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Volumn 31, Issue , 2019, Pages 743-750

Retraction Note to: Predicting the effects of nanoparticles on early age compressive strength of ash-based geopolymers by artificial neural networks (Neural Computing and Applications, (2019), 31, S2, (743-750), 10.1007/s00521-012-1085-0);Predicting the effects of nanoparticles on early age compressive strength of ash-based geopolymers by artificial neural networks

Author keywords

Artificial neural networks; Compressive strength; Geopolymer; Nanoparticles mixture

Indexed keywords


EID: 85048064734     PISSN: 09410643     EISSN: 14333058     Source Type: Journal    
DOI: 10.1007/s00521-020-05122-z     Document Type: Erratum
Times cited : (15)

References (28)
  • 1
    • 84856120768 scopus 로고    scopus 로고
    • Microstructural and strength evolutions of geopolymer composite reinforced by resin exposed to elevated temperature
    • Zhang YJ, Li S, Wang YC, Xu DL (2012) Microstructural and strength evolutions of geopolymer composite reinforced by resin exposed to elevated temperature. J Non Cryst Solids 358:620–624
    • (2012) J Non Cryst Solids , vol.358 , pp. 620-624
    • Zhang, Y.J.1    Li, S.2    Wang, Y.C.3    Xu, D.L.4
  • 2
    • 33748333230 scopus 로고    scopus 로고
    • Appraisal of long-term effects of fly ash and silica fume on compressive strength of concrete by neural networks
    • Pala M, Ozbay O, Oztas A, Yuce MI (2005) Appraisal of long-term effects of fly ash and silica fume on compressive strength of concrete by neural networks. Constr Build Mater 21(2):384–394
    • (2005) Constr Build Mater , vol.21 , Issue.2 , pp. 384-394
    • Pala, M.1    Ozbay, O.2    Oztas, A.3    Yuce, M.I.4
  • 3
    • 77954142552 scopus 로고    scopus 로고
    • Compressive strength, modulus of elasticity, and water permeability of inorganic polymer concrete
    • Wongpa J, Kiattikomol K, Jaturapitakkul C, Chindaprasirt P (2010) Compressive strength, modulus of elasticity, and water permeability of inorganic polymer concrete. Mater Des 31:4748–4754
    • (2010) Mater Des , vol.31 , pp. 4748-4754
    • Wongpa, J.1    Kiattikomol, K.2    Jaturapitakkul, C.3    Chindaprasirt, P.4
  • 4
    • 0032295215 scopus 로고    scopus 로고
    • Modeling of strength of HPC using ANN
    • Yeh IC (1998) Modeling of strength of HPC using ANN. Cem Concr Res 28(12):1797–1808
    • (1998) Cem Concr Res , vol.28 , Issue.12 , pp. 1797-1808
    • Yeh, I.C.1
  • 5
    • 0031084643 scopus 로고    scopus 로고
    • Concrete strength prediction by mean of neural networks
    • Lai S, Sera M (1997) Concrete strength prediction by mean of neural networks. Constr Build Mater 11(2):93–98
    • (1997) Constr Build Mater , vol.11 , Issue.2 , pp. 93-98
    • Lai, S.1    Sera, M.2
  • 6
    • 0037653583 scopus 로고    scopus 로고
    • Prediction of concrete strength using artificial neural networks
    • Lee SC (2003) Prediction of concrete strength using artificial neural networks. Eng Struct 25(7):849–857
    • (2003) Eng Struct , vol.25 , Issue.7 , pp. 849-857
    • Lee, S.C.1
  • 7
    • 0034242043 scopus 로고    scopus 로고
    • Prediction of compressive strength of concrete by neural networks
    • Hong-Guang N, Ji-Zong W (2000) Prediction of compressive strength of concrete by neural networks. Cem Concr Res 30(8):1245–1250
    • (2000) Cem Concr Res , vol.30 , Issue.8 , pp. 1245-1250
    • Hong-Guang, N.1    Ji-Zong, W.2
  • 8
    • 0035480545 scopus 로고    scopus 로고
    • Neural networks for predicting properties of concretes with admixtures
    • Dias WPS, Pooliyadda SP (2001) Neural networks for predicting properties of concretes with admixtures. Constr Build Mater 15(7):371–379
    • (2001) Constr Build Mater , vol.15 , Issue.7 , pp. 371-379
