ID 原文 译文
40336 为了在攻击形式多样化、入侵数据海量及多维化的环境中快速、准确地识别网络攻击，提出了一种融合Fisher-PCA特征提取与深度学习的入侵检测算法。 To quickly and accurately identify network attacks in a multi-dimensional environment with diversified attack forms and massive intrusion data, an intrusion detection model combining Fisher-PCA feature extraction and deep learning is proposed.
40337 通过Fisher特征选择算法选出重要的特征组成特征子集，然后基于主成分分析法(Principal component analysis，PCA)将特征子集进行降维，提取出了分类能力强的特征集。 Firstly, the Fisher feature selection algorithm selects important features to form feature subsets. Then the dimension of the feature subsets is reduced based on principal component analysis(PCA)and the feature set with strong classification ability is extracted.
40338 构建了一种新的深度神经网络(Deep neural networks，DNN)模型对网络攻击数据和正常数据进行识别与分类。 A new deep neural network(DNN)is constructed to identify and classify network attack data and normal data.
40339 在KDD99数据集上进行实验，结果表明：与传统的人工神经网络(Artificial neural network，ANN)和支持向量机(Support vector machine，SVM)算法相比，这种入侵检测算法的准确率分别提高了12.63%和6.77%，误报率由原来的2.31%和1.96%降为0.28%； Experimental results on KDD99 dataset show that compared with the traditional artificial neural network(ANN)and support vector machine(SVM)algorithms, the accuracy of this intrusion detection algorithm can be improved by 12.63% and 6.77%, respectively, and the false alarm rate is reduced from2.31% and 1.96% to 0.28%.
40340 与DBN4和PCA-CNN算法相比，在准确率和检测率保持基本相同的同时有着更低的误报率。 Compared with DBN4 and PCA-CNN algorithms, its accuracy and detection rate are basically the same, while the false alarm rate is lower.
40341 提出了基于LDA主题模型和直觉模糊TOPSIS的农产品在线评论情感分析方法。 An emotional analysis method based on LDA thematic model and intuitionistic fuzzy TOPSIS for agricultural product online reviews was proposed.
40342 该方法使用情感词典对在线评论进行情感倾向分析，并计算农产品的积极情感值； The method uses the affective dictionary to analyze the emotional tendency of online comments and calculate the positive emotional value of agricultural products.
40343 运用LDA主题模型计算各个属性的权重，结合直觉模糊TOPSIS方法计算农产品的综合评价值； The LDA thematic model is used to calculate the weight of each attribute, and the comprehensive evaluation value of agricultural products is calculated with the intuitive fuzzy TOPSIS method.
40344 采用SPSS统计分析软件进行有效性检验。 SPSS statistical analysis software was used to verify the validity.
40345 结果表明，综合评价值与月销售量、积极情感值呈显著的正相关性，说明该方法具有合理性，为挖掘农产品在线评论中的情感信息提供一种新的思路。 The results show that the comprehensive evaluation value has a significant positive correlation with monthly sales volume and positive emotional value, which indicates that the method is reasonable and provides a new idea for mining emotional information in the online evaluation of agricultural products.