摘要
从石油企业自身特点和实际出发,通过问卷调查和主成分因素分析法,构建了6个维度18个指标的石油企业核心竞争力评价指标体系。基于评价指标,设计了BP神经网络模型,选择了6家样本企业、2家测试企业进行了应用试验,对5家综合实力较强的石油企业进行了应用分析。研究表明:本评价模型与传统的线性评价模型相比,具有更高的动态性和自学习性,评价结果误差小,精度高,能充分反映石油企业核心竞争力的真实状况,为石油企业核心竞争力的打造提供了基准,同时对石油企业核心竞争力进行定量评价开辟了另一条途径。
Through questionnaire and principal component analysis,the authors establish a system evaluating core competitiveness of oil enterprises which consists of 6 dimensions and 18 indices.And a BP artificial neural network(ANN) model is designed based on this evaluation system.6 sample enterprises and 2 others as test subjects are chosen for the application test and then analysis is made about 5 oil enterprises with greater comprehensive competitiveness.The study suggests that compared with conventional linear evaluation model,the BP ANN model is more dynamic and learns better.Therefore,the evaluation is more accurate and better reflects the real picture of oil enterprises' core competitiveness.The authors hope that this BP ANN model will provide a new method of core competitiveness evaluation for oil enterprises.
出处
《西南石油大学学报（社会科学版）》
2010年第6期22-26,共5页
Journal of Southwest Petroleum University(Social Sciences Edition)
基金
2009年四川循环经济中心资助项目(XHJJ-0908)
2009四川省南充市科技局项目"南充市天然气利用规划项目融资方案研究"(市050)
关键词
石油企业
核心竞争力
BP神经网络
评价指标体系
网络训练
oil enterprises
core competitiveness
BP artificial neural network
evaluation index system
network training