    • Dias, W.P.S.1    Pooliyadda, S.P.2
  • 9
    • 33646926510 scopus 로고    scopus 로고
    • Predicting the compressive strength and slump of high strength concrete using neural network
    • Oztas A, Pala M, Ozbay E, Kanca E, Caglar N, Asghar Bhatti M (2006) Predicting the compressive strength and slump of high strength concrete using neural network. Constr Build Mater 20(9):769–775
    • (2006) Constr Build Mater , vol.20 , Issue.9 , pp. 769-775
    • Oztas, A.1    Pala, M.2    Ozbay, E.3    Kanca, E.4    Caglar, N.5    Asghar Bhatti, M.6
  • 10
    • 0037799569 scopus 로고    scopus 로고
    • The use of GA-ANNs in the modelling of compressive strength of cement mortar
    • Akkurt S, Ozdemir S, Tayfur G, Akyol B (2003) The use of GA-ANNs in the modelling of compressive strength of cement mortar. Cem Concr Res 33(7):973–979
    • (2003) Cem Concr Res , vol.33 , Issue.7 , pp. 973-979
    • Akkurt, S.1    Ozdemir, S.2    Tayfur, G.3    Akyol, B.4
  • 11
    • 0038426410 scopus 로고    scopus 로고
    • Artificial neural networks in prediction of mechanical behavior of concrete at high temperature
    • Mukherjee A, Biswas SN (1997) Artificial neural networks in prediction of mechanical behavior of concrete at high temperature. Nucl Eng Des 178(1):1–11
    • (1997) Nucl Eng Des , vol.178 , Issue.1 , pp. 1-11
    • Mukherjee, A.1    Biswas, S.N.2
  • 12
    • 80255137571 scopus 로고    scopus 로고
    • Experimental investigations and ANFIS prediction of water absorption of geopolymers produced by waste ashes
    • Nazari A, Riahi S (2012) Experimental investigations and ANFIS prediction of water absorption of geopolymers produced by waste ashes. J Non Cryst Solids 358(1):40–46
    • (2012) J Non Cryst Solids , vol.358 , Issue.1 , pp. 40-46
    • Nazari, A.1    Riahi, S.2
  • 13
    • 84858076167 scopus 로고    scopus 로고
    • Prediction total specific pore volume of geopolymers produced from waste ashes by ANFIS
    • Nazari A, Khalaj G, Riahi S, Bohlooli H, Kaykha MM (2012) Prediction total specific pore volume of geopolymers produced from waste ashes by ANFIS. Ceram Int 38:3111–3120
    • (2012) Ceram Int , vol.38 , pp. 3111-3120
    • Nazari, A.1    Khalaj, G.2    Riahi, S.3    Bohlooli, H.4    Kaykha, M.M.5
  • 14
    • 84858157961 scopus 로고    scopus 로고
    • Experimental investigations and fuzzy logic modeling of compressive strength of geopolymers with seeded fly ash and rice husk bark ash
    • Bohlooli H, Nazari A, Khalaj G, Kaykha MM, Riahi S (2012) Experimental investigations and fuzzy logic modeling of compressive strength of geopolymers with seeded fly ash and rice husk bark ash. Compos B 43:1293–1301
    • (2012) Compos B , vol.43 , pp. 1293-1301
    • Bohlooli, H.1    Nazari, A.2    Khalaj, G.3    Kaykha, M.M.4    Riahi, S.5
  • 17
    • 84861346447 scopus 로고    scopus 로고
    • The effects of nanoparticles on early age compressive strength of ash-based geopolymers
    • Riahi S, Nazari A (2012) The effects of nanoparticles on early age compressive strength of ash-based geopolymers. Ceram Int 38:4467–4476
    • (2012) Ceram Int , vol.38 , pp. 4467-4476
    • Riahi, S.1    Nazari, A.2
  • 18
    • 84856593904 scopus 로고    scopus 로고
    • Compressive strength of ash-based geopolymers at early ages designed by Taguchi method
    • Riahi S, Nazari A, Zaarei D, Khalaj G, Bohlooli H, Kaykha MM (2012) Compressive strength of ash-based geopolymers at early ages designed by Taguchi method. Mater Des 37:443–449
    • (2012) Mater Des , vol.37 , pp. 443-449
    • Riahi, S.1    Nazari, A.2    Zaarei, D.3    Khalaj, G.4    Bohlooli, H.5    Kaykha, M.M.6
  • 19
    • 45049086097 scopus 로고    scopus 로고
    • Predicting the strength development of cements produced with different pozzolans by neural network and fuzzy logic
