Prediction of cement strength using soft computing techniques

Baykasoglu A., Dereli T., Tanis S.

CEMENT AND CONCRETE RESEARCH, cilt.34, sa.11, ss.2083-2090, 2004 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 34 Sayı: 11
  • Basım Tarihi: 2004
  • Doi Numarası: 10.1016/j.cemconres.2004.03.028
  • Dergi Adı: CEMENT AND CONCRETE RESEARCH
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.2083-2090
  • Anahtar Kelimeler: modelling, compressive strength, cement manufacture
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

In this paper, it is aimed to propose prediction approaches for the 28-day compressive strength of Portland composite cement (PCC) by using soft computing techniques. Gene expression programming (GEP) and neural networks (NNs) are the soft computing techniques that are used for the prediction of compressive cement strength (CCS). In addition to these methods, stepwise regression analysis is also used to have an idea about the predictive power of the soft computing techniques in comparison to classical statistical approach. The application of the genetic programming (GP) technique GEP to the cement strength prediction is shown for the first time in this paper. The results obtained from the computational tests have shown that GEP is a promising technique for the prediction of cement strength. (C) 2004 Elsevier Ltd. All rights reserved.