We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 2024

Submit your paper
Know more
The week's pick
Responsive image
An Efficient Restoration Method for the Faint Dot Matrix Images

Ao Zhu Peng Cao
Random Articles
Reseach Article

Design and Implementation of Neuro Fuzzy model for Software Development Time Estimation

by Shina Dhingra, Palvinder Singh Mann
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 86 - Number 5
Year of Publication: 2014
Authors: Shina Dhingra, Palvinder Singh Mann
10.5120/14979-3179

Shina Dhingra, Palvinder Singh Mann . Design and Implementation of Neuro Fuzzy model for Software Development Time Estimation. International Journal of Computer Applications. 86, 5 ( January 2014), 7-12. DOI=10.5120/14979-3179

@article{ 10.5120/14979-3179,
author = { Shina Dhingra, Palvinder Singh Mann },
title = { Design and Implementation of Neuro Fuzzy model for Software Development Time Estimation },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 86 },
number = { 5 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 7-12 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume86/number5/14979-3179/ },
doi = { 10.5120/14979-3179 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:03:24.195425+05:30
%A Shina Dhingra
%A Palvinder Singh Mann
%T Design and Implementation of Neuro Fuzzy model for Software Development Time Estimation
%J International Journal of Computer Applications
%@ 0975-8887
%V 86
%N 5
%P 7-12
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

To develop a project successfully, it is important for any organization that the project should be completed within budget, on time and the project should have requisite quality. This paper presents an Adaptive Neuro-Fuzzy Approach for Software Development Time Estimation. This proposed technique is aimed at building and evaluating a Neuro - fuzzy model using three (3) membership functions (MFs) for software project development time. The forty one modules were used as a data set. Our proposed approach for Neuro fuzzy using 3 membership functions i. e. Gaussian MF (GMF), Triangular MF (Tri MF) and Trapezoidal MF (Trap MF) is compared with neural network models and the results show that values of various relative error parameters for Neuro-fuzzy is lower than the values of parameters applying neural network.

