Researchers have developed a quantum particle swarm optimization algorithm for maximum power point tracking that reportedly generates 3.33% more power in higher temperature tests and 0.89% more power ...

Named entity recognition (NER) has been seen as a fundamental component for various natural language processing (NLP) tasks, such as extracting information and answering questions. NER is used to ...

Optimization algorithms seek the best possible solutions to complex problems by iteratively refining candidate solutions. Swarm intelligence techniques draw inspiration from collective behaviours in ...

Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers ...

Researchers demonstrated a quantum algorithmic speedup with the quantum approximate optimization algorithm, laying the groundwork for advancements in telecommunications, financial modeling, materials ...

Researchers have suggested to use a hybrid version of the so-called salp swarm algorithm (SSA) algorithm for maximum power point tracking in PV systems operating under highly fluctuating environmental ...

A quantum computer can solve optimization problems faster than classical supercomputers, a process known as "quantum advantage" and demonstrated by a USC researcher in a paper recently published in ...