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Abstract: An implementation of justification-based belief maintenance using a Hopfield network has been proposed for relabeling belief graphs during belief ...
Bibliographic details on Justification-based belief maintenance using neural networks.
Oct 7, 2020 · This learning process takes place by running gradient descend algorithm combined with backpropagation algorithm. These enable to calculate the ...
Jan 22, 2019 · Second, it will investigate optimised deep neural networks to predict maintenance measures such as remaining useful life (RUL) and time-to- ...
Mar 31, 2020 · Neural network based Deep Learning methods can analyze images with reasonable accuracy. Three major classes of Deep Learning are: MLP, CNN, and ...
This paper tries to reduce the complexity of the proposed networks by suitable data pre-processing to be able to classify the measured data on the edge platform ...
Missing: Justification- belief
This article presents and justifies the using of ... Software Defect Categorization based on Maintenance Effort and Change Impact using Multinomial Naïve Bayes ...
We propose a framework to integrate data-driven probabilistic RUL prognostics into predictive maintenance planning. We estimate the distribution of RUL using ...
Mar 13, 2024 · Our approach is a computationally efficient XAI method that extracts example-based justifications and uncertainty estimates that can be applied ...
Missing: belief | Show results with:belief
Feb 1, 2021 · The main novelty of this approach is that a separate neural network is trained for each label leading to better results for each case.