This book covers theoretical aspects as well as recent innovative applications of Artificial Neural networks (ANNs) in natural, environmental, biological, social, industrial and automated systems.\nIt presents
An Artificial Neural Network (ANN) is defined as a computational model that imitates the functioning of biological neurons. It consists of input, hidden, and output layers, processing molecular information to produce biological activity or properties as output. ...
State of charge estimation for a group of lithium-ion batteries using long short-term memory neural network 2022, Journal of Energy Storage Show abstract Investigation on the co-pyrolysis of agricultural waste and high-density polyethylene using TG-FTIR and artificial neural network modelling 2022, ...
Augmented realityArtificial neural networkModellingSimulationCloud servicesThe digitalization of industry is targeting at the integration of artificial intelligence (AI) in manufacturing systems, for delivering intelligent machinery. Although AI seems a long-term target, similar enabling technologies such as ...
gradient-domain machine-learning model31, or the artificial neural network (NN) approach13,14,15,16,17,18,32,33,34,35,36,37,38. If properly trained, a ML potential can predict the system energy with a nearly DFT accuracy (a few meV/atom). ML potentials are not specific to a particu...
that span scientific, technological and clinical aspects in their interdisciplinary research [41,42,43,44,45]. Different keywords were used to perform the search [46,47,48,49,50]. Primary keywords include ‘structural equation modelling’ and ‘artificial neural network’, as described in Fig.1...
6d). One possible solution would be to try to use the recent progress in generative modelling with deep neural networks36,37,38 to improve the quality of the generator. Although this approach might work to certain extent, an issue is that incrementally training high-quality generative models is...
44、control Underwater robot control,04/09/2020,Artificial Neural Networks - I,62,ANN Function Modelling,ANN as universal function approximator Dynamic system modelling Learning capability Data driven Non-linear mapping Generalisation capability Handle and filter large input data Reconstruct noisy and i...
2025-09-09 会议地点: Kaunas, Lithuania 届数: 34 CCF:cCORE:bQUALIS:b1浏览:125971关注:293参加:90 征稿 We invite prospective authors to submit original and innovative papers in the following areas: AI and Machine Learning: Theory and Foundations of Neural Networks, Novel Neural Network Architecture...
1.Multilayer feedforward networks and backpropagation 2.Training of feedforward neural networks 3.Generalization 4. Bayesian learning of neural networks 5. Recurrent neural networks 6. Unsupervised learning 7. Nonlinear modelling and control 8.Support vector machines 9.Deep learning...