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Student Number 85423004
Author Tien-Chang Wu(吳典璋)
Author's Email Address No Public.
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Department Information Management
Year 1997
Semester 2
Degree Master
Type of Document Master's Thesis
Language zh-TW.Big5 Chinese
Title The study on Software Development Cost Estimation using Neural Network
Date of Defense
Page Count 78
Keyword
  • neural network
  • software cost estimation
  • software cost estimation model
  • Abstract Estimating software cost is a very important factor to a successful software project. It's very difficult to estimate software development cost. If manager's estimate is too low, then the software development team will be lacking in resources during a later phase of the software life cycle. Besides, the software quality will be affected. If a manager's estimate is too high, too many resources will be committed to the project. If the company is engaged in contract software development, then too high an estimate may fail to secure a contract. Until now, Most software companies don't use a reliable, quantitative software cost estimation model.   Using neural network to solve the prediction or classification problems is a fair solution. Backpropagation network is used to solve this kind of problems. In this paper, we use backpropagation network to estimate software development cost, and construct two kinds of software cost estimation models based on the 63 projects from COCOMO database.
       The contribution of this study are :
    1.Construct two kinds of software cost estimation models using neural network. Model 1:software cost prediction model.Model 2: software cost classification model.
    2.Describe the method in detail to construct the software cost estimation models using neural network. It provides other researchers reference this paper to apply.
       There are a lot of factors affecting the software cost, these factors and the software cost are nonlinear relationship. This study try to construct the software cost estimation models using neural network to solve this kind of problem.
    Table of Content 第一章 緒論 1
    第一節 研究背景 1
    第二節 研究動機 2
    第三節 研究目的 3
    第四節 研究架構及步驟 3
    第二章 文獻探討 6
    第一節 軟體成本導出因子 6
    第二節 軟體成本衡量指標 9
    第三節 各種成本預估模式 10
    第四節 COCOMO模式 14
    第五節 機器學習成本估算模式 20
    第六節 類神經網路模式 21
    第七節 倒傳遞式類神經網路(BACK-PROPAGATION NETWORK) 26
    第八節 工具介紹 33
    第三章 模式一:預測模式之建立 35
    第一節 系統分析 36
    第二節 系統設計 43
    第三節 模式的訓練 45
    第四節 測試結果 50
    第五節 與其它模式比較 52
    第四章 模式二:分類模式之建立 58
    第一節 分類處理 58
    第二節 模式建立 61
    第三節 修正後模式的建立 64
    第四節 測試結果 69
    第五章 結論與建議 70
    第一節 研究結果 70
    第二節 研究貢獻 71
    第三節 研究困難與應用限制 72
    第四節 後續研究建議 74
    Reference 參考文獻
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    Advisor
  • Yih-Chearng Shiue(薛義誠)
  • Files No Any Full Text File.
    Date of Submission

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