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人工免疫数据挖掘方法的分析与研究展望 总被引:3,自引:2,他引:3
目前,受生物免疫系统启发而产生的人工免疫系统正在兴起,它作为计算智能研究的新领域,提供了一种强大的信息处理和问题求解范式,简要介绍了生物免疫系统的结构和相关机理。对人工免疫系统在数据挖掘方面的应用进行了回顾,分析了近年来AIS在数据挖掘应用领域的研究成果,指出了进一步的研究方向。 相似文献
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目前,受生物免疫系统启发而产生的人工免疫系统(Artifial Immune System,AIS)正在兴起。人工免疫系统是借鉴和利用生物免疫系统(主要是人类的免疫系统)的各种原理、机制和特征而发展的各类信息处理技术、计算技术及其在工程和科学中应用而产生的各种智能系统的统称。生物免疫系统是一种复杂的分布式信息处理系统,具有免疫防护、免疫耐受、免疫记忆功能,且有较强的自适应性、自组织、多样性、学习、识别和记忆等特点,其特点及机理所包含的丰富思想为工程问题的解决提供了新的契机,引起了国内外研究人员的广泛兴趣,它的应用领域也逐渐扩展到模式识别、智能优化、数据挖掘、机器人学、自动控制和故障诊断等诸多领域。 相似文献
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生物免疫系统是一个复杂、并行、鲁棒的自适应系统,以其智能的信息处理能力而逐渐备受关注。为使研究人员能全面了解人工免疫常用算法原理及其应用和免疫系统与其他智能系统的交叉融合研究,以及由此建立的人工免疫系统模型、算法,在简述免疫系统生物学原理的基础上,概括了不同的免疫算法和各自的特性,总结了当前人工免疫系统与人工神经网络、进化算法、模糊系统的集成情况及工程应用现状。最后讨论了人工免疫系统面临的问题及未来发展趋势。 相似文献
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给出了一个入侵免疫系统的结构模型,对目前应用的免疫机制做了简要介绍,在此基础上,对迄今国内外所提出的几种典型的入侵免疫系统模型做了较详尽的描述和分析;提出了影响网络入侵免疫系统的评测因素以及入侵免疫系统今后进一步的研究方向。 相似文献
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免疫细胞是生物免疫系统中的重要成分,它在整个生命周期的演变过程决定了免疫系统的性能。成熟免疫细胞和记忆免疫细胞的相互进化过程,体现出良好的识别、分类作用。通过借鉴免疫细胞的不同进化机理而抽取的聚类算法是一种新的聚类算法,能有效地提取数据的有用信息,表现出了其良好的应用前景。 相似文献
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人工免疫算法及其应用 总被引:18,自引:1,他引:18
阐述了人工免疫系统的基本概念,讨论了几种典型的算法,包括基于免疫系统基本机制的免疫算法、基于免疫特异性的否定选择算法、基于免疫系统克隆选择理论的克隆选择算法、基于接种疫苗及免疫多样性的免疫进化算法、AIS与神经网络混合智能算法和模糊免疫系统等;以年代为序简述了AIS发展历史,介绍了AIS在若干具有代表性的领域中的应用情况。最后通过对AIS的特性和存在问题的分析,展望了今后的研究重点和发展趋势。 相似文献
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基于人类免疫系统的工作原理,提出了一个求解冗余多传感器系统的费用最小化问题的人工免疫算法.该算法采用免疫系统的超变异机制搜索局部区域;采用受体编辑机制跳出局部最小点.本算法比遗传算法和模拟退火算法更适合于解决具有很多局部最小值的冗余传感器系统费用优化的问题,仿真实验结果表明本算法是很有效的. 相似文献
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An immune system inspired clustering and classification method to detect critical areas in electrical power networks 总被引:1,自引:1,他引:0
Identifying critical, failure prone areas in a power system network are often a difficult and computationally intensive task.
