Research And Applications Of Clone Immune Network Algorithm

The artificial immune system (AIS) is one of important field in the artificial intelligent research emerging after the artificial network; evolution computing and fuzzy system. It is inspired from the biological immune system and imitates the function of natural immune systems as an intelligent method. In this paper, we took the artificial immune system as the research background. After having compared with the immune network model and referred to their advantages and disadvantages suggested by other people, we designed an optimized algorithm, The Clone Immune Network Algorithm, which is based on the conditional immune theory. The core of this algorithm is some operators combining the clone selection theory with the idiotype immune network theory. These operators include the antibody selection operator, the antibody clone operator, the antibody recombination operator, the antibody variation operator, the antibody restraint operator and so on. And with the Markov chain state translation theory, we proved the probability weak convergence of the clone immune network algorithm. The simulation research stated that it was not only effective but also feasible.The clone immune network algorithm is an optimized algorithm in nature. So it can be widely used in many fields, such as automatic control, optimization design, fault diagnosis, pattern recognition, data...