Description: this an immune program in matlab that show you how initial antibody population and other steps in immune algorithm-this is an immune program in matlab that show you how initial antibody population and other steps in immune algorithm Platform: |
Size: 1024 |
Author:maryam |
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Description: 量子进化算法和免疫算法都是解决优化问题的强有力算法。在分析了量子进化算法搜索的特点和免疫算法的机理基础上，对它们进行比较，阐明了二者的不同特点-Quantum-inspired evolutionary algorithms and immune algorithms are a powerful algorithm to solve optimization problems. After analyzing the characteristics of the quantum evolutionary algorithm and immune algorithm search mechanism based on the comparison of them to clarify the different characteristics of the two Platform: |
Size: 825344 |
Author:daijiang |
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Description: 针对目标与背景两类图像模式识别问题,在已有的特征选择方法基础上,提出了一种新颖的基于免疫分子编码机理的图像特征选择方法(IACA). 该方法借鉴生物免疫系统的抗体分
子编码机理,在对样本进行参数估计情况下,提出熵度量单个特征对于目标和背景的识别敏感度 从集合的角度研究并且定义了特征之间的包含和互补关系 并且基于组成抗体分子氨基酸结合能量最小原则,提出了关于图像目标的免疫抗体构建规则 最终实现了寻找最优特征子集的算法IACA ,该特征子集的维数通过算法自动获得无需人为设定,选择结果为目标的“免疫抗体”,能很好的从背景中识别目标. 利用归纳法证明了用IACA 得到的特征子集的最优性. 与其他特征选择方法比较,测试结果显示该算法具有较低的计算复杂度和错误识别率,表明了该方法的优越性和先进性.-Aiming at two classes image pattern recognition problem of object and background , a novel image feature selection method ,named immune antibody construction algorithm ( IACA) is proposed , inspired by the biological immune antibody encoding principle. In the case of sample parameter estimation , IACA considers entropy to measure individual feature’s sensitivity of object and background ,and defines the inclusion and complementary formulas about multi features in set theory perspective. Guided by the minimum energy principle , image immune antibody construction rules and corresponding algorithm are proposed to find an
optimized feature subset as object immune antibody. Furthermore ,the dimension of the subset can be automatically determined with out prior setting. The induction proved the result was the optimal feature subset. Data testing result shows that IACA has a lower computational complexity and error recognition rate than other methods ,which has verified the superiority and t Platform: |
Size: 593920 |
Author:崔冰 |
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Description: 提出一种基于免疫原理的人工免疫算法,用于模糊关联规则的挖掘. 该算法通过借鉴生物免疫系统中的克隆选择原理来实施优化操作,它直接从给出的数据中,通过优化机制自动确定每个属性对应的模糊集合,使推导出的满足条件的模糊关联规则数目最多. 将实际数据集和相关算法进行性能比较,实验结果表明了所提出算法的有效性-An algorithm is proposed for mining fuzzy association rules based on immune principles , which is mainly
inspired by the clonal selection principle of biological immune systems. It is employed to optimize the number of st rong rules that satisfy the specified thresholds by adjusting the parameters of fuzzy sets for each quantitative att ribute. The
performances of the algorithm is compared with other relevant algorithms and the experimental result s show the effectiveness of the algorithm. Platform: |
Size: 406528 |
Author:崔冰 |
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Description: It is a general purpose one-class classification algorithm. As a development in the research area of Artificial Immune Systems (AIS), it is a negative selection algorithm, one of the earliest methods inspired by immune system. Negative selection algorithms are mainly based on the negative selection process in the thymus, in which immature T cells that recognize self cells are eliminated before the rest can mature and are deployed into the immune system.
The implementation posted here uses real-valued representation although the algorithm of V-detector should apply to other data representations as long as the matching rule can be expressed as a threshold of some distance measure.
Platform: |
Size: 602112 |
Author:nour12 |
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Description: 人工免疫算法：基本免疫算法基于生物免疫系统基本机制，模仿了人体的免疫系统。基本免疫算法从体细胞理论和网络理论得到启发，实现了类似于生物免疫系统的抗原识别、细胞分化、记忆和自我调节的功能 。如果将免疫算法与求解优化问题的一般搜索方法相比较，那么抗原、抗体、抗原和抗体之间的亲和性分别对应于优化问题的目标函数、优化解、解与目标函数的匹配程度-Artificial immune algorithm: the basic immune algorithm is based on the basic mechanisms of biological immune system, mimicking the body s immune system. Basic immune algorithm inspired by the somatic theory and network theory, similar to the antigen recognition of the biological immune system, cell differentiation, memory and self-regulating function. If the immune algorithm for solving optimization problems in a general search method, compared to the affinity between antigen, antibody, antigen and antibody correspond to objective function optimization problems, optimal solution, match of the solution with objective function Platform: |
Size: 402432 |
Author:jax |
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Description: 免疫算法是受生物免疫系统的启发而推出的一种新型的智能搜索算法，是一种确定性和随机性选择相结合并具有"勘探"与"开采"能力的启发式随机搜索算法。
算法主要的步骤:
(1)抗原识别与初始抗体产生。
(2)抗体评价
(3)免疫操作
免疫算法的特点:
(1)全局搜索能力
(2)多样性保持机制
(3)鲁棒性强
(4)并行分布式搜索机制(A new intelligent immune algorithm is inspired by the biological immune system and the introduction of the search algorithm is a deterministic and random selection are combined with "heuristic random search algorithm exploration" and "Exploitation" ability.
Main steps of the algorithm:
(1) antigen recognition and initial antibody production.
(2) antibody evaluation
(3) immunization
Characteristics of immune algorithm:
(1) global search capability
(2) diversity retention mechanism
(3) robust
(4) parallel distributed search mechanism) Platform: |
Size: 27648 |
Author:傲视天下
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Description: 免疫算法受生物免疫系统启发，是在免疫学理论基础上发展起来的一种新兴的智能计算算法(Immune algorithm, inspired by biological immune system, is a new intelligent algorithm developed on the basis of immunology theory.) Platform: |
Size: 30720 |
Author:小叶子啦啦啦 |
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Search - immune-inspired algorithm