针对目前已有多目标威胁评估方法主观性强、稳定性弱、评估过程不连续的问题,综合考虑目标运动特性、目标行为意图,提出了一种基于动态贝叶斯网络(Dynamic Bayesian Network,DBN)和逼近理想解法(Technique for Order Preference by Simi...针对目前已有多目标威胁评估方法主观性强、稳定性弱、评估过程不连续的问题,综合考虑目标运动特性、目标行为意图,提出了一种基于动态贝叶斯网络(Dynamic Bayesian Network,DBN)和逼近理想解法(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)的多目标威胁评估方法DBN-TOPSIS。通过分析目标特征指标间的节点关系,建立多目标威胁评估DBN。采用模糊理论,通过梯形隶属度函数对战场传感器、雷达等获取的连续型特征指标数据进行离散化处理,统一特征指标形态。利用联合树(Junction Tree,J-tree)算法进行动态威胁程度推理。构造DBN推理结果与TOPSIS评估矩阵之间的映射关系,采用TOPSIS法将威胁评估概率结果转换为威胁程度综合评估得分,进行多目标威胁程度准确排序。实验结果表明,DBN-TOPSIS多目标威胁评估方法具有较好的合理性和准确性。展开更多
The theory of poroelasticity is introduced to study the hydraulic properties of the steady uniform turbulent flow in a partially vegetated rectangular channel. Plants are assumed as immovable media. The resistance cau...The theory of poroelasticity is introduced to study the hydraulic properties of the steady uniform turbulent flow in a partially vegetated rectangular channel. Plants are assumed as immovable media. The resistance caused by vegetation is expressed by the theory of poroelasticity. Considering the influence of a secondary flow, the momentum equation can be simplified. The momentum equation is nondimensionalized to obtain a smooth solution for the lateral distribution of the longitudinal velocity. To verify the model, an acoustic Doppler velocimeter （ADV） is used to measure the velocity field in a rectangular open channel partially with emergent artificial rigid vegetation. Comparisons between the measured data and the computed results show that the method can predict the transverse distributions of stream-wise velocities in turbulent flows in a rectangular channel with partial vegetation.展开更多
文摘针对目前已有多目标威胁评估方法主观性强、稳定性弱、评估过程不连续的问题,综合考虑目标运动特性、目标行为意图,提出了一种基于动态贝叶斯网络(Dynamic Bayesian Network,DBN)和逼近理想解法(Technique for Order Preference by Similarity to an Ideal Solution,TOPSIS)的多目标威胁评估方法DBN-TOPSIS。通过分析目标特征指标间的节点关系,建立多目标威胁评估DBN。采用模糊理论,通过梯形隶属度函数对战场传感器、雷达等获取的连续型特征指标数据进行离散化处理,统一特征指标形态。利用联合树(Junction Tree,J-tree)算法进行动态威胁程度推理。构造DBN推理结果与TOPSIS评估矩阵之间的映射关系,采用TOPSIS法将威胁评估概率结果转换为威胁程度综合评估得分,进行多目标威胁程度准确排序。实验结果表明,DBN-TOPSIS多目标威胁评估方法具有较好的合理性和准确性。
基金supported by the National Natural Science Foundation of China (Nos. 10972163 and 51079102)the Fundamental Research Funds for the Central Universities (No. 2104001)
文摘The theory of poroelasticity is introduced to study the hydraulic properties of the steady uniform turbulent flow in a partially vegetated rectangular channel. Plants are assumed as immovable media. The resistance caused by vegetation is expressed by the theory of poroelasticity. Considering the influence of a secondary flow, the momentum equation can be simplified. The momentum equation is nondimensionalized to obtain a smooth solution for the lateral distribution of the longitudinal velocity. To verify the model, an acoustic Doppler velocimeter （ADV） is used to measure the velocity field in a rectangular open channel partially with emergent artificial rigid vegetation. Comparisons between the measured data and the computed results show that the method can predict the transverse distributions of stream-wise velocities in turbulent flows in a rectangular channel with partial vegetation.