References
  1. S. Basha and P. Dhavachelvan, "Analysis of Empirical Software Effort Estimation Models" in International Journal of Computer Science and Information Security (IJCSIS), Vol. 7, 2010.
  2. B. Hughes and M. Cotterell, "Software Project Management", Tata McGraw-Hill, 2006.
  3. T. Gruschke, "Empirical Studies of Software Cost Estimation: Training of EffortEstimation Uncertainty Assessment Skills", 11th IEEE International Software Metrics Symposium, IEEE, 2005.
  4. B. W. Boehm, "Software Engineering Economics", Prentice-Hall, Englewood Cliffs, NJ, USA, 1981.
  5. C. C. Kung and J. Y. Su, "Affine Takagi-Sugeno fuzzy modeling algorithm byFuzzy c-regression models clustering with a novel cluster validity criterion", IETControl Theory Appl. , pp. 1255 – 1265, 2007.
  6. V. Khatibi, Dayang and N. A. Jawawi, " Software Cost Estimation Methods: A Review", Journal of Emerging Trends in Computing and Information Sciences, CIS Journal, Vol. 2, no. 1, ISSN 2079-8407, 2011.
  7. N. Sharma1, A. Bajpai and M. R. Litoriya, "A Comparison of Software Cost Estimation Methods: A Survey", The International Journal of Computer Science and Applications (TIJCSA), Vol. 1, no. 3, ISSN – 2278 – 1080, May 2012.
  8. J. Keung, "Software Development Cost Estimation Using Analogy: A Review", Australian Software Engineering conference, IEEE, 2009.
  9. T. R. Benala, S. Dehuri and R. Mall, "Computational Intelligence in Software Cost Estimation: An Emerging Paradigm", ACM SIGSOFT Software Engineering Notes Page, Vol. 37, no. 3, 2012.
  10. J. S. Pahariya, V. Ravi and M. Carr, "Software Cost Estimation using Computational Intelligence Techniques", World Congress on Nature & Biologically Inspired Computing (NaBIC 2009) IEEE, 2009.
  11. Mrinal Kanti Ghose, Roheet Bhatnagar and Vandana Bhattacharjee, "Comparing Some Neural gNetwork Models for Software Development Effort Prediction", IEEE conference , 2011.
  12. Venus Marza, Amin Seyyedi and Luiz Fernando Capretz, "Estimating Development Time of Software Projects Using a Neuro Fuzzy Approach", World Academy of Science, Engineering and Technology, 2008.
  13. Vachik S. Dave, Kamlesh Dutta, "Neural Network based Software Effort Estimation & Evaluation criterion MMRE", International Conference on Computer & Communication Technology (ICCCT), pp. 347-351, 2011.
  14. Cuauhtémoc López Martín, "Software Development Effort Estimation Using Fuzzy Logic: A Case Study", Proceedings of the Sixth Mexican International Conference on Computer Science (ENC'05), IEEE 2005.
  15. Moataz A. Ahmed, Moshood Omolade Saliu and Jarallah AlGhamdi, "Adaptive fuzzy logic-based framework for software development effort prediction", Information and Software Technology, 2005.
  16. C. J. Burgess, M. Lefley, " Can genetic programming improve software effort estimation? A comparative evaluation", Information and Software Technology, pp. 863–873, 2001.
  17. Anish Mittal, Kamal Parkash and Harish Mittal "Software Cost Estimation Using Fuzzy Logic", ACM SIGSOFT Software Engineering Notes Page , Vol 35 no. 1, November 2010.
  18. Harsh Kumar Verma, Vishal Sharma, "Handling Imprecision in Inputs using Fuzzy Logicto Predict Effort in Software Development" , IEEE conference, 2010.
  19. G. D. Boetticher, "An assessment of metric contribution in the construction of a neural network-based effort estimator", Proceedings of Second International Workshop on Soft Computing Applied to Software Engineering, 2001.
  20. Xishi Huang et al. , "A Neuro-Fuzzy Model for Software Cost Estimation", Proceedings of the Third International Conference on Quality Software (QSIC'03), IEEE, 2003.
  21. A. R. Venkatachalam, "Software cost estimation using artificial neural networks", in: Proceedings of the International Joint Conference on Neural Networks, pp. 987–990, 1993.
  22. J. Ryder, "Fuzzy modeling of software effort prediction", Proceedings of IEEE Information Technology Conference, Syracuse, NY, 1998.
  23. Allidri et al. , "COCOMO Cost Model Using Fuzzy Logic", 7th International Conference On RFuzzy Theory & Technology Atlantic City, New Jersey, February27-March3, 2000.
  24. Heejum Park and Seung Baek, "An Empirical validation of a neural network model for software effort estimation", Expert System with Application,Elsevier, pp. 929-937, 2007.
  25. Dinesh C. S. Bisht and Ashok Jangid, "Discharge Modelling using Adaptive Neuro-Fuzzy Inference System", International Journal of Advanced Science and Technology,Vol. 31,pp. 99-114, June 2011.
  26. Rama Sree P,Prasad Reddy and Sudha K. R. , "Hybrid Neuro-Fuzzy Systems for Software Development Effort Estimation", International Journal on Computer Science and Engineering, Vol. 4, pp. 1924-1932, Dec 2012.
  27. Urvashi Rahul Saxena, S. P. Singh, "Software Effort Estimation Using Neuro-Fuzzy Approach", CSI 6th International Conference, pp. 1-6, Sept. 2012.
  28. Mrinal Kanti Ghose, Roheet Bhatnagar and Vandana Bhattacharjee, "Software Development Effort Estimatiom- Neural Network Vs. Regression Modelling Approach", International Journal of Engineerig and Technology, Vol. 2(7), pp. 2950-2956, 2010.
  29. Divya Kashyap, Ashish Tripathi,Prof. A. K. Mishra, "Software Development Effort and Cost Estimation: Neuro-Fuzzy Model", IOSR Journal of Computer Engineering (IOSRJCE), Vol. 2, pp. 12-14, July-Aug. 2012.
  30. M. Chemuturi, "Software Estimation Best Practices, Tools & Techniques: A Complete Guide for Software Project Estimator" , 2009.
  31. Vachik S. Dave, Kamlesh Dutta, "Comparison of Regression model, Feed-forward Neural Network and Radial Basis Neural Network for Software Development Effort Estimation", ACM SIGSOFT Software Engineering, Vol. 36, No. 5, Sept. 2011.
  32. J. Jantzen, "Neuro- Fuzzy modeling", Reort no 98-H-874, 1998.
  33. M. T. Su, T. C. Ling, "Enhanced Software Development Effort and Cost Estimation Using Fuzzy Logic Model",Malyasian Journal of Computer Science, Vol. 20,No. 2,2007,pp. 199-207.
  34. A. Heiat, "Comparison of artificial neural network and regression models for estimating software development effort", Information and Software Technology, Vol. 44,Issue 15,2002,pp. 911-922.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive Neuro Fuzzy Inference System (ANFIS) Neural Network Fuzzy Logic Prediction MRE MMRE BRE Development Time (DT) Membership Function (MF).

Powered by PhDFocusTM