stronger anti-interference performance同义替换

更强的抗干扰性能 (stronger anti-interference capability)
更强的抗干扰性能 (enhanced resistance to interference)
更强的抗干扰性能 (improved immunity to interference)
更强的抗干扰性能 (greater resilience to interference)
更强的抗干扰性能 (enhanced anti-jamming performance)
更强的抗干扰性能 (superior anti-interference effectiveness)

相关问题

The conventional convolution neural network (CNN) adopts softmax function as classifier, which has problems of overflow and underflow. This paper proposes a rolling bearing intelligent fault diagnosis method based on multi-scale convolution neural network, bi-directional long short term memory and support vector machine (MCNN-BiLSTM-SVM). The wavelet threshold denoising algorithm is adopted for signal preprocessing. The multi-scale convolution neural network (MCNN) and the bidirectional long short-term memory network (BiLSTM) are combined as the feature extractor to improve feature extraction capability. The support vector machine (SVM) is adopted as the classifier to improve classification performance. Transfer learning is used in MCNN-BiLSTM-SVM for different conditions. According to the experiments, the proposed MCNN-BiLSTM-SVM fault diagnosis method has higher diagnostic accuracy, stronger anti-noise performance and better stability under different conditions than other diagnostic methods.给出以上内容审稿意见

本文提出了一种基于多尺度卷积神经网络、双向长短时记忆网络和支持向量机的轴承智能故障诊断方法（MCNN-BiLSTM-SVM）。该方法采用小波阈值去噪算法进行信号预处理，将多尺度卷积神经网络（MCNN）和双向长短时记忆网络（BiLSTM）组合作为特征提取器，以提高特征提取能力；采用支持向量机（SVM）作为分类器，以提高分类性能。在MCNN-BiLSTM-SVM中使用迁移学习处理不同条件下的数据。经过实验验证，本文提出的MCNN-BiLSTM-SVM故障诊断方法具有更高的诊断准确性、更强的抗噪性能和更好的稳定性，优于其他诊断方法。

该论文在轴承智能故障诊断方面提出了一种新的方法，并且通过实验证明其有效性。同时，论文的结构清晰，表述准确，实验数据充分且有说服力。建议作者进一步说明MCNN-BiLSTM-SVM方法在处理不同条件下的数据时，采用了哪些具体的迁移学习方法，以便读者更好地理解。此外，建议作者在文献综述中加入更多相关领域的研究工作，以进一步突显本文的创新性和实用性。

-webkit-font-smoothing

WebKit-font-smoothing is a CSS property used to control how fonts appear on web pages in WebKit-based browsers such as Safari, Chrome, and Opera. It is used to improve the readability and aesthetics of text on a webpage.

The property is used to control the anti-aliasing of fonts, which is the smoothing of jagged edges that appear when fonts are displayed on screens. By default, anti-aliasing is enabled on WebKit-based browsers, but the -webkit-font-smoothing property allows web developers to make adjustments to the anti-aliasing to achieve different effects.

The property values include:

- auto: This is the default value and enables the browser to use its own algorithm to determine the best font smoothing for the text.
- none: This value turns off font smoothing completely, resulting in jagged edges around text.
- antialiased: This value enables a light anti-aliasing effect, which smooths out the edges of the text slightly.
- subpixel-antialiased: This value enables a stronger anti-aliasing effect, which uses sub-pixel rendering to smooth out the edges of the text even more.

The -webkit-font-smoothing property can be applied to individual elements or the entire body of a webpage. It is a useful tool for web developers who want to control the appearance of text on their web pages and ensure a consistent user experience across different browsers.