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An improved particle swarm optimization algorithm for enterprise informatization maturity evaluation

机译:企业信息化成熟度评估的改进粒子群算法

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In order to overcome the problems of premature convergence and high dimension complex function optimization in conventional particle swarm optimization algorithm, the paper presents an improved particle swarm optimization algorithm and applies it to evaluate enterprise informatization maturity. First, the working principle and current problems of original particle swarm optimization algorithm are analyzed; Then, the methods of late random inertia weight and non-linear dynamic inertia weight are advanced to seek for proper inertia weight; Third, the calculation flows of the presented algorithm are redesigned to reduce iteration times; Finally, the evaluation indicators of enterprise informatization maturity are analyzed and the improved algorithm is realized. The simulation results illustrates that the algorithm has better self-adaptability and can simplify model structure, increase algorithm efficiency, and improve evaluation accuracy when used for evaluating enterprise informatization maturity.
机译:为了克服传统粒子群算法中的过早收敛和高维复杂函数优化的问题,提出了一种改进的粒子群算法,并将其应用于企业信息化成熟度的评估。首先,分析了原始粒子群算法的工作原理和当前存在的问题;然后,提出了后期随机惯性权重和非线性动态惯性权重的方法,以寻求合适的惯性权重。第三,重新设计了该算法的计算流程,以减少迭代时间。最后,分析了企业信息化成熟度的评价指标,并实现了改进算法。仿真结果表明,该算法用于企业信息化成熟度评估时,具有较好的自适应性,可以简化模型结构,提高算法效率,提高评估精度。

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