Biological immune system by evolutionary adaptive learning of neural networks

S. Oeda, T. Icmmura, T. Yamashita
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引用次数: 3

Abstract

Artificial immune systems have been identified as artificially intelligent systems. Some algorithms have been developed on this antigen-antibody response. Here, a model is presented wherein the behavior of each immune cell is specified. We improve this model using knowledge of the major histocompatibility complex. For this purpose an evolutionary neural network was used. Qualitative analysis of the results offers verification of the effectiveness of this approach to simulating an immune system.
生物免疫系统的进化适应学习神经网络
人工免疫系统是一种人工智能系统。针对这种抗原-抗体反应已经开发了一些算法。这里,提出了一个模型,其中每个免疫细胞的行为是指定的。我们利用主要组织相容性复合体的知识来改进这个模型。为此,使用了进化神经网络。对结果进行定性分析,验证了这种方法模拟免疫系统的有效性。
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