... decomposition is employed to decompose dam deformation data into trend, periodic and random components, significantly reducing time series complexity and enhancing feature extraction. Next, the out-of-bag (OOB) error-based feature selection method from Random Forest identifies the most influential factors...

... with feature selection techniques to perform the first sensor placement optimization (SPO) methodology with variable sensor number. It is applied aiming for the largest amount of information about using the most used modal metrics in the literature and the smallest sensor number at the same time. Findings...

.../approach In this paper, based on the idea of feature selection and cascaded regression, two strategies including Laguerre polynomials and manifolds optimization are proposed to enhance the accuracy of multi-variable regression. Laguerre polynomials were combined with the genetic algorithm to enhance...

...Wenzhong Gao; Xingzong Huang; Mengya Lin; Jing Jia; Zhen Tian Purpose The purpose of this paper is to target on designing a short-term load prediction framework that can accurately predict the cooling load of office buildings. Design/methodology/approach A feature selection scheme and stacking...

... is to propose a method of feature selection based on filter methods combined with hidden Bayesian classifier for improving the efficiency of defect recognition and reduce the complexity of calculation. The method can select the optimal hybrid model for realizing the accurate classification of steel strip...