基于 R-RNN的孵化器运营水平评价及应用

针对科技企业孵化器运营水平难以科学定量评估的问题,提出了基于粗糙集和 RBF神经网络的 R RNN孵化器运营水平评价模型.基于孵化器运营工作原理的归纳分析,提出多层次孵化器运营水平评价指标体系.根据指标重要程度采用粗糙集理论对评价指标进行预处理,去除冗余指标项,选取重要控制指标并减少网络输入维度,进而采用 RBF神经网络对科技企业运营水平进行综合评价.最后通过具体的应用实例验证了该评价模型的有效性与可行性

Enterprise Incubator Operation Index Evaluation and Application based on R-RNN

Aiming to solve the scientific evaluation problem of science and technology enterprises incubators, R-RNN incubator evaluation model based on rough sets and RBF neural network was proposed. Based on the analysis of incubator operation principle, multi-level incubator operation level evaluation index system was presented. According to the importance levels of indexes, rough sets theory was employed to remove redundant indexes. Important control indexes were selected and network input dimensions were reduced, and then RBF neural network technology was used to comprehensively evaluate enterprise operation. Finally, through the concrete examples, effectiveness and feasibility are verified.