and a weighted particle swarm optimization (PSO) algorithm. Trained on real manufacturing data that includes manufacturing variations, the surrogate model better reflects actual fabrication conditions ...

Abstract: The received signal strength (RSS) fingerprint-based technique is extensively utilized for indoor localization, as it does not require time synchronization. However, conventional RSS ...

It’s been difficult to find important questions that quantum computers can answer faster than classical machines, but a new ...

The research team (NEAL) from the University of South China has made significant progress in nuclear reactor radiation-shielding design. The team has developed a radiation-shielding optimization ...

Quantum computing represents an existential threat to modern cryptographic defenses, particularly for non-human identities—machines, IoT devices, workloads, applications, services and APIs—which rely ...

However, our research extends this framework by integrating the predictive model with a particle swarm optimization stage. This second stage identifies the optimal operational parameters that can be ...

This project utilizes Particle Swarm Optimization (PSO) to optimize the parameters of thermal detection systems. The goal is to enhance the detection of thermal patterns, improving the accuracy of ...

This Python module implements hyperparameter optimization using Particle Swarm Optimization (PSO) for various machine learning algorithms in classification task. PSO is a population-based optimization ...