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Management Rules Optimization for Software Development Based on System Dynamics and Swarm Intelligence

机译:基于系统动态和群体智能的软件开发管理规则优化

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Software research and development has to take considerable costs and time. For traditional decision making, the experience of mangers is a crucial key to make accurate decisions. In contrast, modern entrepreneurs employ database and statistical model to determine efficiently favorable strategies. The main goal of this study is to build system equation models by limited but informational data and to transform observed mathematical results into pragmatic plans for decision makers. Here we apply the simulation of System Dynamics to build Abdel-Hamid's dynamics model and to create pseudo-outcomes requisite for iteration method of Particle Swarm Optimization (PSO), and then to search the optimization solution by PSO algorithm. The results seem to indicate that PSO algorithm is competitive with other evolutionary algorithms, and can be successfully applied to more data mining domains.
机译:软件研发必须采取相当大的成本和时间。对于传统决策,人工人员的经验是做出准确决策的重要关键。相比之下,现代企业家使用数据库和统计模型来确定有效的有利策略。本研究的主要目标是通过有限但信息数据构建系统方程模型,并将观察到的数学结果转化为决策者的务实计划。在这里,我们应用系统动态的模拟来构建Abdel-Hamid的动态模型,并为粒子群优化(PSO)的迭代方法创建伪结果的必要条件,然后通过PSO算法搜索优化解决方案。结果似乎表明PSO算法与其他进化算法竞争,并且可以成功应用于更多数据挖掘域。

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