Intelligent Neural Network Optimization with Evolutionary Algorithms is a project aimed at exploring the use of evolutionary algorithms to optimize the performance of neural networks (Conf of weights) ...

Neural networks with memory can benefit from memory-based optimization algorithms, enhancing the accuracy of spiking neural networks. Inspired by simple graphs, graph neural networks have applications ...

Optimize, Evolve, Excel! 🧠🔧 I'd explain that optimization in machine learning involves refining algorithms to improve performance. Neural network optimization is distinct as it deals with ...

Gray Wolf Optimization (GWO), Imperialist Competitive Algorithm (ICA) and Particle Swarm Optimization (PSO) are used to improve the weights achieved by a Neural Network trained with Gradient Descent ...

Methods: In this paper, a radial basis function neural network (RBFNN) based on an improved black widow optimization algorithm (IBWO) has been developed, which is called the IBWO-RBF model. In order ...

The original neural network optimization algorithm (NNA) faces issues like weak global search capability, susceptibility to local optima in the later optimization stages, and inadequate convergence ...

Keywords: nuclear reactor, optimization, fast neutron source, convolutional neural networks, surrogate model, machine learning. Citation: Pevey J, Sobes V and Hines WJ (2022) Neural Network ...

Trajectory optimization has recently been addressed to compute energy-efficient routes for ornithopter navigation, but its online application remains a challenge. To overcome the high computation time ...