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中文摘要：
建立了基于粗糙集和BP神经网络的复合图书馆馆藏质量评价模型,首先运用粗糙集模型对评价指标体系中的指标进行约简,消除冗余,然后把约简后得到的评价指标输入到BP神经网络中进行智能训练,最后把待评价的检测样本输入到训练好的BP网络中,得到了馆藏质量实际输出值,实际输出与期望输出结果相吻合,从而证明了评价的可行性和有效性。
英文摘要：
The paper constructs a model for the evaluation of hybrid library collection quality based on rough set and BP neural network. Firstly, the paper reduces the indices of the evaluation system by the use of the rough set model, and eliminates the redundancy, then inputs the residual indices to BP neural network for intelligent training. Finally, the paper inputs the test samples to be evaluated to the trained BP network and gets the actual output values of the library collection quality. The actual output results are matched with the desired output results, thereby, proving the feasibility and effectiveness of the evaluation.
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