基于神经网络的高新技术企业吸收能力评估

Evaluation of High-tech Enterprise's Absorptive Capability Based on Neural Network

知识吸收能力是影响高新技术企业创新能力的重要因素,同时是一个非常复杂的系统。鉴于传统评价方法的局限,研究了人工神经网络技术在高新技术企业知识吸收能力评估管理中的优化应用。在总结分析企业吸收能力的影响因素基础上,建立了吸收能力评价的指标体系。通过引入人工神经网络,提出了一个基于BP神经网络的吸收能力的仿真评估模型,综合考虑了专家意见和要素间的非线性等特点。模型的仿真结果和目标分析结果具有较高的逼近度,从而证明了人工神经网络在高新技术企业知识吸收能力评估中的可行性及其优越性。

Absorptive capability is a very important factor affecting high - tech enterprise＇s innovative ability, which is a complicated system. Owing to the limitation of traditional evaluation methods, the paper investigated how to use neural network to evaluate high - tech enterprise＇s absorptive capability. It analyzed the factors affecting high - tech enterprise＇s absorptive capability, and then constructed an index system to evaluate it. Taking advantage of BP neural network, an evaluation model of absorptive capability was designed which integrated the expertise with non - linear characteristic of factors. And there is a high approximation degree between the results of simulation and analysis which proved the feasibility and advantages of BP neural network used in evaluating absorptive capability through an example.