文件名称:libsvm-3.1-[FarutoUltimate3.1Mcode]
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态势要素获取作为整个网络安全态势感知的基础,其质量的好坏将直接影响态势感知系统的性能。针对态势要素不易获取问题,提出了一种基于增强型概率神经网络的层次化框架态势要素获取方法。在该层次化获取框架中,利用主成分分析(PCA)对训练样本属性进行约简并对特殊属性编码融合处理,将其结果用于优化概率神经网络(PNN)结构,降低系统复杂度。以PNN作为基分类器,基分类器通过反复迭代、权重更替,然后加权融合处理形成最终的强多分类器。实验结果表明,该方案是有效的态势要素获取方法并且精确度达到95.53%,明显优于文中其他算法,有较好的泛化能力。(As the basis of the whole network security situation awareness, the quality of situation elements extraction will directly affect the performance of the situation awareness system. To solve the problem that the situation element is difficult to extract, we propose a method to extract the hierarchical frame situation elements based on the enhanced probabilistic neural network. In the hierarchical access frame, we use the principal component analysis (PCA) to reduct the training sample attribute and to process the special attribute encoding fusion. The result can be used to optimize the structure of the probabilistic neural network (PNN) and reduce the system complexity. Take PNN as the base classifier to form the final strong classifier by repeated iteration, weight replacement and weighted fusion. The experimental results show that the scheme is an effective method to obtain the situation factors and its accuracy is 95.53%,which is significantly better than other algorithms.)
相关搜索: 网络安全;态势要素
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下载文件列表
tools\checkdata.py
tools\easy.py
tools\grid.py
tools\README
tools\subset.py
windows\libsvm.dll
windows\libsvmread.mexw32
windows\libsvmread.mexw64
windows\libsvmwrite.mexw32
windows\libsvmwrite.mexw64
windows\svm-predict.exe
windows\svm-scale.exe
windows\svm-toy.exe
windows\svm-train.exe
windows\svmpredict.mexw32
windows\svmpredict.mexw64
windows\svmtrain.mexw32
windows\svmtrain.mexw64
svm.cpp.bak
svm-predict.c
svm-scale.c
svm-train.c
svm.h
svm.cpp
svm.def
FAQ.html
Makefile.win
COPYRIGHT
heart_scale
Makefile
README
java\libsvm\svm.java
java\libsvm\svm.m4
java\libsvm\svm_model.java
java\libsvm\svm_node.java
java\libsvm\svm_parameter.java
java\libsvm\svm_print_interface.java
java\libsvm\svm_problem.java
java\libsvm.jar
java\Makefile
java\svm_predict.java
java\svm_scale.java
java\svm_toy.java
java\svm_train.java
java\test_applet.html
matlab\heart_scale.mat
matlab\libsvmread.c
matlab\libsvmread.mexw32
matlab\libsvmwrite.c
matlab\libsvmwrite.mexw32
matlab\make.m
matlab\Makefile
matlab\README
matlab\svm.obj
matlab\svmpredict.c
matlab\svmpredict.mexw32
matlab\svmtrain.c
matlab\svmtrain.c.bak
matlab\svmtrain.mexw32
matlab\svm_model_matlab.c
matlab\svm_model_matlab.h
matlab\svm_model_matlab.obj
matlab-implement[by faruto]\a_template_flow_usingSVM_class.m
matlab-implement[by faruto]\a_template_flow_usingSVM_regress.m
matlab-implement[by faruto]\ClassResult.m
matlab-implement[by faruto]\ClassResult_test.m
matlab-implement[by faruto]\gaSVMcgForClass.m
matlab-implement[by faruto]\gaSVMcgForRegress.m
matlab-implement[by faruto]\gaSVMcgpForRegress.m
matlab-implement[by faruto]\libsvm参数说明.txt
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\bs2rv.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\contents.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtbase.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtbp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtrp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\migrate.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mpga.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mut.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mutate.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mutbga.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mytest\gaSVM.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\ranking.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recdis.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recint.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\reclin.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recmut.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recombin.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\reins.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\rep.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\resplot.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\rws.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\scaling.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\select.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\sus.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovdp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovdprs.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovmp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovsh.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovshrs.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovsp.m
tools\easy.py
tools\grid.py
tools\README
tools\subset.py
windows\libsvm.dll
windows\libsvmread.mexw32
windows\libsvmread.mexw64
windows\libsvmwrite.mexw32
windows\libsvmwrite.mexw64
windows\svm-predict.exe
windows\svm-scale.exe
windows\svm-toy.exe
windows\svm-train.exe
windows\svmpredict.mexw32
windows\svmpredict.mexw64
windows\svmtrain.mexw32
windows\svmtrain.mexw64
svm.cpp.bak
svm-predict.c
svm-scale.c
svm-train.c
svm.h
svm.cpp
svm.def
FAQ.html
Makefile.win
COPYRIGHT
heart_scale
Makefile
README
java\libsvm\svm.java
java\libsvm\svm.m4
java\libsvm\svm_model.java
java\libsvm\svm_node.java
java\libsvm\svm_parameter.java
java\libsvm\svm_print_interface.java
java\libsvm\svm_problem.java
java\libsvm.jar
java\Makefile
java\svm_predict.java
java\svm_scale.java
java\svm_toy.java
java\svm_train.java
java\test_applet.html
matlab\heart_scale.mat
matlab\libsvmread.c
matlab\libsvmread.mexw32
matlab\libsvmwrite.c
matlab\libsvmwrite.mexw32
matlab\make.m
matlab\Makefile
matlab\README
matlab\svm.obj
matlab\svmpredict.c
matlab\svmpredict.mexw32
matlab\svmtrain.c
matlab\svmtrain.c.bak
matlab\svmtrain.mexw32
matlab\svm_model_matlab.c
matlab\svm_model_matlab.h
matlab\svm_model_matlab.obj
matlab-implement[by faruto]\a_template_flow_usingSVM_class.m
matlab-implement[by faruto]\a_template_flow_usingSVM_regress.m
matlab-implement[by faruto]\ClassResult.m
matlab-implement[by faruto]\ClassResult_test.m
matlab-implement[by faruto]\gaSVMcgForClass.m
matlab-implement[by faruto]\gaSVMcgForRegress.m
matlab-implement[by faruto]\gaSVMcgpForRegress.m
matlab-implement[by faruto]\libsvm参数说明.txt
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\bs2rv.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\contents.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtbase.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtbp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\crtrp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\migrate.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mpga.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mut.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mutate.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mutbga.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\mytest\gaSVM.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\ranking.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recdis.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recint.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\reclin.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recmut.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\recombin.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\reins.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\rep.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\resplot.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\rws.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\scaling.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\select.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\sus.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovdp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovdprs.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovmp.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovsh.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovshrs.m
matlab-implement[by faruto]\myprivate\gatbx[Sheffield]\xovsp.m
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