With the rapid advancement of digital transformation, enterprises face escalating challenges in cloud resource allocation due to dynamic workloads and substantial capital investments. Existing ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

Abstract: Uncovering the direct causal relationships between decision variables and optimization objectives can significantly simplify the complexity of optimization problems. However, most existing ...

Introduction: Effective energy management for optimizing energy and speed allocation for athletes in road cycling individual time trials is crucial due to the race’s long distances. Existing ...

In this video, we implement the Adam optimization algorithm from scratch using pure Python. You'll learn how Adam combines the benefits of momentum and RMSProp, and how it updates weights efficiently ...

ABSTRACT: Manual timetable preparation in colleges and universities is often time-consuming, error-prone, and inefficient, especially with increasing student and course complexity. This paper proposes ...

Department of Software Engineering, Faculty of Architecture and Engineering, Rauf Denktas University, Mersin, Türkiye. Manual timetable preparation in colleges and universities is often time-consuming ...

Aqarios' platform Luna v1.0 marks a major milestone in quantum optimization. This release significantly improves usability, performance, and real-world applicability by introducing FlexQAOA, a hybrid ...

What if you could choose your child’s future health and lifespan—before they were even born? A U.S.-based biotech company claims to have developed the world’s first genetic optimization software that ...