A review on the role of machine learning in enabling IoT based healthcare applications
The Internet of Things (IoT) is playing a vital role in the rapid automation of the healthcare
sector. The branch of IoT dedicated towards medical science is at times termed as …
sector. The branch of IoT dedicated towards medical science is at times termed as …
Machine learning techniques for chronic kidney disease risk prediction
Chronic kidney disease (CKD) is a condition characterized by progressive loss of kidney
function over time. It describes a clinical entity that causes kidney damage and affects the …
function over time. It describes a clinical entity that causes kidney damage and affects the …
The orb-weaving spider algorithm for training of recurrent neural networks
AS Mikhalev, VS Tynchenko, VA Nelyub, NM Lugovaya… - Symmetry, 2022 - mdpi.com
The quality of operation of neural networks in solving application problems is determined by
the success of the stage of their training. The task of learning neural networks is a complex …
the success of the stage of their training. The task of learning neural networks is a complex …
[HTML][HTML] An approach towards missing data management using improved GRNN-SGTM ensemble method
The paper considers missing data management task in smart systems. The main strategies
of missing data management in handling missing data are analyzed. A prediction method for …
of missing data management in handling missing data are analyzed. A prediction method for …
Significant wave height forecasting using hybrid ensemble deep randomized networks with neurons pruning
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 …
However, the dynamic characteristics and significant fluctuation of waves' historical data …
Multiple linear regression based on coefficients identification using non-iterative SGTM neural-like structure
In the paper, a new method for solving the multiple linear regression task via a linear
polynomial as a constructive formula is proposed. It is based on the use of high-speed …
polynomial as a constructive formula is proposed. It is based on the use of high-speed …
Digitalization, circular economy and environmental sustainability: The application of Artificial Intelligence in the efficient self-management of waste
The great advances produced in the field of artificial intelligence and, more specifically, in
deep learning allow us to classify images automatically with a great margin of reliability. This …
deep learning allow us to classify images automatically with a great margin of reliability. This …
Robust learning-enabled intelligence for the internet of things: A survey from the perspectives of noisy data and adversarial examples
Y Wu - IEEE Internet of Things Journal, 2020 - ieeexplore.ieee.org
The Internet of Things (IoT) has been widely adopted in a range of verticals, eg, automation,
health, energy, and manufacturing. Many of the applications in these sectors, such as self …
health, energy, and manufacturing. Many of the applications in these sectors, such as self …
Explainable AI: Using Shapley value to explain complex anomaly detection ML-based systems
Abstract Generally, Artificial Intelligence (AI) algorithms are unable to account for the logic of
each decision they take during the course of arriving at a solution. This “black box” problem …
each decision they take during the course of arriving at a solution. This “black box” problem …
An approach towards missing data recovery within IoT smart system
Today, the fast development of the hardware for the Internet of things systems creates
conditions for the development of IoT based Services of various purposes. The imperfect …
conditions for the development of IoT based Services of various purposes. The imperfect …