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针对产业集群创新能力评价的一些复杂方法,以文献中的基于BP神经网络的产业集群创新能力评价模型作为比较对象,提出了两种评价模型:组合评价模型和主成分指数模型.前者将变异系数法和Topsis法组合使用,用以评价产业集群创业能力;后者则是对所有参评样本的评价指标进行主成分分析,以主成分的方差贡献率为权重,构建主成分综合指数,从而形成产业集群创新能力的综合评价指数模型.对这两个模型用来自比较对象模型的同一数据进行了验证,三个模型都得出了非常相近的结果,而这两种模型更具可操作性且易于解释,这两者相比,主成分分析的方法则更为简单易行.
Aiming at some complicated methods of industrial cluster’s innovation ability evaluation, two evaluation models are proposed based on the evaluation model of industrial cluster’s innovative ability based on BP neural network in the literature: the combination evaluation model and the principal component index model, the former combines the coefficient of variation Method and Topsis method are used in combination to evaluate the entrepreneurial ability of industrial clusters; the latter is to carry out principal component analysis on the evaluation indexes of all the participating samples, construct the composite index of principal components by taking the variance contribution rate of the principal components as the weight, and form the industry A comprehensive evaluation index model for cluster innovation capacity.The two models were validated using the same data from the comparison object model and all three models yielded very similar results and the two models were more maneuverable and easier to Explain that the principal component analysis is much simpler than the two.