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。

相关问题

Write the statement(s) necessary to increase the customer’s number of orders by 1 using “getter” and “setter” methods, named getNumberOfOrders and setNumberofOrders, as conventional in Java.

Assuming that the `Customer` class has getter and setter methods for the `numberOfOrders` field, named `getNumberOfOrders()` and `setNumberOfOrders()`, respectively, you can increase the number of orders by 1 using the following statement in Java:

customer.setNumberOfOrders(customer.getNumberOfOrders() + 1);

This code will call the `getNumberOfOrders()` method to retrieve the current number of orders, increment it by 1, and then call the `setNumberOfOrders()` method with the new value to update the `numberOfOrders` field.

Function dir returns the contents of a specified directory. The dir command returns a structure array with four fields, as follows: » d = dir('chap7') d = 36x1 struct array with fields: name date bytes isdir The field name contains the names of each file, date contains the last modification date for the file, bytes contains the size of the file in bytes, and isdir is 0 for conventional files and 1 for directories. Write a function that accepts a directory name and path and returns the total size of all files in the directory, in bytes.用matlab写

以下是一个用 MATLAB 编写的函数，它接受一个目录名和路径，并返回该目录中所有文件的总大小（以字节为单位）：

function totalSize = calculateTotalFileSize(directory)
% 获取目录下所有文件信息
dirInfo = dir(directory);
% 初始化总文件大小
totalSize = 0;
% 循环遍历每个文件
for i = 1:length(dirInfo)
    % 如果当前项是一个文件而不是目录
    if ~dirInfo(i).isdir
        % 累加文件大小
        totalSize = totalSize + dirInfo(i).bytes;
    end
end
end

你可以将上述代码保存到一个名为 `calculateTotalFileSize.m` 的文件中，并在 MATLAB 中调用该函数来计算目录中所有文件的总大小。例如，假设你想计算当前目录下所有文件的大小，你可以输入以下命令：

totalSize = calculateTotalFileSize(pwd)

这将返回一个表示当前目录下所有文件大小之和的数字。