IJIMT 2014 Vol.5(5): 374-377 ISSN: 2010-0248
DOI: 10.7763/IJIMT.2014.V5.543

Software Effort Estimation Using Multilayer Perceptron and Adaptive Neuro Fuzzy Inference System

Berna Seref and Necaattin Barisci
Abstract— Accurate software effort estimation has a big importance for software companies for the reason that management of the project, control of the project, financial matters and timely deliveries are achieved with effort estimation. Thus, effort estimation plays vital role for software companies. In this study, software effort estimation is predicted by using Multilayer Perceptron and Adaptive Neuro Fuzzy Inference System. As a dataset, NASA 93 with 93 projects and Desharnais with 77 projects are used. The results show that Mean Magnitude Relative Error of Adaptive Neuro Fuzzy Inference System is lower than Multilayer Perceptron. In addition, it is seen that PRED(0.25) value of Adaptive Neuro Fuzzy Inference System is higher than Multilayer Perceptron. Thus, performance of Adaptive Neuro Fuzzy Inference System is better when compared to performance of Multilayer Perceptron.

Index Terms— Software effort estimation, multilayer perceptron, adaptive neuro fuzzy inference system.

B. Seref is with Faculty of Engineering, Department of Computer Engineering, Dumlupinar University, Kutahya, 43100, Turkey (e-mail: berna.seref@dpu.edu.tr).
N. Barisci is with the Faculty of Technology, Department of Computer Engineering, Gazi University, Ankara, 06500, Turkey (e-mail: nbarisci@gazi.edu.tr).

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Cite: Berna Seref and Necaattin Barisci, " Software Effort Estimation Using Multilayer Perceptron and Adaptive Neuro Fuzzy Inference System," International Journal of Innovation, Management and Technology vol. 5, no. 5, pp. 374-377, 2014.

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