Fuzzy Numbers Unraveling the Intricacies of Neural Network Functionality

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Abstract

This research delves into the synergy between fuzzy numbers and neural networks, presenting a novel perspective on interpreting neural network functionality. Fuzzy numbers offer a flexible framework to capture uncertainties and imprecisions, enriching the interpretability of neural network outputs. By integrating fuzzy number theory into the analysis, our study seeks to enhance the transparency and reliability of neural network models, contributing to a more nuanced understanding of their inner
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模糊数 揭开神经网络功能的神秘面纱
这项研究深入探讨了模糊数与神经网络之间的协同作用,提出了解读神经网络功能的新视角。模糊数为捕捉不确定性和不精确性提供了一个灵活的框架,丰富了神经网络输出的可解释性。通过将模糊数理论融入分析,我们的研究力求提高神经网络模型的透明度和可靠性,从而有助于更细致地理解其内在功能。
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