Results 101 to 110 of about 3,821,405 (172)

Fault diagnosis method for gearbox systems using OVMD and KLIRVM. [PDF]

Sci Rep
Meng S.
europepmc   +1 more source

Implementasi Metode Relevance Vector Machine Dalam Peringkasan Teks Otomatis

, 2017
Support Vector Machine (SVM) merupakan salah satu metode pembelajaran mesin bersifat supervised yang digunakan untuk proses regresi dan klasifikasi. Support Vector Machine telah banyak diimplementasikan dalam berbagai permasalahan dunia nyata, salah ...
Budiman Eka Putra, Arief
core  

A data driven comparison of hybrid machine learning techniques for soil moisture modeling using remote sensing imagery. [PDF]

Sci Rep
Settu P, Ramaiah M.
europepmc   +1 more source

Time Series Prediction Based on the Relevance Vector Machine with Adaptive Kernels

, 2002
The Relevance Vector Machine (RVM) introduced by Tipping is a probabilistic model similar to the widespread Support Vector Machines (SVM), but where the training takes place in a Bayesian framework, and where predictive distributions of the outputs ...
Joaquin Qui Nonero-c, Joaquin Quiñonero-Candela, Lars Kai Hansen   +2 more
core  

Probabilistic day-ahead forecasting of system-level renewable energy and electricity demand. [PDF]

Nat Commun
Terrén-Serrano G, Deshmukh R, Martínez-Ramón M.   +2 more
europepmc   +1 more source

Research on Remaining Useful Life Prediction of Equipment Based on Digital Twins. [PDF]

Sensors (Basel)
Wu J, Zhou Y, Wang X, Chen C, Ma Y, Zhang C.   +5 more
europepmc   +1 more source

Combined Modelling of Sparse and Dense noise improves Bayesian RVM

, 2014
Using a Bayesian approach, we consider the problem of recovering sparse signals under additive sparse and dense noise. Typically, sparse noise models outliers, impulse bursts or data loss.
Jansson, Magnus, Sundin, Martin, Chatterjee, Saikat   +2 more
core  

An interpretable IGWO-MKRVM model for predicting excavation damaged zone thickness of drift. [PDF]

Sci Rep
Yang R, Zhang G, Ye Y, Wan M.
europepmc   +1 more source

PREDICTION OF 28-DAY COMPRESSIVE STRENGTH OF CONCRETE USING RELEVANCE VECTOR MACHINES (RVM)

, 2013
Early and accurate prediction of the compressive strength of concrete is important in the construction industry. Modeling the compressive strength of concrete to obtain a balance and equality between prediction accuracy, time and uncertainty of the ...
Owusu Twumasi, Jones
core  

Prediction of tablet disintegration time based on formulations properties via artificial intelligence by comparing machine learning models and validation. [PDF]

Sci Rep
Ghazwani M, Hani U.
europepmc   +1 more source