基于FNN的软件项目绩效评价模型研究

摘要

从分析软件项目绩效评价指标体系不完善、评价方法不规范和模型考虑因素过于单一入手,应用统计分析理论建立软件组织状态、软件项目自身特征的指标体系；以文献研究的方式,界定软件项目绩效的内涵；提出了一种新的网络拓扑结构设计方法,建立了基于模糊神经网络的软件项目绩效评价模型；引入改进粒子群学习算法,准确高效地解决了评价模型连接权系数的确定问题.实证研究表明,该模型能够有效地评价软件项目绩效和识别项目风险因素,对软件组织制定风险规避策略、改善项目绩效水平、提供了决策支持信息.%From the analysis of software project performance evaluation indicator system, owing to its incompleteness, excessive simple evaluation model, and informal approach, using the statistic a-nalysis theory, an indicator system about software organizations status and software projects characteristics is given. The connotation of software project performance is defined through literature research. Then, the author develops a software project performance evaluation model based on Fuzzy Neural Network using a new network topology structure, which precisely and efficiently resolves the problem of evaluation model' s connection right weights. The empirical research indicates that the model may effectively evaluate the software project performance and cognize project risk factors, provide risk avoiding measures, better project performance, and give decision-making support information.