Bilateral sensitivity analysis: a better understanding of a neural network
A model-independent sensitivity analysis for (deep) neural network, Bilateral sensitivity
analysis (BiSA), is proposed to measure the relationship or dependency between neurons …
analysis (BiSA), is proposed to measure the relationship or dependency between neurons …
Hierarchical feature selection for random projection
Random projection is a popular machine learning algorithm, which can be implemented by
neural networks and trained in a very efficient manner. However, the number of features …
neural networks and trained in a very efficient manner. However, the number of features …
Intelligent control of microgrid with virtual inertia using recurrent probabilistic wavelet fuzzy neural network
A microgrid with virtual inertia using master-slave control is proposed in this article to
overcome the drawbacks of traditional inverter-based distributed generators for lack of …
overcome the drawbacks of traditional inverter-based distributed generators for lack of …
Stacking-and voting-based ensemble deep learning models (SEDL and VEDL) and active learning (AL) for mapping land subsidence
A Mohammadifar, H Gholami, S Golzari - Environmental Science and …, 2023 - Springer
This contribution presents a novel methodology based on the feature selection, ensemble
deep learning (EDL) models, and active learning (AL) approach for prediction of land …
deep learning (EDL) models, and active learning (AL) approach for prediction of land …
A health assessment method with attribute importance modeling for complex systems using belief rule base
Z Lian, ZJ Zhou, CH Hu, J Wang, CC Zhang… - Reliability Engineering & …, 2024 - Elsevier
In the health assessment for complex systems, system attributes refer to the indicators or
components having an impact on the health state of the system. When assessing the health …
components having an impact on the health state of the system. When assessing the health …
Flattening layer pruning in convolutional neural networks
E Jeczmionek, PA Kowalski - Symmetry, 2021 - mdpi.com
The rapid growth of performance in the field of neural networks has also increased their
sizes. Pruning methods are getting more and more attention in order to overcome the …
sizes. Pruning methods are getting more and more attention in order to overcome the …
A method for rockburst prediction in the deep tunnels of hydropower stations based on the monitored microseismicity and an optimized probabilistic neural network …
G Feng, G Xia, B Chen, Y Xiao, R Zhou - Sustainability, 2019 - mdpi.com
Hydropower is one of the most important renewable energy sources. However, the safe
construction of hydropower stations is seriously affected by disasters like rockburst, which, in …
construction of hydropower stations is seriously affected by disasters like rockburst, which, in …
[HTML][HTML] Improving computational efficiency of machine learning modeling of nonlinear processes using sensitivity analysis and active learning
T Zhao, Y Zheng, Z Wu - Digital Chemical Engineering, 2022 - Elsevier
In this work, we develop a model reduction method using sensitivity analysis and active
learning to improve the computational efficiency of machine learning modeling of nonlinear …
learning to improve the computational efficiency of machine learning modeling of nonlinear …
Analog circuit fault diagnosis based on density peaks clustering and dynamic weight probabilistic neural network
J Shi, Y Deng, Z Wang - Neurocomputing, 2020 - Elsevier
Fault diagnosis methods based on probabilistic neural networks (PNNs) have been widely
used in various products, owing to their simplicity and efficiency. However, in some multi …
used in various products, owing to their simplicity and efficiency. However, in some multi …
[HTML][HTML] Architecture reduction of a probabilistic neural network by merging k-means and k-nearest neighbour algorithms
M Kusy, PA Kowalski - Applied Soft Computing, 2022 - Elsevier
Probabilistic neural network (PNN) has a sizable structure since it requires all training
records in the activation of its hidden layer. This fact makes it suffer from the problem of the …
records in the activation of its hidden layer. This fact makes it suffer from the problem of the …