… proposed a novel pseudorandom initialization strategy called the … We have compared the
novel techniques with the basic … that the training of neural networks with the WE-PSO algorithm …

… Input parameters are initialized within the specified range, … different kinds of optimization
techniques such as PSO, EA, CSA, … novel way of solving optimization tasks by the neural network…

… Unfortunately, the training of simple recurrent neural networks is problematic because of …
a new training algorithm based on particle swarm optimization. The algorithm does not use …

… , simulated annealing, tabu search methods, particle swarm optimization, genetic algorithm
… weight optimization and weight initialization techniques for non-iterative training have been …

… This paper introduces a novel PSO-GA based hybrid training … Adam Optimization for training
Artificial Neural Networks. We aim … Since the initialization of the weights may play a decisive …

… In this research, random initialization in used for assigning … of the PSO and backpropagation
as neural networks training … layer perceptron NN as a novel training approach to cover the …

… use of PSO in training artificial neural networks (ANNs), many researchers have castoff this
algorithm as a suitable trainer to train … In this study, the weight vectors are randomly initialized …

… Particle Swarm Optimization (PSO) algorithms have faster convergence and are used to …
for a particle rather than the whole swarm and is not utilized in the initialization phase. As a new …

… a particle swarm optimization (PSO) algorithm with an improved Elman recurrent neural
network (ERNN) to form a PSO-… When initializing the population of the network, the PSO-ERNN …

… ) variant with two-level learning phases to train ANN for image … global best positions), novel
exemplars might be constructed … In this study, a modified initialization scheme incorporated …