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基于粒子群优化算法的中小企业竞争情报搜集系统模型
引用本文:王洪林,刘伟.基于粒子群优化算法的中小企业竞争情报搜集系统模型[J].科技管理研究,2021,41(21):196-203.
作者姓名:王洪林  刘伟
作者单位:山东科技大学计算机科学与工程学院,山东青岛 266590
基金项目:山东省自然科学基金面上项目“基于逻辑Petri网的电子商务多主体协同决策优化研究”(ZR2020MF033);国家自然科学基金项目“扩展逻辑Petri网理论及其在跨组织业务过程协同中的应用研究”(61472228)
摘    要:以粒子群优化算法为基本理论,结合我国中小企业目前对竞争情报的迫切需求和开展竞争情报工作的困难,利用跨学科分析法和仿真实验检验法,构建一个适用于中小企业的竞争情报"粒子搜索模型".该模型充分调用各粒子"经验"寻找全局最优解,用以为我国中小企业构建低成本、高收益、易组织管理的竞争情报搜集系统模型提供参考.

关 键 词:粒子群优化算法  中小企业  竞争情报搜集系统  粒子搜索模型
收稿时间:2021/6/8 0:00:00
修稿时间:2021/9/9 0:00:00

Competitive Intelligence Collection System Model for Small and Medium Enterprises Based on Particle Swarm Optimization Algorithm
Wang Honglin,Liu Wei.Competitive Intelligence Collection System Model for Small and Medium Enterprises Based on Particle Swarm Optimization Algorithm[J].Science and Technology Management Research,2021,41(21):196-203.
Authors:Wang Honglin  Liu Wei
Abstract:Collecting competitive intelligence is an important part for the competitive intelligence work of enterprise, and it is a key factor in the research of competitive intelligence collection process that intelligence personnel how to sort the value of massive information sources, and effectively search for high-value intelligence. This paper constructs a "particle search model" of competitive intelligence for small and medium enterprises(SMEs) by taking Particle Swarm Optimization Algorithm as the basic theory and using interdisciplinary analysis and simulation test method in view of the urgent demand for competitive intelligence and the difficulties in carrying out competitive intelligence work of SMEs in China. The model fully utilize the "experience" of each particle to find the global optimal solution, which can provide reference for SMEs in China to build a competitive intelligence collection system model with low cost, high income and easy organization and management.
Keywords:Particle Swarm Optimization(PSO)  small and medium enterprises  Competitive Intelligence Collection System  Particle search model
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