... performances. In addition, several neural network (NN) structures for MFS modeling have been introduced, benefiting from recent developments in deep learning research. However, existing multi-fidelity (MF) NNs have been developed assuming identical sets of input variables for LF and HF data, a condition...

... are then used to train neural networks capable of predicting these grasp forces. Finally, the grasp strength and pullout resistance of the fingers are experimentally measured, and experimental results are shown to be in good accordance with the FEA and neural network models. As will also be shown...

...Christopher S. Mabey; Erin E. Peiffer; Nordica MacCarty; Christopher A. Mattson This paper presents a methodology for predicting a product’s adoption and social impact using agent-based modeling (ABM) and neural networks to aid in decision-making related to the design and implementation...

... sentiment analysis of IBM Watson. Finally, the importance of the identified attributes is estimated by evaluating the effect of sentiments of each product attribute on the overall rating using an explainable deep neural network. A Shapley additive explanation-based method is proposed to estimate...