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Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning
(
Elsevier Ltd
, 2023 , Article)
The reliable control of wave energy devices highly relies on the forecasts of wave heights. However, the dynamic characteristics and significant fluctuation of waves’ historical data pose challenges to precise predictions. ...
Dynamic ensemble deep echo state network for significant wave height forecasting
(
Elsevier Ltd
, 2023 , Article)
Forecasts of the wave heights can assist in the data-driven control of wave energy systems. However, the dynamic properties and extreme fluctuations of the historical observations pose challenges to the construction of ...
Data-driven fault detection and isolation of nonlinear systems using deep learning for Koopman operator
(
ISA - Instrumentation, Systems, and Automation Society
, 2023 , Article)
This paper proposes a data-driven actuator fault detection and isolation approach for the general class of nonlinear systems. The proposed method uses a deep neural network architecture to obtain an invariant set of basis ...
DSPNet: A Self-ONN Model for Robust DSPN Diagnosis From Temperature Maps
(
Institute of Electrical and Electronics Engineers Inc.
, 2023 , Article)
Diabetic sensorimotor polyneuropathy (DSPN) leads to pain, diabetic foot ulceration (DFU), amputation, and death. The diagnosis of advanced DSPN to identify those at risk is key to preventing DFU and amputation. Alterations ...
Deep learning-based middle cerebral artery blood flow abnormality detection using flow velocity waveform derived from transcranial Doppler ultrasound
(
Elsevier
, 2023 , Article)
Since the brain is unlike any other organ in that it cannot store energy and has a high metabolic demand, constant blood flow is essential for healthy brain function. The maximum flow velocity waveform that is produced by ...
NDDNet: a deep learning model for predicting neurodegenerative diseases from gait pattern
(
Springer Nature
, 2023 , Article)
Neurodegenerative diseases damage neuromuscular tissues and deteriorate motor neurons which affects the motor capacity of the patient. Particularly the walking gait is greatly influenced by the deterioration process. Early ...
Employing machine learning techniques in monitoring autocorrelated profiles
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
In profile monitoring, it is usually assumed that the observations between or within each profile are independent of each other. However, this assumption is often violated in manufacturing practice, and it is of utmost ...
Deep Learning-Based Conjunctival Melanoma Detection Using Ocular Surface Images
(
springer link
, 2023 , Article)
The human eye could be affected with conjunctival melanoma, which indicates a fatal malignant growth of the eye. Being a very rare disease, there exists a lack of related data in the literature. Also, very few studies ...
RamanNet: a generalized neural network architecture for Raman spectrum analysis
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
Raman spectroscopy provides a vibrational profile of the molecules and thus can be used to uniquely identify different kinds of materials. This sort of molecule fingerprinting has thus led to the widespread application of ...
BIO-CXRNET: a robust multimodal stacking machine learning technique for mortality risk prediction of COVID-19 patients using chest X-ray images and clinical data
(
Springer Science and Business Media Deutschland GmbH
, 2023 , Article)
Nowadays, quick, and accurate diagnosis of COVID-19 is a pressing need. This study presents a multimodal system to meet this need. The presented system employs a machine learning module that learns the required knowledge ...