Results 21 to 30 of about 92,198 (268)

The Machine Learning-Based Dropout Early Warning System for Improving the Performance of Dropout Prediction

open access: yesApplied Sciences, 2019
A dropout early warning system enables schools to preemptively identify students who are at risk of dropping out of school, to promptly react to them, and eventually to help potential dropout students to continue their learning for a better future ...
Sunbok Lee, Jae Young Chung
doaj   +1 more source

AE-CGAN Model based High Performance Network Intrusion Detection System

open access: yesApplied Sciences, 2019
In this paper, a high-performance network intrusion detection system based on deep learning is proposed for situations in which there are significant imbalances between normal and abnormal traffic.
JooHwa Lee, KeeHyun Park
doaj   +1 more source

Credibility Based Imbalance Boosting Method for Software Defect Proneness Prediction

open access: yesApplied Sciences, 2020
Imbalanced data are a major factor for degrading the performance of software defect models. Software defect dataset is imbalanced in nature, i.e., the number of non-defect-prone modules is far more than that of defect-prone ones, which results in the ...
Haonan Tong, Shihai Wang, Guangling Li
doaj   +1 more source

Source signature processing in deep water, Gulf of Mexico: comparison between deterministic deconvolution and phase conjugation

open access: yesAnnals of Geophysics, 2000
The Center for Marine Resources and Environmental Technology has been developing a new method to improve the resolution of high-resolution seismic profiling.
C. R. Partouche
doaj   +1 more source

Oversampling Method on Classifying Hypertension Using Naive Bayes, Decision Tree, and Artificial Neural Network

open access: yesJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2020
Oversampling is a technique to balance the number of data records for each class by generating data with a small number of records in a class, so that the amount is balanced with data with a class with a large number of records.
Nurul Chamidah   +2 more
doaj   +1 more source

Imbalanced Data Classification Method Based on LSSASMOTE

open access: yesIEEE Access, 2023
Imbalanced data exist extensively in the real world, and the classification of imbalanced data is a hot topic in machine learning. In order to classify imbalanced data more effectively, an oversampling method named LSSASMOTE is proposed in this paper ...
Zhi Wang, Qicheng Liu
doaj   +1 more source

Equalization with oversampling in multiuser CDMA systems [PDF]

open access: yes, 2004
Some of the major challenges in the design of new-generation wireless mobile systems are the suppression of multiuser interference (MUI) and inter-symbol interference (ISI) within a single user created by the multipath propagation. Both of these problems
Vaidyanathan, P. P., Vrcelj, Bojan
core   +3 more sources

Oversampling generates super-wavelets [PDF]

open access: yesProceedings of the American Mathematical Society, 2007
We show that the second oversampling theorem for affine systems generates super-wavelets. These are frames generated by an affine structure on the space L 2 ( R d
Dutkay, Dorin Ervin, Jorgensen, Palle
openaire   +3 more sources

Optimasi MWMOTE pada data tidak seimbang menggunakan complete linkage

open access: yesJurnal Teknologi dan Sistem Komputer, 2021
Data yang tidak seimbang dapat menyebabkan kesalahan klasifikasi, menurunkan kinerja dan akurasi. Pengelompokan pada MWMOTE dapat dioptimalkan untuk meningkatkan kinerja pembangkitan data sintetis menjadi representatif serta meningkatkan kinerja MWMOTE ...
Meida Cahyo Untoro
doaj   +1 more source

Joint optimization of transceivers with fractionally spaced equalizers [PDF]

open access: yes, 2008
In this paper we propose a method for joint optimization of transceivers with fractionally spaced equalization (FSE). We use the effective single-input multiple-output (SIMO) model for the fractionally spaced receiver.
Vaidyanathan, P. P., Weng, Ching-Chih
core   +1 more source

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