Artificial Immune System (AIS) algorithms have been shown to be capable of generalization and learning to identify previously
unseen patterns. In this paper, a method is developed that uses artificial immune system classification and clustering algorithms
to identify critical areas in the network. The algorithm identifies areas of the power system network that are prone to voltage
collapse and areas with overloaded lines. The applicability of AIS for this particular task is demonstrated on test electrical
power system networks. Its accuracy is compared with an optimised support vector machine (SVM) algorithm and k nearest neighbours
algorithm (kNN) across 3 different power system networks. 相似文献
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给出人工免疫与机器人学的四个结合模型:负选择、克隆选择、进化免疫、免疫网络.介绍其生物机理,归纳和评述了主要算法及在机器人中的应用成果. 与其它进化算法做了比较,并展望了进一步的研究方向. 相似文献
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Self-maintenance and engineering immune systems: Towards smarter machines and manufacturing systems 总被引:1,自引:0,他引:1
This paper discusses the state-of-the-art research in the areas of self-maintenance and engineering immune systems (EIS) for machines with smarter adaptability to operating regime changes in future manufacturing systems. Inspired by the biological immune and nervous systems, the authors are introducing the transformation of prognostics and health management (PHM) to engineering immune systems (EIS). First, an overview on PHM is introduced. Its transformation toward resilient systems, self-maintenance systems, and engineering immune systems is also discussed. Finally, new concepts in developing future biological-based smarter machines based on autonomic computing and cloud computing are discussed. 相似文献
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This article reviews the production scheduling problems focusing on those related to flexible job-shop scheduling. Job-shop and flexible job-shop scheduling problems are one of the most frequently encountered and hardest to optimize. This article begins with a review of the job-shop and flexible job-shop scheduling problem, and follow by the literature on artificial immune systems (AIS) and suggests ways them in solving job-shop and flexible job-shop scheduling problems. For the purposes of this study, AIS is defined as a computational system based on metaphors borrowed from the biological immune system. This article also, summarizes the direction of current research and suggests areas that might most profitably be given further scholarly attention. 相似文献
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Hybridization of genetic algorithm with immune system for optimization problems in structural engineering 总被引:1,自引:1,他引:0
Optimization is the task of getting the best solution among the feasible solutions. There are many methods available to obtain
an optimized solution. Genetic algorithm (GA), which is a heuristic type of optimization method, is discussed in this paper.
The focus of the paper is the use of GA for large dimensionality design problems, where computational efficiency is a major
concern. The motivation of this paper is to hybridize GA with an immune system mechanism by avoiding the implementation of
penalty constants, which are highly sensitive to the choice of algorithm parameters. The principal advantage of the immune
system is in its seamless integration with GA-based search for optimal design. It is being hybridized with the immune system
mechanism. The hybrid GA and immune system is applied for the design of the optimal mix of high-performance concrete (HPC),
which is still based on trial mix and for which no rigorous mathematical approach is available. As such, to infer the values
of strength and slump, a wavelet back propagation neural network or wavelet neural network is used for any HPC mix. It is
necessary to minimize the cost of HPC/unit weight of HPC subjected to strength and slump constraints. The interwoven algorithm
is also applied to obtain optimal sectional areas for minimum weight of space trusses subjected to static loading. Formian
programming language is used for the generation of the space trusses, and Feast package is used for the static analysis of
the trusses. In addition to the induction of immune system in the GA for constraint handling, it is being applied in this
particular application for improving the search of GA in obtaining the best optimal solution. For obtaining the optimal sections
of space trusses subjected to earthquake loading, SAP 90 package is used, and reliable results are obtained. 相似文献
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Theoretical advances in artificial immune systems 总被引:2,自引:0,他引:2
Artificial immune systems (AIS) constitute a relatively new area of bio-inspired computing. Biological models of the natural immune system, in particular the theories of clonal selection, immune networks and negative selection, have provided the inspiration for AIS algorithms. Moreover, such algorithms have been successfully employed in a wide variety of different application areas. However, despite these practical successes, until recently there has been a dearth of theory to justify their use. In this paper, the existing theoretical work on AIS is reviewed. After the presentation of a simple example of each of the three main types of AIS algorithm (that is, clonal selection, immune network and negative selection algorithms respectively), details of the theoretical analysis for each of these types are given. Some of the future challenges in this area are also highlighted. 相似文献