Comprehensive review on twin support vector machines
Twin support vector machine (TWSVM) and twin support vector regression (TSVR) are newly
emerging efficient machine learning techniques which offer promising solutions for …
emerging efficient machine learning techniques which offer promising solutions for …
Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms
Floods and droughts are environmental phenomena that occur in Peninsular Malaysia due
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …
to extreme values of streamflow (SF). Due to this, the study of SF prediction is highly …
Inverse free reduced universum twin support vector machine for imbalanced data classification
Imbalanced datasets are prominent in real-world problems. In such problems, the data
samples in one class are significantly higher than in the other classes, even though the other …
samples in one class are significantly higher than in the other classes, even though the other …
KNN weighted reduced universum twin SVM for class imbalance learning
In real world problems, imbalance of data samples poses major challenge for the
classification problems as the data samples of a particular class are dominating. Problems …
classification problems as the data samples of a particular class are dominating. Problems …
Predicting suspended sediment load in Peninsular Malaysia using support vector machine and deep learning algorithms
High loads of suspended sediments in rivers are known to cause detrimental effects to
potable water sources, river water quality, irrigation activities, and dam or reservoir …
potable water sources, river water quality, irrigation activities, and dam or reservoir …
Long Short-Term Memory-Based Twin Support Vector Regression for Probabilistic Load Forecasting
Z Zhang, Y Dong, WC Hong - IEEE Transactions on Neural …, 2023 - ieeexplore.ieee.org
A probabilistic load forecast that is accurate and reliable is crucial to not only the efficient
operation of power systems but also to the efficient use of energy resources. In order to …
operation of power systems but also to the efficient use of energy resources. In order to …
EEG signal classification using improved intuitionistic fuzzy twin support vector machines
Support-vector machines (SVMs) have been successfully employed to diagnose
neurological disorders like epilepsy and sleep disorders via electroencephalogram (EEG) …
neurological disorders like epilepsy and sleep disorders via electroencephalogram (EEG) …
Multi-view intuitionistic fuzzy support vector machines with insensitive pinball loss for classification of noisy data
C Lou, X Xie - Neurocomputing, 2023 - Elsevier
Multi-view support vector machines (MvSVMs) have been widely used to solve multi-view
classification problems. However, the conventional MvSVMs often overlook the presence of …
classification problems. However, the conventional MvSVMs often overlook the presence of …
EEG signal classification via pinball universum twin support vector machine
Electroencephalogram (EEG) have been widely used for the diagnosis of neurological
diseases like epilepsy and sleep disorders. Support vector machines (SVMs) are widely …
diseases like epilepsy and sleep disorders. Support vector machines (SVMs) are widely …
Safe intuitionistic fuzzy twin support vector machine for semi-supervised learning
L Bai, X Chen, Z Wang, YH Shao - Applied Soft Computing, 2022 - Elsevier
Learning unlabeled samples without deteriorating performance is a challenge in semi-
supervised learning. In this paper, we propose a safe intuitionistic fuzzy twin support vector …
supervised learning. In this paper, we propose a safe intuitionistic fuzzy twin support vector …