机译:基于遗传的EM算法可提高高斯混合模型在桥梁损伤检测中的鲁棒性
Fed Univ Para, Appl Electromagnetism Lab, R Augusto Correa,Guama 01, BR-66075110 Belem, Para, Brazil;
Univ Lusofona Humanidades & Tecnol, Fac Engn, Campo Grande 376, P-1749024 Lisbon, Portugal;
Fed Univ Para, Appl Electromagnetism Lab, R Augusto Correa,Guama 01, BR-66075110 Belem, Para, Brazil;
Fed Univ Para, Appl Electromagnetism Lab, R Augusto Correa,Guama 01, BR-66075110 Belem, Para, Brazil;
Fed Univ Para, Appl Electromagnetism Lab, R Augusto Correa,Guama 01, BR-66075110 Belem, Para, Brazil;
Fed Univ Para, Appl Electromagnetism Lab, R Augusto Correa,Guama 01, BR-66075110 Belem, Para, Brazil;
Structural health monitoring; Data normalization; Damage detection; Gaussian mixture models; Expectation-maximization algorithm; Genetic algorithms; Operational and environmental conditions;
机译:基于遗传的EM算法学习高斯混合模型
机译:基于高斯建模的冲击声信号处理技术检测损坏的小麦内核和改进的极限习题机算法
机译:基于时间序列的高斯混合模型结构损伤检测算法
机译:使用改进的Hough变换和高斯混合模型进行可靠的车道检测和跟踪
机译:具有改进桁架/桥型结构损伤检测的广义特征溶液的平行Jacobi转化算法
机译:基于自适应特征选择高斯混合模型的局部邻域鲁棒模糊聚类图像分割算法
机译:混合高斯规则纸的自主机器人鲁棒场景变化检测新算法。