Integrating Elman recurrent neural network with particle swarm optimization algorithms for an improved hybrid training of multidisciplinary datasets
There are several types of neural networks (NNs) that are widely used for data classification
tasks. The supervised learning NN is an advanced network with a training algorithm for …
tasks. The supervised learning NN is an advanced network with a training algorithm for …
A recurrent neural network-based identification of complex nonlinear dynamical systems: a novel structure, stability analysis and a comparative study
For the purpose of identifying nonlinear dynamic systems, a compound recurrent feed-
forward neural network based on the combination of feed-forward neural network (FFNN) …
forward neural network based on the combination of feed-forward neural network (FFNN) …
Application of improved artificial intelligence with runner-root meta-heuristic algorithm for dairy products industry: a case study
As the dairy products have a short consumption period, the accurate prediction of their
demand is very important for the dairy industry. Accordingly, this research specifically …
demand is very important for the dairy industry. Accordingly, this research specifically …
Metaheuristic Techniques Optimised LSTM Network for Improved Weather Prediction
S Mittal, OP Sangwan - 2024 IEEE International Conference on …, 2024 - ieeexplore.ieee.org
Tremendous amount of meteorological data is being generated on a daily basis from a
number of sources such as weather stations, balloons, satellites, sensors etc. Timely …
number of sources such as weather stations, balloons, satellites, sensors etc. Timely …
Improving pre-trained weights through meta-heuristics fine-tuning
Machine Learning algorithms have been extensively researched throughout the last decade,
leading to unprecedented advances in a broad range of applications, such as image …
leading to unprecedented advances in a broad range of applications, such as image …