[Objective] The study aimed to predict the peak water level in Pearl River Estuary under the background of sea level rise. [Method] The changing trends of peak water level at Denglongshan station and Hengmen station w...[Objective] The study aimed to predict the peak water level in Pearl River Estuary under the background of sea level rise. [Method] The changing trends of peak water level at Denglongshan station and Hengmen station were analyzed firstly on the basis of regression models, and then sea level rise in Pearl River Estuary in 2050 was predicted to estimate the 1-in-50-year peak water level in the same year. [Result] Regression analyses showed that the increasing rate of peak water level over past years was 6.3 mm/a at Denglongshan station and 5.8 mm/a at Hengmen station. In addition, if sea level will rise by 20, 30 and 60 cm respectively in 2050, it was predicted that the 1-in-50-year peak water level will reach 3.04, 3.14 and 3.44 m at Denglongshan station, and 3.19, 3.29 and 3.59 m at Hengmen station separately. [Conclusion] The estimation of peak water level in Pearl River Estuary could provide theoretical references for water resources planning.展开更多
针对在阵列孔径、阵元数目、最小阵元间距等多约束条件下的稀布矩形平面阵列天线优化问题,提出了基于改进型灰狼优化(improved grey wolf optimizer,IGWO)算法和窗函数加权的稀布矩形平面阵列天线综合方法。首先,利用Tent混沌映射、非...针对在阵列孔径、阵元数目、最小阵元间距等多约束条件下的稀布矩形平面阵列天线优化问题,提出了基于改进型灰狼优化(improved grey wolf optimizer,IGWO)算法和窗函数加权的稀布矩形平面阵列天线综合方法。首先,利用Tent混沌映射、非线性收敛因子、优势狼动态置信策略和对立学习策略对灰狼优化(grey wolf optimizer,GWO)算法进行改进,增加算法的种群多样性和跳出局部最优的能力。然后,利用窗函数对阵列单元进行加权,生成位置分布矩阵,减少稀疏矩阵优化时间,提高优化效率。最后,利用位置分布矩阵生成稀疏阵列,再运用IGWO算法进行多约束条件的稀布优化。为验证所提方法的有效性进行了仿真实验,实验结果表明,本文方法可以有效提高阵列天线的性能,降低峰值旁瓣电平,对于解决在多约束条件下的阵列分布问题,具有一定的工程意义和参考价值。展开更多
基金Supported by National Natural Science Foundation of China (50839005)Major State Basic Research Development Program (973 Program)(2010CB428405)+1 种基金Scientific Research Project of Public Welfare Industry of the Ministry of Water Resources,China (201001022)Scientific Research Project of China Water Resources Pearl River Planning Surveying and Designing Co.Ltd.(2012)
文摘[Objective] The study aimed to predict the peak water level in Pearl River Estuary under the background of sea level rise. [Method] The changing trends of peak water level at Denglongshan station and Hengmen station were analyzed firstly on the basis of regression models, and then sea level rise in Pearl River Estuary in 2050 was predicted to estimate the 1-in-50-year peak water level in the same year. [Result] Regression analyses showed that the increasing rate of peak water level over past years was 6.3 mm/a at Denglongshan station and 5.8 mm/a at Hengmen station. In addition, if sea level will rise by 20, 30 and 60 cm respectively in 2050, it was predicted that the 1-in-50-year peak water level will reach 3.04, 3.14 and 3.44 m at Denglongshan station, and 3.19, 3.29 and 3.59 m at Hengmen station separately. [Conclusion] The estimation of peak water level in Pearl River Estuary could provide theoretical references for water resources planning.
文摘针对在阵列孔径、阵元数目、最小阵元间距等多约束条件下的稀布矩形平面阵列天线优化问题,提出了基于改进型灰狼优化(improved grey wolf optimizer,IGWO)算法和窗函数加权的稀布矩形平面阵列天线综合方法。首先,利用Tent混沌映射、非线性收敛因子、优势狼动态置信策略和对立学习策略对灰狼优化(grey wolf optimizer,GWO)算法进行改进,增加算法的种群多样性和跳出局部最优的能力。然后,利用窗函数对阵列单元进行加权,生成位置分布矩阵,减少稀疏矩阵优化时间,提高优化效率。最后,利用位置分布矩阵生成稀疏阵列,再运用IGWO算法进行多约束条件的稀布优化。为验证所提方法的有效性进行了仿真实验,实验结果表明,本文方法可以有效提高阵列天线的性能,降低峰值旁瓣电平,对于解决在多约束条件下的阵列分布问题,具有一定的工程意义和参考价值。
