检索结果-南通市图书馆

Detecting DNS Covert Channels Using stacking model

China Communications 2020年第10期17卷 183-194页

作者： Peng Yang Ye Li Yunze Zang National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing 100029China Institute of Information Engineering Chinese Academy of SciencesBeijing 100093China

A covert channel is an information channel that is used by the computer process to exfiltrate data through bypassing security *** DNS protocol is one of the important ways to implement a covert *** covert channels are easily used by attackers for malicious ***,an effective detection approach of the DNS covert channels is significant for computer systems and network *** at the difficulty of the DNS covert channel identification,we propose a DNS covert channel detection method based on a stacking *** stacking model is evaluated on a campus network and the experimental results show that the detection based on the stacking model can detect the DNS covert channels ***,it can identify unknown covert channel *** area under the curve(AUC)of the proposed method reaches 0.9901,which outperforms existing detection methods.

关键词： DNS covert channel stacking model

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Electroencephalogram Emotion Recognition Based on A stacking Classification model

Electroencephalogram Emotion Recognition Based on A Stacking...

引用

第37届中国控制会议

作者： Qiao Xie Zhen-Tao Liu Xue-Wen Ding School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

To improve the accuracy of Electroencephalogram(EEG) emotion recognition,a stacking emotion classification model is proposed,in which different classification models such as XGBoost,LightGBM and Random Forest are integrated to learn the *** addition,the Renyi entropy of 32 channels' EEG signals are extracted as the feature and Linear discriminant analysis(LDA) is employed to reduce the dimension of the feature *** proposal is tested on the DEAP dataset,and the EEG emotional states are accessed in Arousal-Valence emotion space,in which HA/LA and HV/LV are classified,*** result shows that the average recognition accuracies of 77.19%for HA/LA and 79.06%for HV/LV are obtained,which demonstrates that the proposal is feasible in EEG emotion recognition.

关键词： Emotion recognition Electroencephalogram stacking model Renyi entropy

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

A stacking machine learning model for predicting pullout capacity of small ground anchors

引用

AI in Civil Engineering 2024年第1期3卷 221-235页

作者： Lin Li Linlong Zuo Guangfeng Wei Shouming Jiang Jian Yu School of Highway Chang’an UniversityXi’an 710064China Shanghai Baoye Group Co. LtdShanghai 200941China Department of Geotechnical Engineering Tongji UniversityShanghai 200092China

Small ground anchors are widely used to fix securing tents in disaster relief *** the urgent nature of rescue operations,it is crucial to obtain prompt and accurate estimations of their pullout *** this study,a stacking machine learning(ML)model is developed for the rapid estimation of pullout capacity offered by small ground anchors used for temporary tents,leveraging cone penetration *** proposed stacking model incorporates three ML algorithms as the base regression models:K-nearest neighbors(KNN),support vector regression(SVR),and extreme gradient boosting(XGBoost).A dataset comprising 119 in-situ anchor pullout tests,where the cone penetration data were measured,is utilized to train and assess the stacking model *** metrics,i.e.,coefficient of determination(R2),mean absolute error(MAE),and root mean square error(RMSE),are employed to evaluate the predictive accuracy of the proposed model and compare its performance against four popular ML models and an empirical formula to highlight the advantages of the proposed stacking *** results affirm that the proposed stacking model outperforms other ML models and the empirical approach as achieving higher R2 and lower MAE and RMSE and more predicted data points falling within 20%error ***,the proposed stacking model holds promising potential as a solution for efficiently predicting the pullout capacity of small ground anchors.

关键词： Ground anchor Pullout capacity stacking model model performance Machine learning

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Novel stacking models based on SMOTE for the prediction of rockburst grades at four deep gold mines

引用

Underground Space 2024年第6期19卷 169-188页

作者： Peng Xiao Zida Liu Guoyan Zhao Pengzhi Pan State Key Laboratory of Geomechanics and Geotechnical Engineering Institute of Rock and Soil MechanicsChinese Academy of SciencesWuhan 430071China School of Resources and Safety Engineering Central South UniversityChangsha 410083China

Rockburst is a frequently encountered hazard during the production of deep gold *** prediction of rockburst is an important measure to prevent rockburst in gold *** study considers seven indicators to evaluate rockburst at four deep gold *** research and rock tests were performed at two gold mines in China to collect these seven indicators and rockburst *** collected database was oversampled by the synthetic minority oversampling technique(SMOTE)to balance the categories of rockburst *** models combining tree-based models and logistic regression(LR)were established by the balanced *** datasets from another two deep gold mines were implemented to verify the applicability of the predictive *** stacking model combining extremely randomized trees and LR based on SMOTE(SMOTE-ERT-LR)was the best model,and it obtained a training accuracy of 100%and an evaluation accuracy of 100%.Moreover,model evaluation suggested that SMOTE can enhance the prediction performance for weak rockburst,thereby improving the overall ***,sensitivity analysis was performed for *** results indicated that the SMOTE-ERT-LR model can achieve satisfactory performance when only depth,maximum tangential stress index,and linear elastic energy index were available.

关键词： Rockburst prediction Gold mine stacking model SMOTE

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Structures and Properties of Polyimide with Different Pre-imidization Degrees

引用

Chinese Journal of Polymer Science 2020年第8期38卷 840-846,I0006页

作者： Fu-Yao Hao Jian-Hua Wang Sheng-Li Qi Guo-Feng Tian De-Zhen Wu State Key Laboratory of Chemical Resource Engineering Beijing University of Chemical TechnologyBeijing 100029China

A series of polyimide(PI)films derived from pyromellitic dianhydride(PMDA)and 4,4'-oxydianiline(ODA)were prepared with the employment of chemical pre-imidization,and the pre-imidization degree(pre-ID)was found influential on structures and properties of the films ***,a certain degree of chemical imidization could promote the in-plane orientation of molecular chains inside the film,which then enhanced the mechanical strength and reduced the coefficient of thermal expansion(CTE)of the ***,such pre-imidization process could expand the internal space gap inside the films,thereby lowering their dielectric constant and glass transition *** study provides a new approach for preparing high-performance PI films through chemical imidization.

关键词： Polyimide Pre-imidization stacking model In-plane orientation

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Fine-Grained Emotion Prediction for Movie and Television scene images

引用

The Journal of China Universities of Posts and Telecommunications 2024年第3期31卷 43-55页

作者： Su Zhibin Zhou Xuanye Liu Bing Ren Hui State Key Laboratory of Media Convergence and Communication Communication University of ChinaBeijing 100024China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of ChinaBeijing 100024China School of Information and Communication Engineering Communication University of ChinaBeijing 100024China

For the task of content retrieval,analysis and generation of film and television scene images in the field of intelligent editing,fine-grained emotion recognition and prediction of images is of great *** this paper,the fusion of traditional perceptual features,art features and multi-channel deep learning features are used to reflect the emotion expression of different levels of the *** addition,the integrated learning model with stacking architecture based on linear regression coefficient and sentiment correlations,which is called the LS-stacking model,is proposed according to the factor association between multi-dimensional *** experimental results prove that the mixed feature and LS-stacking model can predict well on the 16 emotion categories of the self-built image *** study improves the fine-grained recognition ability of image emotion by computers,which helps to increase the intelligence and automation degree of visual retrieval and post-production system.

关键词： fine-grained emotion prediction movie and television scene images stacking model linear regression

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：