Editor/Reviewer loginFrequency : 12 issues per year
Subject : Computer Applications and Technology
ISSN : 2319–8656 (Online)
IJCATR Volume 6 Issue 7
Software Effort Estimation Using Adaptive Fuzzy-Neural Approach
Riyadh A.K. Mehdi
10.7753/IJCATR0607.1011
keywords : Software effort estimation; fuzzy inference; datasets; neural networks; and fuzzy-neural systems.
Software effort estimation is an important step in software development. It predicts the amount of effort and development time required to build a software system. It is one of the most important tasks and an accurate estimate is vital to the successful completion of the project. Building software effort estimation requires developing sound computational models. This paper investigates the use of fuzzy-neural systems in estimating software effort. A comparison is made with a radial basis neural network. Results obtained based on the China dataset indicates that a hybrid model that combine fuzzy inferencing with neural networks ability to learn from examples provided more accurate results than using neural networks alone.
@artical{r672017ijcatr06071012,
Title = "Software Effort Estimation Using Adaptive Fuzzy-Neural Approach",
Journal ="International Journal of Computer Applications Technology and Research(IJCATR)",
Volume = "6",
Issue ="7",
Pages ="329 - 332",
Year = "2017",
Authors ="Riyadh A.K. Mehdi"}
An adaptive neuro fuzzy model (ANFIS) was used
A Sugeno fuzzy model is used
Results were compared with those obtained using a radial basis function neural network
The ANFIS model has far less deviation that those of the RBFN model.