This paper proposes a negative selection with neighborhood representation named as neighborhood negative selection algorithm.This algorithm employs a new representation method which uses the fully adjacent but mutuall...This paper proposes a negative selection with neighborhood representation named as neighborhood negative selection algorithm.This algorithm employs a new representation method which uses the fully adjacent but mutually disjoint neighborhoods to present the self samples and detectors.After normalizing the normal samples into neighborhood shape space,the algorithm uses a special matching rule similar as Hamming distance to train mature detectors at the training stage and detect anomaly at the detection stage.The neighborhood negative selection algorithm is tested using KDD CUP 1999 dataset.Experimental results show that the algorithm can prevent the negative effect of the dimension of shape space,and provide a more accuracy and stable detection performance.展开更多
为提高局部约束线性编码(locality-constrained linear coding,LLC)的效率,提出一种结合邻居匹配策略改进的LLC方法。依据输入向量的空间相关性,在采用LLC方法计算输入向量的近邻码值矩阵之前,计算输入向量与空间相邻的已编码输入向量...为提高局部约束线性编码(locality-constrained linear coding,LLC)的效率,提出一种结合邻居匹配策略改进的LLC方法。依据输入向量的空间相关性,在采用LLC方法计算输入向量的近邻码值矩阵之前,计算输入向量与空间相邻的已编码输入向量之间的欧氏距离,用其推断输入向量与码本中所有码值之间欧氏距离的上下边界,依据距离下边界判决条件跳过部分码值与输入向量的距离计算,依据距离上边界快速求解输入向量的近似近邻码值矩阵,依据LLC方法进行向量编码。图像分类实验结果表明,该方法的分类正确率高,编码耗时少。展开更多
针对现存应急预案大都是文本形式预案,用于处理突发事件时指导性不强、指导作用不明显,提出基于案例推理(case based reasoning,CBR)与基于规则推理(rule based reasoning,RBR)相结合的方法。采用RBR方法,推理得出需要的应急预案,运用CB...针对现存应急预案大都是文本形式预案,用于处理突发事件时指导性不强、指导作用不明显,提出基于案例推理(case based reasoning,CBR)与基于规则推理(rule based reasoning,RBR)相结合的方法。采用RBR方法,推理得出需要的应急预案,运用CBR方法,使用最近邻匹配方法从案例库中查找符合给定相似度的案例,并将2种方法相结合。结果表明:该方法能克服单独使用CBR时面临的无规则预案生成陷入困境及单独使用RBR时预案生成延时及规则建立难度大的瓶颈,兼容RBR极强的推理演绎能力和CBR建立与维护系统容易的优势,使生成应急预案更加高效可靠。展开更多
基金Sponsored by the National Natural Science Foundation of China (Grant No. 60671049)the Subject Chief Foundation of Harbin (Grant No.2003AFXXJ013)+1 种基金the Education Department Research Foundation of Heilongjiang Province(Grant No. 10541044 and 1151G012)the Postdoctoral Science-research Developmental Foundation of Heilongjiang Province(Grant No. LBH-Q09075)
文摘This paper proposes a negative selection with neighborhood representation named as neighborhood negative selection algorithm.This algorithm employs a new representation method which uses the fully adjacent but mutually disjoint neighborhoods to present the self samples and detectors.After normalizing the normal samples into neighborhood shape space,the algorithm uses a special matching rule similar as Hamming distance to train mature detectors at the training stage and detect anomaly at the detection stage.The neighborhood negative selection algorithm is tested using KDD CUP 1999 dataset.Experimental results show that the algorithm can prevent the negative effect of the dimension of shape space,and provide a more accuracy and stable detection performance.
文摘为提高局部约束线性编码(locality-constrained linear coding,LLC)的效率,提出一种结合邻居匹配策略改进的LLC方法。依据输入向量的空间相关性,在采用LLC方法计算输入向量的近邻码值矩阵之前,计算输入向量与空间相邻的已编码输入向量之间的欧氏距离,用其推断输入向量与码本中所有码值之间欧氏距离的上下边界,依据距离下边界判决条件跳过部分码值与输入向量的距离计算,依据距离上边界快速求解输入向量的近似近邻码值矩阵,依据LLC方法进行向量编码。图像分类实验结果表明,该方法的分类正确率高,编码耗时少。
文摘针对现存应急预案大都是文本形式预案,用于处理突发事件时指导性不强、指导作用不明显,提出基于案例推理(case based reasoning,CBR)与基于规则推理(rule based reasoning,RBR)相结合的方法。采用RBR方法,推理得出需要的应急预案,运用CBR方法,使用最近邻匹配方法从案例库中查找符合给定相似度的案例,并将2种方法相结合。结果表明:该方法能克服单独使用CBR时面临的无规则预案生成陷入困境及单独使用RBR时预案生成延时及规则建立难度大的瓶颈,兼容RBR极强的推理演绎能力和CBR建立与维护系统容易的优势,使生成应急预案更加高效可靠。
