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首页> 外文期刊>International Journal of Electrical Engineering: Transactions of the Chinese Institute of Engineers, Series E >A SOFTWARE RELIABILITY PREDICTION BASED ON RBM ALGORITHM IMPROVEMENT METHOD
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A SOFTWARE RELIABILITY PREDICTION BASED ON RBM ALGORITHM IMPROVEMENT METHOD

机译：一种基于RBM算法改进方法的软件可靠性预测

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摘要

Although the classic DBN has a good capability of feature extraction layer by layer and plays an important role in the area of software reliability prediction, training data still costs more time, and test error rate is relatively large. Therefore, the algorithm and network structure of DBN still has room for improvement. In this paper, the algorithms and architectures of DBN model is improved by determining the input dimension combined with self-organizing algorithm, automatically adjusting the number of hidden units and adding the support vector machine (SVM) classifier with the model output. In this way, it will not only substantially reduce the amount of information loss in each layer and the time of training data, but also improving the prediction accuracy of software reliability prediction. In order to verify the superiority of the improved software reliability prediction model, we have compared the traditional DBN software reliability prediction model with the improved one by experiment in this paper.
机译：虽然经典DBN通过层具有良好的特征提取层的能力，但在软件可靠性预测的区域中起重要作用，训练数据仍然需要更多的时间，并且测试错误率相对较大。因此，DBN的算法和网络结构仍然具有改进的空间。在本文中，通过确定输入维度与自组织算法确定输入维度，自动调整隐藏单元的数量并将支持向量机（SVM）分类器添加到模型输出，改进了DBN模型的算法和架构。以这种方式，它不仅大大减少了每层的信息损失和训练数据的时间，而且还提高了软件可靠性预测的预测准确性。为了验证改进的软件可靠性预测模型的优越性，我们通过本文通过实验将传统的DBN软件可靠性预测模型与改进的一个进行了比较。

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