A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） proble...A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.展开更多
针对传统的特征选择算法只专注于特征间的相关性和冗余性而没有考虑特征之间交互作用的问题,提出一种基于交互信息的混合特征选择(hybrid feature selection based on mutual information,MIHFS)算法,该算法以K-最近邻算法的分类准确率...针对传统的特征选择算法只专注于特征间的相关性和冗余性而没有考虑特征之间交互作用的问题,提出一种基于交互信息的混合特征选择(hybrid feature selection based on mutual information,MIHFS)算法,该算法以K-最近邻算法的分类准确率作为衡量所选特征分类性能的评价指标,有效地去除了冗余和不相关的特征,保留了具有交互作用的特征。为了评估该算法的性能,从分类准确率、所选特征数量以及算法稳定性三方面,与最大相关最小冗余、联合互信息等7种特征选择算法在8个数据集上进行了实验比较和分析。实验结果表明:MIHFS算法具有较强的稳定性,不仅有效降低了特征空间的维数,而且在所选特征的分类性能方面明显优于其他特征选择算法。最后将MIHFS算法与灰色关联分析法-逼近理想解的排序技术法相结合并应用到高邮凹陷永安地区戴一段地质评价中,其评价结果准确率为80%,与实际钻探结果基本吻合,具有较高的可靠性,能够有效指导油气地质评价。展开更多
基金supported by the National Natural Science Foundation of China(51375389)
文摘A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.
文摘针对传统的特征选择算法只专注于特征间的相关性和冗余性而没有考虑特征之间交互作用的问题,提出一种基于交互信息的混合特征选择(hybrid feature selection based on mutual information,MIHFS)算法,该算法以K-最近邻算法的分类准确率作为衡量所选特征分类性能的评价指标,有效地去除了冗余和不相关的特征,保留了具有交互作用的特征。为了评估该算法的性能,从分类准确率、所选特征数量以及算法稳定性三方面,与最大相关最小冗余、联合互信息等7种特征选择算法在8个数据集上进行了实验比较和分析。实验结果表明:MIHFS算法具有较强的稳定性,不仅有效降低了特征空间的维数,而且在所选特征的分类性能方面明显优于其他特征选择算法。最后将MIHFS算法与灰色关联分析法-逼近理想解的排序技术法相结合并应用到高邮凹陷永安地区戴一段地质评价中,其评价结果准确率为80%,与实际钻探结果基本吻合,具有较高的可靠性,能够有效指导油气地质评价。
