优化软件项目时间和进度的神经网络估计模型

Mohamed Hamada, Abdelrahman Abdallah, M. Kasem, Mohamed Abokhalil
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引用次数: 10

摘要

软件项目的失败率很高,对于重要的IT项目来说,失败率似乎徘徊在60%左右。估算时间和项目进度是一项至关重要的任务,对项目的成果影响很大。人工智能现在可以为软件项目的大多数问题提供多种解决方案。本文旨在开发一个神经网络估计模型来处理软件项目的时间问题。该模型可以预测项目时间的估计值,从而优化调度过程,经测试数据集测试,该模型取得了较高的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Neural Network Estimation Model to Optimize Timing and Schedule of Software Projects
Software projects have a probability of high failure rates that appear to linger around 60% for significant IT projects. Estimating time and project schedule are crucial tasks and extremely influence the project outcomes. Artificial Intelligence now can provide multiple solutions for most problems of software projects. This article aims to develop a Neural Network estimation model to manipulate the problem of timing for software projects. The model can predict the estimation value of project time which optimizes the scheduling process, the developed model achieved high accuracy after testing through the test datasets.
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