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.

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

The challenge takes place from July 11-20 in designated South Florida locations. Participants compete for prizes, including $10,000 for removing the most pythons. Pythons must be killed humanely using ...

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 ...

Abstract: In addition to the support of permanent magnet synchronous machine (PMSM) design theory, the advanced structural optimization methods are needed to achieve PMSMs with high performance and ...

The bleeding edge: In-memory processing is a fascinating concept for a new computer architecture that can compute operations within the system's memory. While hardware accommodating this type of ...

ABSTRACT: In the evolving landscape of artificial intelligence and machine learning, the choice of optimization algorithm can significantly impact the success of model training and the accuracy of ...

I am here to ask a question about the QuantLib wrapper in Python. I would like to use the G2 class to have a Two-additive-factor Gaussian model and I would like to have the discount coupon of this ...

The RICE method has been used for decades to help soft tissue injuries recover, but some experts suggest other methods may be better for your recovery. Our bodies are incredibly resilient, able to ...