Abstract: In this study, optimization methods for the design of the compact and broadband adiabatic couplers are presented. Two definitions of an uncoupled waveguide system are introduced: the first ...

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Zelensky makes major concession to ...

ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

Traditional approaches to analytical method optimization (e.g., univariate and “guess-and-check”) can be time-consuming, costly, and often fail to identify true optima within the parameter space.

ABSTRACT: The aim of this research article is to apply topological optimization gradient algorithm applied to 1D and 2D photonic charged slabs. We compute the topological gradient using min max method ...

College of Mechanical and Electronic Engineering, Shanghai Jianqiao University, Shanghai, China Introduction: To enhance energy management in electric vehicles (EVs), this study proposes an ...

Abstract: To address the challenge of collaborative optimization between surface shape accuracy and stiffness of large aperture space mirrors for optical remote sensors, a multiobjective optimization ...

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...

Schug discusses the role of surrogate modelling in chromatographic method development and process optimization. Surrogate modelling is emerging as a powerful tool in chromatographic method development ...