Title page for etd-0613115-111710


[Back to Results | New Search]

URN etd-0613115-111710
Author Jin-ming Liang
Author's Email Address No Public.
Statistics This thesis had been viewed 5362 times. Download 1 times.
Department Information Management
Year 2014
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Using Hybrid Artificial Neural Network to Estimate Software Effort
Date of Defense 2015-07-21
Page Count 40
Keyword
  • Software Effort
  • Estimate
  • Clustering Theory
  • Fuzzy Set
  • Hybrid Artificial Neural Network
  • Abstract Abstract
    In this study, we propose a hybrid artificial neural network for software effort estimation , which developed by fuzzy set, clustering theory and least squared estimation algorithm. The new model can work efficiently and robustly, and also easily aggregated by different algorithms to obtain the finally output. To evaluate the performance of estimation of software effort, we will compare the proposed model with some traditional models (Halstead、Walston-Felix、Bailey-Basili及Doty). Most accuracy measure of fitting (MAE, MMRE, RMSE, pred25) are improved by novel model.
    Advisory Committee
  • William Chao - chair
  • Chia-Mei Chen - co-chair
  • Bing-Chiang Jeng - advisor
  • Files
  • etd-0613115-111710.pdf
  • Indicate in-campus at 0 year and off-campus access at 5 year.
    Date of Submission 2015-07-30

    [Back to Results | New Search]


    Browse | Search All Available ETDs

    If you have more questions or technical problems, please contact eThesys