FUZZY LOGIC MODEL FOR THE PREDICTION OF CEMENT COMPRESSIVE STRENGTH

A fuzzy logic prediction model for the 28-day compressive strength of cement mortar under standard curing conditions was created in this paper. Data collected from a cement plant were used in the model construction and testing. The input variables of alkali, Blaine, SO3, and C3S and the output variable of 28-day cement strength were fuzzified by the use of artificial neural networks (ANNs), and triangular membership functions were employed for the fuzzy subsets. The Mamdani fuzzy rules relating the input variables to the output variable were created by the ANN model and were laid out in the If-Then format. Product (prod) inference operator and the center of gravity (COG; centroid) defuzzification methods were employed. The prediction of 50 sets of the 28-day cement strength data by the developed fuzzy model was quite satisfactory. The average percentage error levels in the fuzzy model were successfully low (2.69%). The model was compared with the ANN model for its error levels and ease of application. The results presented in the paper indicated that through the application of fuzzy logic algorithm, a more user friendly and more explicit model than the ANNs could be produced within successfully low error margins.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00088846
• Corporate Authors:

  Elsevier

  The Boulevard, Langford Lane
  Kidlington, Oxford  United Kingdom  OX5 1GB
• Authors:
  • Akkurt, S
  • Tayfur, G
  • Can, S
• Publication Date: 2004-8

Language

• English

Media Info

• Features: Figures; References; Tables;
• Pagination: 5 p.
• Serial:
  • Cement and Concrete Research
  • Volume: 34
  • Issue Number: 8
  • Publisher: Elsevier
  • ISSN: 0008-8846
  • Serial URL: http://www.sciencedirect.com/science/journal/00088846

Subject/Index Terms

• TRT Terms: Alkali; Artificial aggregates; Cement; Compressive strength; Construction; Data collection; Fuzzy logic; Neural networks; Operations; Strength of materials; Testing
• Subject Areas: Administration and Management; Construction; Highways; Materials; I32: Concrete;

Filing Info

• Accession Number: 00983082
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 9 2004 12:00AM