Inspired by the immune network theory, an adaptive anomaly detection paradigm based on artificial immune network, referred as APAI, is proposed. The implementation of the paradigm includes： initially, the first is to...Inspired by the immune network theory, an adaptive anomaly detection paradigm based on artificial immune network, referred as APAI, is proposed. The implementation of the paradigm includes： initially, the first is to create the initial antibody network; then, through the learning of each training antigen, the antibody network is evolved and updated by the optimal antibodies. Finally, anomaly detection process is accomplished by majority vote of the k nearest neighbor antibodies in the network. The experiments used the famous Sonar Benchmark dataset in our study, which is taken from the UCI machine learning database. The obtained detection accuracy of APAI was 97.7%, which was very promising with regard to the other classification applications in the literature for this problem. In addition to its nonlinear classification properties, APAI possesses biological immune network properties such as clonal selection, immune network, and immune memory, which can be applied to pattern recognition, classification, and etc.展开更多
Previous studies,including ASME and RCC-MR standards,did not consider the influence of environmental factors on the ratcheting boundary of the material,and only a unified ratcheting boundary was proposed.In this paper...Previous studies,including ASME and RCC-MR standards,did not consider the influence of environmental factors on the ratcheting boundary of the material,and only a unified ratcheting boundary was proposed.In this paper,thermal aging was taken into consideration,and the effect of thermal aging time on the ratcheting boundary of 316 LN austenitic stainless steel was characterized by the efficiency diagram rule.The results show that,when the secondary ratio U is small,there is no significant difference in ratcheting boundary between the original material and the thermal aged material.When the secondary ratio U is large,the ratcheting boundary of the material presents a slight upward trend with the increase of thermal aging time.Compared with ASME and RCC-MR standards,it is found that RCC-MR is conservative.Based on the evolution of the efficiency index V with the number of cycles,it is more conservative and reasonable to choose the stage when the efficiency index V develops into a constant.展开更多
基金Supported by the National High Technology Research and Development Program of Chin(a863 Program)(2006AA01Z435)the National Natural Science Foundation of China (60573130, 60502011).
文摘Inspired by the immune network theory, an adaptive anomaly detection paradigm based on artificial immune network, referred as APAI, is proposed. The implementation of the paradigm includes： initially, the first is to create the initial antibody network; then, through the learning of each training antigen, the antibody network is evolved and updated by the optimal antibodies. Finally, anomaly detection process is accomplished by majority vote of the k nearest neighbor antibodies in the network. The experiments used the famous Sonar Benchmark dataset in our study, which is taken from the UCI machine learning database. The obtained detection accuracy of APAI was 97.7%, which was very promising with regard to the other classification applications in the literature for this problem. In addition to its nonlinear classification properties, APAI possesses biological immune network properties such as clonal selection, immune network, and immune memory, which can be applied to pattern recognition, classification, and etc.
基金the National Natural Science Foundation of China(Grant No.51435012)。
文摘Previous studies,including ASME and RCC-MR standards,did not consider the influence of environmental factors on the ratcheting boundary of the material,and only a unified ratcheting boundary was proposed.In this paper,thermal aging was taken into consideration,and the effect of thermal aging time on the ratcheting boundary of 316 LN austenitic stainless steel was characterized by the efficiency diagram rule.The results show that,when the secondary ratio U is small,there is no significant difference in ratcheting boundary between the original material and the thermal aged material.When the secondary ratio U is large,the ratcheting boundary of the material presents a slight upward trend with the increase of thermal aging time.Compared with ASME and RCC-MR standards,it is found that RCC-MR is conservative.Based on the evolution of the efficiency index V with the number of cycles,it is more conservative and reasonable to choose the stage when the efficiency index V develops into a constant.
