Tag: Cluster Computing

A newly published two-stage deep network called FADFNet uses parallel feature extraction, source-image compensation, and a decomposition feedback loop to ...

Every second, billions of events flow through the data pipelines behind fraud detection systems, traffic analytics platforms, and industrial monitoring ...

A French research team has combined time-domain reflectometry with temporal convolutional networks to detect, locate, and characterize wiring faults, achieving ...

Reinforcement learning and swarm intelligence combine to let cloud systems re-provision resources on the fly as workflows change mid-execution, outperforming ...

Researchers have developed a new fuzzy multi-criteria group decision-making framework that combines a novel score function, partitioned Maclaurin symmetric mean ...

A new convolutional architecture called MRTFNet combines multi-resolution temporal embeddings with frequency-domain modeling to outperform Transformer-based models on most long-term ...

A new two-stage differential evolution algorithm that borrows the foraging behavior of squirrels outperforms leading optimization methods on standard benchmarks ...

Researchers have developed a self-tuning zeroing neural network with a dynamic adaptive gain and integral activation function that lets multi-agent ...

Researchers in China have developed GSCMO, a dual-population evolutionary algorithm that uses entropy and neighborhood information to guide solution generation ...

Researchers in Seoul have rebuilt the classic extreme studentized deviate test into an online, self-tuning algorithm that detects anomalies in ...