In this paper,we propose a novel Intrusion Detection System (IDS) architecture utilizing both the evidence theory and Rough Set Theory (RST). Evidence theory is an effective tool in dealing with uncertainty question. ...In this paper,we propose a novel Intrusion Detection System (IDS) architecture utilizing both the evidence theory and Rough Set Theory (RST). Evidence theory is an effective tool in dealing with uncertainty question. It relies on the expert knowledge to provide evidences,needing the evidences to be independent,and this make it difficult in application. To solve this problem,a hybrid system of rough sets and evidence theory is proposed. Firstly,simplification are made based on Variable Precision Rough Set (VPRS) conditional entropy. Thus,the Basic Belief Assignment (BBA) for all evidences can be calculated. Secondly,Dempster’s rule of combination is used,and a decision-making is given. In the proposed approach,the difficulties in acquiring the BBAs are solved,the correlativity among the evidences is reduced and the subjectivity of evidences is weakened. An illustrative example in an intrusion detection shows that the two theories combination is feasible and effective.展开更多
Damage on surfaces often compromises the efficiency of some types of energy production, the safety and reliability of components, and ultimately increases costs. The environment can degrade the structural integrity of...Damage on surfaces often compromises the efficiency of some types of energy production, the safety and reliability of components, and ultimately increases costs. The environment can degrade the structural integrity of surfaces in service by the accumulation of large numbers of small destructive events, which based on the Central Limit Theorem leads to a Gaussian distribution of pit depth. In order to develop safety envelopes relating fracture loci with topological parameters of a brittle material, scatter plots were obtained and analyzed. Starting with an engineering surface, after 6 to 9 micrometers of average degradation depth, safety envelopes could be developed using average roughness and two other proposed parameters. Interestingly, maximum pit depth showed very low correlation with the location of fracture, at the early stage of degradation studied. This is attributed to relaxation of stress concentration at a given pit location due to the assuaging effect caused by neighboring pits. Additionally, energy at fracture was obtained, and a maximum relaxation region was observed. Analytical and experimental study of this region, as well as ductility effects are currently under research.展开更多
Interval-valued data appear as a way to represent the uncertainty affecting the observed values. Dealing with interval-valued information systems is helpful to generalize the applications of rough set theory. Attribut...Interval-valued data appear as a way to represent the uncertainty affecting the observed values. Dealing with interval-valued information systems is helpful to generalize the applications of rough set theory. Attribute reduction is a key issue in analysis of interval-valued data. Existing attribute reduction methods for single-valued data are unsuitable for interval-valued data. So far, there have been few studies on attribute reduction methods for interval-valued data. In this paper, we propose a framework for attribute reduction in interval-valued data from the viewpoint of information theory. Some information theory concepts, including entropy, conditional entropy, and joint entropy, are given in interval-valued information systems. Based on these concepts, we provide an information theory view for attribute reduction in interval-valued information systems. Consequently, attribute reduction algorithms are proposed. Experiments show that the proposed framework is effective for attribute reduction in interval-valued information systems.展开更多
基金Supported by the National Natural Science Foundation of China (No. 60774029)
文摘In this paper,we propose a novel Intrusion Detection System (IDS) architecture utilizing both the evidence theory and Rough Set Theory (RST). Evidence theory is an effective tool in dealing with uncertainty question. It relies on the expert knowledge to provide evidences,needing the evidences to be independent,and this make it difficult in application. To solve this problem,a hybrid system of rough sets and evidence theory is proposed. Firstly,simplification are made based on Variable Precision Rough Set (VPRS) conditional entropy. Thus,the Basic Belief Assignment (BBA) for all evidences can be calculated. Secondly,Dempster’s rule of combination is used,and a decision-making is given. In the proposed approach,the difficulties in acquiring the BBAs are solved,the correlativity among the evidences is reduced and the subjectivity of evidences is weakened. An illustrative example in an intrusion detection shows that the two theories combination is feasible and effective.
文摘Damage on surfaces often compromises the efficiency of some types of energy production, the safety and reliability of components, and ultimately increases costs. The environment can degrade the structural integrity of surfaces in service by the accumulation of large numbers of small destructive events, which based on the Central Limit Theorem leads to a Gaussian distribution of pit depth. In order to develop safety envelopes relating fracture loci with topological parameters of a brittle material, scatter plots were obtained and analyzed. Starting with an engineering surface, after 6 to 9 micrometers of average degradation depth, safety envelopes could be developed using average roughness and two other proposed parameters. Interestingly, maximum pit depth showed very low correlation with the location of fracture, at the early stage of degradation studied. This is attributed to relaxation of stress concentration at a given pit location due to the assuaging effect caused by neighboring pits. Additionally, energy at fracture was obtained, and a maximum relaxation region was observed. Analytical and experimental study of this region, as well as ductility effects are currently under research.
基金Project supported by the National Natural Science Foundation of China(Nos.61473259,61502335,61070074,and60703038)the Zhejiang Provincial Natural Science Foundation(No.Y14F020118)the PEIYANG Young Scholars Program of Tianjin University,China(No.2016XRX-0001)
文摘Interval-valued data appear as a way to represent the uncertainty affecting the observed values. Dealing with interval-valued information systems is helpful to generalize the applications of rough set theory. Attribute reduction is a key issue in analysis of interval-valued data. Existing attribute reduction methods for single-valued data are unsuitable for interval-valued data. So far, there have been few studies on attribute reduction methods for interval-valued data. In this paper, we propose a framework for attribute reduction in interval-valued data from the viewpoint of information theory. Some information theory concepts, including entropy, conditional entropy, and joint entropy, are given in interval-valued information systems. Based on these concepts, we provide an information theory view for attribute reduction in interval-valued information systems. Consequently, attribute reduction algorithms are proposed. Experiments show that the proposed framework is effective for attribute reduction in interval-valued information systems.
