Abstract: Support vector machines (SVMs) are successful supervised learning models that analyze data for classification and regression. Previous work has demonstrated the superiority of the SVMs in ...

Sparse identification of nonlinear dynamical systems is an important project, directly addressing the physics community’s long-standing goal of data-driven discovery. Although many effective methods ...

Abstract: The M-ary support vector machine (SVM) is introduced as a nonparameter nonlinear phase noise (NLPN) mitigation approach for the coherent optical systems. The NLPN tolerance of the system can ...

In order to better extract the displacement fault signals inside bearings based on the vibration characteristics of rolling bearings after failure, a two-degree-of-freedom model simplifying the ...

Inertial microfluidics allows for passive, label-free manipulation of particles suspended in a fluid. Physical experiments can understand the underlying mechanisms to an extent whereby inertial ...

Dataset import and preprocessing Automatic feature map generation 27-type feature catalogue for iterative (re)calculation to support model integration into optimization 7 customizable internal model ...

Considering the strong non-linear time-varying behavior of dam deformation, a novel prediction model, called Levy flight-based grey wolf optimizer optimized support vector regression (LGWO-SVR), is ...

There will be homeworks, followed by the final project. Everyone needs to present their work and submit a project report. 1-page Final Project proposal due : just before Spring Break Final Project ...