    • Topcu IB, Karakurt C, Sarıdemir M (2008) Predicting the strength development of cements produced with different pozzolans by neural network and fuzzy logic. Mater Des 29:1986–1991
    • (2008) Mater Des , vol.29 , pp. 1986-1991
    • Topcu, I.B.1    Karakurt, C.2    Sarıdemir, M.3
  • 20
    • 2142827946 scopus 로고    scopus 로고
    • Prediction of fracture parameters of concrete by artificial neural networks
    • Ince R (2004) Prediction of fracture parameters of concrete by artificial neural networks. Eng Fract Mech 71(15):2143–2159
    • (2004) Eng Fract Mech , vol.71 , Issue.15 , pp. 2143-2159
    • Ince, R.1
  • 21
    • 51249194645 scopus 로고
    • A logical calculus of the ideas immanent in neural nets
    • McCulloch WS, Pitts W (1943) A logical calculus of the ideas immanent in neural nets. Bull Math Biophys 5:115–137
    • (1943) Bull Math Biophys , vol.5 , pp. 115-137
    • McCulloch, W.S.1    Pitts, W.2
  • 22
    • 57749180879 scopus 로고    scopus 로고
    • Prediction of long-term effects of GGBFS on compressive strength of concrete by artificial neural networks and fuzzy logic
    • Sarıdemir M, Topcu IB, Ozcan F, Severcan MH (2009) Prediction of long-term effects of GGBFS on compressive strength of concrete by artificial neural networks and fuzzy logic. Constr Build Mater 23:1279–1286
    • (2009) Constr Build Mater , vol.23 , pp. 1279-1286
    • Sarıdemir, M.1    Topcu, I.B.2    Ozcan, F.3    Severcan, M.H.4
  • 23
    • 0037066643 scopus 로고    scopus 로고
    • Detection of cracks using neural networks and computational mechanics
    • Liu SW, Huang JH, Sung JC, Lee CC (2002) Detection of cracks using neural networks and computational mechanics. Comput Methods Appl Mech Eng 191(25–26):2831–2845
    • (2002) Comput Methods Appl Mech Eng , vol.191 , Issue.25-26 , pp. 2831-2845
    • Liu, S.W.1    Huang, J.H.2    Sung, J.C.3    Lee, C.C.4
  • 24
    • 3242891065 scopus 로고    scopus 로고
    • A neural network approach for early cost estimation of structural systems of building
    • Gunaydin HM, Dogan SZ (2004) A neural network approach for early cost estimation of structural systems of building. Int J Proj Manag 22(7):595–602
    • (2004) Int J Proj Manag , vol.22 , Issue.7 , pp. 595-602
    • Gunaydin, H.M.1    Dogan, S.Z.2
  • 25
    • 33845451253 scopus 로고    scopus 로고
    • The effect of alkali and Si/Al ratio on the development of mechanical properties of metakaolin-based geopolymers
    • Duxson P, Mallicoat SW, Lukey GC, Kriven WM, van Deventer JSJ (2007) The effect of alkali and Si/Al ratio on the development of mechanical properties of metakaolin-based geopolymers. Colloids Surf A 292(1):8–20
    • (2007) Colloids Surf A , vol.292 , Issue.1 , pp. 8-20
    • Duxson, P.1    Mallicoat, S.W.2    Lukey, G.C.3    Kriven, W.M.4    van Deventer, J.S.J.5
  • 27
    • 33746306540 scopus 로고    scopus 로고
    • Prediction of web crippling strength of cold-formed steel sheetings using neural networks
    • Guzelbey IH, Cevik A, Erklig A (2006) Prediction of web crippling strength of cold-formed steel sheetings using neural networks. J Constr Steel Res 62:962–973
    • (2006) J Constr Steel Res , vol.62 , pp. 962-973
    • Guzelbey, I.H.1    Cevik, A.2    Erklig, A.3
  • 28
    • 37249005831 scopus 로고    scopus 로고
    • Prediction of compressive strength of concrete containing fly ash using artificial neural network and fuzzy logic
    • Topcu IB, Sarıdemir M (2008) Prediction of compressive strength of concrete containing fly ash using artificial neural network and fuzzy logic. Comput Mater Sci 41(3):305–311
    • (2008) Comput Mater Sci , vol.41 , Issue.3 , pp. 305-311
    • Topcu, I.B.1    Sarıdemir, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.