The Study Based on Danger Model Inspired Algorithms
|Course||Applied Computer Technology|
|Keywords||Danger Model Artificial Immune Data Mining Immune Algorithm Association rules Cluster analysis Intrusion Detection|
In recent years , the biological immune system has become an emerging bioinformatics research topic . It is in addition to the nervous system , the body is able to specifically identify the self / non-self \Immune mode SNS the entire immune academia generally circulating a new theory , that is dangerous mode \This theory is pioneering Matzinger, that the immune system can not distinguish between the self / non-self (SNS) and the only distinction between the presence or absence of danger signals (danger signal) . This broke past tolerance of understanding , and questioned the basic theory of modern immunology traditional immune system only distinguish SNS \good explanation , has aroused the scholars widespread concern greater impact . Danger Model theory is not an extension of the immune response , but a new theoretical model . Although so far has not been the biological immune profession generally recognized , but completely artificial immunity for a simulation system for biological immune system can get rid of the shackles of the biological immune cognition , but expanded to the field of artificial immune . Based on the basis of the immune system and the risk of model theory , the article discusses the framework of the system of data mining theory , learn the science of life immune danger model immune model theory around dangerous patterns of immune - based algorithms , association rule mining and data clustering analysis data mining techniques , the proposed approach and its application of data mining algorithm based on the danger model immune .