Modeling of compressive strength and UPV of high-volume mineral-admixtured concrete using rule-based M5 rule and tree model M5P classifiers

AYAZ Y., KOCAMAZ A. F., KARAKOÇ M. B.

CONSTRUCTION AND BUILDING MATERIALS, cilt.94, ss.235-240, 2015 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 94
  • Basım Tarihi: 2015
  • Doi Numarası: 10.1016/j.conbuildmat.2015.06.029
  • Dergi Adı: CONSTRUCTION AND BUILDING MATERIALS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.235-240
  • Anahtar Kelimeler: Data mining, M5 rule, Tree model M5P, Concrete, Compressive strength, UPV, CONSTRUCTION, PREDICTION, REGRESSION, VELOCITY
  • İnönü Üniversitesi Adresli: Evet

Özet

Compressive strength and UPV parameters are the methods that are used to determine high-volume mineral admixture concrete quality. But experiments for all levels of these parameters are expensive, difficult and time consuming. For determination of output values, classifiers with model extraction features can be used. In this study, classifiers, with the rule-based M5 rule and tree model M5P in the area of data mining are used to predict the compressive strength and UPV of concrete mixtures after 3, 7, 28 and 120 days of curing. The M5 rule and tree model M5P are tested using the available test data of 40 different concrete mix-designs gathered from literature [1]. The input of the model is a variable data set corresponding to concrete mixture proportions. The findings of this study indicated that the M5 rule and tree model M5P models are sufficient tools for estimating the compressive strength and UPV of concrete. 97% and 87% success is obtained in predicting compressive strength and UPV results, respectively. (C) 2015 Elsevier Ltd. All rights reserved.