacting concrete containing pulverised fuel ash. Constr. Build. Mat., 23, 7, 2614 (2009).
8.
A. Cevik, M. Sonebi, Modelling the performance of self-compacting SIFCON of cement slurries using genetic programming technique. Comput. Concr., 5, 5, 475 (2008).
9.
ASTM C150, Standard Specifi cation for Portland Cement, annual book of ASTM standards, ASTM, Philadelphia, PA; 2001.
10.
ASTM C39, Standard Test Method for Compressive Strength of Cylindrical Concrete Specimens, ASTM, Philadelphia, PA; 2001.
11.
ASTM C642, Standard Test Method for Density, Absorption, and Voids in Hardened Concrete, ASTM, Philadelphia, PA; 2001.
12.
J. Y. Shih, T. P. Chang, T. C. Hsiao, Effect of nanosilica on characterization of Portland cement composite, Cem. Concr. Res., 36, 697 (2006).
13.
A. Nazari, G. Khalaj, S. Riahi, M. J. Khalaj, The infl uence of Al2O3 nanoparticles on the properties of traditional concrete with ground granulated blastfurnace slag as binder. Cement Wapno Beton, 78, 311 (2011).
14.
H. Li, M. Zhang, J. Ou, Flexural fatigue performance of concrete containing nanoparticles for pavement, Int. J. Fatigue, 29, 1292 (2007).
15.
Q. Ye, The study and development of the nano-composite cement structure materials. New building materials, 1, 4 (2001).
16.
A. Mukherjee, S. N. Biswas, Artifi cial neural networks in prediction of mechanical behavior of concrete at high temperature. Nucl. Eng. Design., 178, 1, 1 (1997).
17.
R. Ince, Prediction of fracture parameters of concrete by artifi cial neural networks. Eng. Fract. Mech., 71, 15, 2143 (2004).
18.
W. S. McCulloch, W. Pitts. A logical calculus of the ideas immanent in neural nets. Bull. Math. Biophys., 5, 115, 37 (1943).
19.
F. Rosenblatt, Principles of neuro dynamics: perceptrons and the theory of brain mechanisms. Washington, DC, Spartan Books 1962.
20.
D. E. Rumelhart, G. E. Hinton, R. J. William, Learning internal representation by error propagation. In: Rumelhart DE, McClelland JL, editors. Proceeding parallel distributed processing foundation, vol. 1., Cambridge, MIT Press 1986.
21.
S. W. Liu, J. H. Huang, J. C. Sung, C. C. Lee, Detection of cracks using neural networks and computational mechanics. Comput. Meth. Appl. Mech. Eng., 191, 25–26, 2831 (2002).
22.
J. A. Anderson, Cognitive and psychological computation with neural models. IEEE Trans. Syst. Man. Cybernetics, V. SMC-13, 5, 799 (1983).
23.
J. J. Hopfi eld, Neural networks and physical systems with emergent collective computational abilities. Proc. Nat. Acad. Sci., 79, 2554 (1982).
24.
A.A. Suratgar, M. B. Tavakoli, A. Hoseinabadi, Modifi ed Levenberg– Marquardt method for neural networks training. World Acad. Sci. Eng. Technol., 6, 46 (2005).
25.
J. R. Koza, Genetic programming: on the programming of computers by means of natural selection. Cambridge, MA, MIT Press 1992.
26.
C. Ferreira, Gene expression programming in problem solving. In: Invited tutorial of the 6th online world conference on soft computing in industrial applications, 2001.
27.
C. Ferreira, Gene expression programming: a new adaptive algorithm for solving problems. Complex. Syst., 13, 2, 87 (2001).
28.
C. Ferreira, Gene expression programming: mathematical modeling by an artifi cial intelligence, 2002.
29.
C. Ferreira, Gene expression programming in problem solving. In: 6th Online world conference on soft computing in industrial applications (invited tutorial), 2001.
30.
O. N. Çiftci, S. Fadıloğlu, F. Goğuş, A. Guven, Genetic programming approach to predict a model acidolysis system. Eng. Appl. Artif. Intell., 22, 4–5, 759 (2009).
31.
I. B. Topcu, M. Sarıdemir, Prediction of compressive strength of concrete containing fl y ash using artifi cial neural network and fuzzy logic. Comp. Mater. Sci., 41 3, 305 (2008).
| ISSN: | 1425-8129 |
Całkowita kwota działania: 101 900 PLN
Kwota dofinansowania z MNiE: 85 100 PLN
Celem działania jest podniesienie poziomu technicznego obsługi Autorów i usprawnienie przepływu artykułów w procesie redakcyjnym.
Działania mające realizować powyższy cel polegać będą na:
- wprowadzeniu systemu elektronicznego zarządzania zgłaszaniem, recenzowaniem i przetwarzaniem artykułów,
- zmiana dotychczasowej organizacji strony internetowej,
- integracja numerów DOI (przydzielanych obecnie publikowanym artykułom) z bazą CrossRef.
© 2006-2024 Journal hosting platform by Bentus
We process personal data collected when visiting the website. The function of obtaining information about users and their behavior is carried out by voluntarily entered information in forms and saving cookies in end devices. Data, including cookies, are used to provide services, improve the user experience and to analyze the traffic in accordance with the Privacy policy. Data are also collected and processed by Google Analytics tool (more).
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
You can change cookies settings in your browser. Restricted use of cookies in the browser configuration may affect some functionalities of the website.
