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An improved particle swarm optimization algorithm for enterprise informatization maturity evaluation

Author(s): Zhu Jianbin

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.

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