Software effort estimation using FAHP and weighted kernel LSSVM machine

  • Sumeet Kaur Sehra
  • Yadwinder Singh Brar
  • Navdeep Kaur
  • Sukhjit Singh Sehra
Methodologies and Application


In the life cycle of software product development, the software effort estimation (SEE) has always been a critical activity. The researchers have proposed numerous estimation methods since the inception of software engineering as a research area. The diversity of estimation approaches is very high and increasing, but it has been interpreted that no single technique performs consistently for each project and environment. Multi-criteria decision-making (MCDM) approach generates more credible estimates, which is subjected to expert’s experience. In this paper, a hybrid model has been developed to combine MCDM (for handling uncertainty) and machine learning algorithm (for handling imprecision) approach to predict the effort more accurately. Fuzzy analytic hierarchy process (FAHP) has been used effectively for feature ranking. Ranks generated from FAHP have been integrated into weighted kernel least square support vector machine for effort estimation. The model developed has been empirically validated on data repositories available for SEE. The combination of weights generated by FAHP and the radial basis function (RBF) kernel has resulted in more accurate effort estimates in comparison with bee colony optimisation and basic RBF kernel-based model.


Software effort estimation Fuzzy analytic hierarchy process Least square support vector machine 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Sumeet Kaur Sehra
    • 1
    • 2
  • Yadwinder Singh Brar
    • 1
  • Navdeep Kaur
    • 3
  • Sukhjit Singh Sehra
    • 4
  1. 1.I.K.G. Punjab Technical UniversityJalandharIndia
  2. 2.Guru Nanak Dev Engineering CollegeLudhianaIndia
  3. 3.Sri Guru Granth Sahib World UniversityFatehgarh SahibIndia
  4. 4.Elocity Technology Inc.TorontoCanada

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