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Comparative Analysis of Risk Assessment for Technical Standards Alliance Based on BP Neural Network and Fuzzy AHP Methods

机译:基于BP神经网络的技术标准联盟风险评估对比分析及模糊AHP方法

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Establishing unified industrial technical standards for a single enterprise in a highly global integrated market is becoming increasingly difficult. In recent years, leading enterprises have often built technical standards alliances around a key core technology to develop industrial standards cooperatively in order to learn from each other and optimize their resource allocation. Although such technical standards alliances result in huge gains to their members, their internal and external risks threaten both the alliances and their members. As compared to other forms of strategic alliances, the risk of such an alliance has fuzzy characteristics and is difficult to fully and accurately identify. This paper uses a fuzzy pattern-recognition method to evaluate and summarize the risks of technical standards alliances. A fuzzy analytic hierarchy process (AHP) evaluation and back propagation (BP) logic fuzzy neural network methods are used to construct a risk-evaluation model of technical standards alliances while considering an alliance around new-energy automobiles in Zhejiang as an empirical example. The two evaluation models are then contrastively analyzed, and cross validation of the evaluation results is performed in order to provide theoretical guidance and support for the application of two fuzzy evaluation models in practice.
机译:在高度全球综合市场中为单一企业建立统一的工业技术标准变得越来越困难。近年来,龙头企业经常建立围绕关键核心技术的技术标准联盟,以协同发展工业标准,以便彼此学习并优化其资源分配。虽然此类技术标准联盟导致其成员提出巨大的收益,但其内部和外部风险威胁着联盟及其成员。与其他形式的战略联盟相比,这种联盟的风险具有模糊特性,并且难以完全和准确地识别。本文采用模糊模式识别方法来评估和总结技术标准联盟的风险。模糊分析层次处理(AHP)评估和反向传播(BP)逻辑模糊神经网络方法用于构建技术标准联盟的风险评估模型,同时考虑浙江省新能源汽车的联盟作为实证例子。然后对两个评估模型进行了对比分析,并且进行了评估结果的交叉验证,以便为在实践中应用两个模糊评估模型的理论指导和支持。

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