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考虑复杂社会技术系统的特点,运用自适应神经模糊推理模型对提高公益科研机构的组织效率进行了实例研究。建立了针对公益科研机构员工激励决策的自适应模糊推理完整模型,利用调研数据及其处理结果验证了模型的有效性。该模型融合了神经网络的学习机制和模糊系统的语言推理能力,弥补了神经网络和模糊逻辑系统各自的不足。研究结果表明,自适应神经模糊推理模型适用于复杂社会技术系统,在解决管理领域的预测、评估和决策问题中有广阔的应用前景。
Considering the characteristics of complex social technology system, this paper uses an adaptive neuro-fuzzy inference model to study the organizational efficiency of public scientific research institutions. A complete model of adaptive fuzzy inference for motivation decision-making of public scientific research institutes was established. The validity of the model was verified by using the survey data and the processing results. The model combines the learning mechanism of neural network and the linguistic reasoning ability of fuzzy system to make up for the deficiencies of neural network and fuzzy logic system. The results show that the adaptive neuro-fuzzy inference model is suitable for complex social technology systems and has broad application prospects in the field of management, forecasting, assessment and decision-making.