Multi-Objective Particle Swarm Optimization (MOPSO) and the Multi-Objective Covariance Matrix Adaptation Evolution Strategy (MO-CMA-ES) apply swarm intelligence and probabilistic modeling, ...

Continuous Learning for Smarter Workflow Optimization Claude Flow’s intelligent agents are powered by advanced neural network algorithms, allowing them to learn and improve over time.

APSO-CNN uses the global search capabilities of Particle Swarm Optimization (PSO) to automatically optimize hyperparameter configurations for architecture-determined Convolutional Neural Networks ...

Kennedy, J. and Eberhart, R. (1995) Particle Swarm Optimization. Proceedings of ICNN95International Conference on Neural Networks, Perth, 27 November-1 December 1995, 1942-1948.

Humans are better than current AI models at interpreting social interactions and understanding social dynamics in moving scenes. Researchers believe this is because AI neural networks were ...

Delaware-based TheStage AI is changing this paradigm with their innovative approach to neural network optimization. The startup recently announced a $4.5 million funding round to commercialize ...

Artificial neurons organize themselves A research team constructs network of self-learning infomorphic neurons Date: March 28, 2025 Source: Max Planck Institute for Dynamics and Self-Organization ...

Critical heat flux (CHF) denotes the thermal limit at which a phase change occurs during heating, that causes a significant decline in heat transfer efficiency and eventual localized overheating of ...

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

To validate the performance of the HS-SBOA algorithm, it was applied to the CEC2021 benchmark function set and three practical engineering problems, and compared with other optimization algorithms ...