ID 原文 译文
49517 提出了一种基于模糊双门限的地波雷达与船只身份自动识别系统(automatic identification system，AIS)目标航迹关联方法， A ground wave radar based on fuzzy double threshold identity with the ship automatic identification system (automatic identification system, AIS) of target correlation method,
49518 该方法主要是利用模糊隶属度来描述两条航迹间的关联程度，并通过双门限检测来确定关联的航迹对。 this method is mainly by using fuzzy membership degree to describe the degree of correlation between two tracks, and through the double threshold detection to determine the associated track.
49519 具体讨论分析了算法中展度、权重、调整因子等参数的选取原则，最后利用2011年10月31和2013年9月6日获取的两批实测地波雷达与AIS数据将本文方法与最近邻航迹关联算法做了对比， Specific discussion brought the degree of the algorithm is analyzed, weight, adjusting factor selection of parameters, such as the principle, the final use of October 31, 2011 and September 6, 2013 to obtain two batch of measured ground wave radar and AIS data to the method and made a comparison of nearest neighbor correlation algorithm,
49520 结果表明，此方法的关联率高于最近邻航迹关联算法，并且在航迹较为复杂情况下，提出的航迹关联算法具有更好的稳定性。 the results show that this method of connection rate is higher than of nearest neighbor correlation algorithm, and under the condition of track is more complex, the correlation algorithm has better stability.
49521 首先针对离散二进制粒子群(binary particle swarm optimization，BPSO)容易陷入局部收敛的问题，提出一种改进的BPSO算法。 First on discrete binary particle swarm (binary particle swarm optimization, BPSO) easy to fall into local convergence problem, an improved BPSO algorithm.
49522 在分析高斯密度函数对尺度敏感性的基础上，利用粒子群与全局最优粒子的一致性动态调节尺度参数， On the basis of analyzing the gaussian density function sensitivity to scale, using particle swarm and the consistency of the global optimal particle dynamic adjust the scale parameter,
49523 并利用密度函数对称区间的定积分确定全局最优粒子的变异概率。 and density function symmetry interval of the definite integral is used to determine the global optimal particle mutation probability.
49524 而后将聚类的选择性集成抽象为组合优化问题， And then to integrate the clustering of selective abstraction to combinatorial optimization problems,
49525 利用聚类成员有效性和差异性的加权组合定义适应度并以改进BPSO的进化过程实现聚类的选择性集成。 using clustering validity and difference of the weighted combination members define fitness and to improve the course of the evolution of BPSO realize the selective integration of clustering.
49526 最后基于标准数据集和图像数据集验证算法的有效性。 Based on the standard data and image data sets verify the effectiveness of the algorithm.