Introduction: In unsupervised learning, data clustering is essential. However, many current algorithms have issues like early convergence, inadequate local search capabilities, and trouble processing ...

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.

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: The design of efficient antenna arrays is critical for achieving high directivity and low sidelobe levels (SLLs) in modern communication systems, radar applications, and satellites. The ...

This workshop on Engineering Design Optimization using MATLAB® and Python™ addresses the shape optimization of mechanical components for strength. Python ...

Students call it hypocritical. A senior at Northeastern University demanded her tuition back. But instructors say generative A.I. tools make them better at their jobs. By Kashmir Hill In February, ...

Department of Radiation Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ...

Abstract: This paper focuses on the research and application of linear optimization algorithm and grey Wolf optimization algorithm, takes the energy storage system configuration optimization of the ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this work, we describe the development of a new algorithm for the computation of ...