High-Performance Concrete Compressive Strength Prediction Based Weighted Support Vector Machines
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 1
Abstract
Concrete is the safest and sustainable construction material which is most widely used in the world as it provides superior fire resistance, gains strength over time and gives an extremely long service life. Unfortunately high performance concrete is undoubtedly one of the most innovativ e materials in construction. Its Designing involves the process of selecting suitable ingredients of concrete (water, cement, fine and aggregates and a number of additives like mineral and chemical admixture) and determining their relative amounts with the objective of producing a high performance concrete of the required, strength, durability, and workability as economically as possible. Their proportions have a high influence on the final strength of the product. These relations do not seem to follow a mathematical formula and yet their knowledge is crucial to optimize the quantities of raw materials used in the manufacture of high performance concrete. Therefore, it would be important to have a tool to numerically model such relationships, even before pro cessing. In this aspect the main purpose of this paper is to predict the compressive strength of the high performance concrete by using classification algorithms. For building these models, training and testing using the available experimental results for 1030 specimens produced with 8 different mixture proportions are used. The result from this study suggests that weighted Support Vector Machines (wSVM) based models perform remarkably well in predicting the compressive strength of the concrete mix.
Authors and Affiliations
Rguig Mustapha, EL Aroussi Mohamed
Keywords
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- EP ID EP389673
- DOI 10.9790/9622-0701016875.
- Views 199
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