Performance Comparison of SVM and ANN in Predicting Compressive Strength of Concrete

Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 5

Abstract

Abstract : Concrete compressive strength prediction is very important in structure and building design, particularly in specifying the quality and measuring performance of concrete as well as determination of its mix proportion. The conventional method of determining the strength of concrete is complicated and time consuming hence artificial neural network (ANN) is widely proposed in lieu of this method. However, ANN is an unstable predictor due to the presence of local minima in its optimization objective. Hence, in this paper we have studied the performance of support vector machine (SVM), a stable and robust learning algorithm, in concrete strength prediction and compare the result to that of ANN. It is found that SVM displayed a slightly better performance compared to ANN and is highly stable.

Authors and Affiliations

Kabiru O. Akande, Ssennoga Twaha , Taoreed O. Owolabi , Sunday O. Olatunji

Keywords

Related Articles

Human Identification via Face Recognition: Comparative Study

Biometric recognition becomes an attractive issue of processing, and have a vast amount of real applications.According to wide spread of Internet and the new aspect of Internet of things, millions of human characteristic...

 Analysis of Intrusion Detection Response System (IDRS) In Cyber Physical Systems (Cps) Using Regular Expression (Regexp)

 Abstract: In this research we aim to design and validate Intrusion Detection Response System (IDRS) for a cyber physical system (CPS) comprising for controlling and protecting physical infrastructures. The design p...

 Spam Detection using Natural Language Processing

 Abstract: Spam mails can be referred as unsolicited bulk email. These messages are used to advertise products and services for phishing purposes or to lead recipients to malicious sites with unethical intentions. A...

 Gender related differences in the use of the Internet by university academics

 Abstract: This paper reports in part some of the findings of a PhD study regarding visibility of gender issues in the use of the internet in university contexts. The study adopted a cross sectional descriptive surv...

 A Comparison Based Study on Biometrics for Human  Recognition

 A biometric system provides automatic recognition of an individual based on a unique feature or characteristic possessed by the individual. These biometric characteristic may physiological or behavioral.  Un...

Download PDF file
  • EP ID EP137049
  • DOI 10.9790/0661-16518894
  • Views 111
  • Downloads 0

How To Cite

Kabiru O. Akande, Ssennoga Twaha, Taoreed O. Owolabi, Sunday O. Olatunji (2014).  Performance Comparison of SVM and ANN in Predicting Compressive Strength of Concrete. IOSR Journals (IOSR Journal of Computer Engineering), 16(5), 88-94. https://europub.co.uk/articles/-A-137049