Towards paddy rice smart farming: a review on big data, machine learning, and rice production tasks

R Alfred, JH Obit, CPY Chin, H Haviluddin, Y Lim - Ieee Access, 2021 - ieeexplore.ieee.org
Big Data (BD), Machine Learning (ML) and Internet of Things (IoT) are expected to have a
large impact on Smart Farming and involve the whole supply chain, particularly for rice …

Artificial intelligence and machine learning in electronic fetal monitoring

K Barnova, R Martinek, R Vilimkova Kahankova… - … Methods in Engineering, 2024 - Springer
Electronic fetal monitoring is used to evaluate fetal well-being by assessing fetal heart
activity. The signals produced by the fetal heart carry valuable information about fetal health …

A historical account of types of fuzzy sets and their relationships

H Bustince, E Barrenechea, M Pagola… - … on Fuzzy Systems, 2015 - ieeexplore.ieee.org
A Historical Account of Types of Fuzzy Sets and Their Relationships Page 1 IEEE
TRANSACTIONS ON FUZZY SYSTEMS, VOL. 24, NO. 1, FEBRUARY 2016 179 A Historical …

Overlap functions

H Bustince, J Fernandez, R Mesiar, J Montero… - … : Theory, Methods & …, 2010 - Elsevier
In this paper we address a key issue in scenario classification, where classifying concepts
show a natural overlapping. In fact, overlapping needs to be evaluated whenever classes …

A kernel fuzzy c-means clustering-based fuzzy support vector machine algorithm for classification problems with outliers or noises

X Yang, G Zhang, J Lu, J Ma - IEEE Transactions on Fuzzy …, 2010 - ieeexplore.ieee.org
The support vector machine (SVM) has provided higher performance than traditional
learning machines and has been widely applied in real-world classification problems and …

New results on overlap and grouping functions

B Bedregal, GP Dimuro, H Bustince, E Barrenechea - Information Sciences, 2013 - Elsevier
Overlap functions and grouping functions are special kinds of aggregation operators that
have been recently proposed for applications in classification problems, like, eg, imaging …

General overlap functions

L De Miguel, D Gómez, JT Rodríguez, J Montero… - Fuzzy Sets and …, 2019 - Elsevier
As a generalization of bivariate overlap functions, which measure the degree of overlapping
(intersection for non-crisp sets) of n different classes, in this paper we introduce the concept …

Automated identification of normal and diabetes heart rate signals using nonlinear measures

UR Acharya, O Faust, NA Kadri, JS Suri… - Computers in biology and …, 2013 - Elsevier
Diabetes mellitus (DM) affects considerable number of people in the world and the number
of cases is increasing every year. Due to a strong link to the genetic basis of the disease, it is …

Detecting climate signals using explainable AI with single‐forcing large ensembles

ZM Labe, EA Barnes - Journal of Advances in Modeling Earth …, 2021 - Wiley Online Library
It remains difficult to disentangle the relative influences of aerosols and greenhouse gases
on regional surface temperature trends in the context of global climate change. To address …

Depression diagnosis support system based on EEG signal entropies

O Faust, PCA Ang, SD Puthankattil… - Journal of mechanics in …, 2014 - World Scientific
Electroencephalography (EEG) is a measure which represents the functional activity of the
brain. We show that a detailed analysis of EEG measurements provides highly discriminant …