Abstract

This research will observe the use of Artificial Neural Networks (ANN) for estimating software cost. Constructive Cost Model (COCOMO) is the most famous estimating model for software cost, which will be used in this research. The model estimates software cost by calculating several variables which are created by expert with some equations. Furthermore, ANN helps to estimate COCOMO effort accurately. This research offers multilayer feed-forward neural network to adjust COCOMO effort estimation parameters. Also, an algorithm such as Back-propagation is applied to improve the architecture by comparing actual effort with estimated effort and updating the network. However, there are several types of neural network architecture. This research tries to compare several types of architecture by testing each architecture model to dataset. This paper concerns with two different architectures. The difference of this two architecture is basic architecture only uses effort multipliers as input layer while modified architecture divides input layer into two categories such as effort multipliers and scale factors. The result is the proposed model increases the accuracy and each model has different result.

Original languageEnglish
Title of host publicationProceeding - 2015 International Conference on Computer, Control, Informatics and Its Applications
Subtitle of host publicationEmerging Trends in the Era of Internet of Things, IC3INA 2015
EditorsArnida L. Latifah
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages68-73
Number of pages6
ISBN (Electronic)9781479987733
DOIs
Publication statusPublished - 8 Jan 2016
EventInternational Conference on Computer, Control, Informatics and Its Applications, IC3INA 2015 - Bandung, Indonesia
Duration: 5 Oct 20157 Oct 2015

Publication series

NameProceeding - 2015 International Conference on Computer, Control, Informatics and Its Applications: Emerging Trends in the Era of Internet of Things, IC3INA 2015

Conference

ConferenceInternational Conference on Computer, Control, Informatics and Its Applications, IC3INA 2015
Country/TerritoryIndonesia
CityBandung
Period5/10/157/10/15

Keywords

  • COCOMO
  • artificial neural network
  • back propagation
  • cost driver
  • effort estimation
  • feed forward
  • neural networks
  • software cost estimation

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