Extreme Learning Machine for Reservoir Parameter Estimation in Heterogeneous Reservoir

2015 ◽  
pp. 199-208 ◽  
Author(s):  
Jianhua Cao ◽  
Jucheng Yang ◽  
Yan Wang
Keyword(s):  
Parameter Estimation ◽  
Extreme Learning Machine ◽  
Heterogeneous Reservoir ◽  
Learning Machine ◽  
Reservoir Parameter

scholarly journals Extreme Learning Machine for Reservoir Parameter Estimation in Heterogeneous Sandstone Reservoir

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Jianhua Cao ◽  
Jucheng Yang ◽  
Yan Wang ◽  
Dan Wang ◽  
Yancui Shi
Keyword(s):  
Parameter Estimation ◽  
Extreme Learning Machine ◽  
Back Propagation ◽  
Support Vector ◽  
Core Data ◽  
Porosity And Permeability ◽  
Sandstone Reservoir ◽  
Learning Machine ◽  
Reservoir Parameter ◽  
Propagation Network

This study focuses on reservoir parameter estimation using extreme learning machine in heterogeneous sandstone reservoir. The specific aim of work is to obtain accurate porosity and permeability which has proven to be difficult by conventional petrophysical methods in wells without core data. 4950 samples from 8 wells with core data have been used to train and validate the neural network, and robust ELM algorithm provides fast and accurate prediction results, which is also testified by comparison with BP (back propagation) network and SVM (support vector machine) approaches. The network model is then applied to estimate porosity and permeability for the remaining wells. The predicted attributes match well with the oil test conclusions. Based on the estimations, reservoir porosity and permeability have been mapped and analyzed. Two favorable zones have been suggested for further research in the survey.

scholarly journals Parameter Estimation of Unstable Aircraft using Extreme Learning Machine

2017 ◽  
Vol 67 (6) ◽  
pp. 603 ◽  
Author(s):  
Hari Om Verma ◽  
N. K. Peyada
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Parameter Estimation ◽  
Extreme Learning Machine ◽  
Nonlinear Function ◽  
Estimated Parameters ◽  
Artificial Neural ◽  
Learning Machine ◽  
Nonlinear Function Approximation ◽  
Error Method

<p class="p1">The parameter estimation of unstable aircraft using extreme learning machine method is presented. In the past, conventional methods such as output error method, filter error method, equation error method and non-conventional method such as artificial neural-network based methods have been used for aircraft’s aerodynamic parameter estimation. Nowadays, a trend of finding an accurate nonlinear function approximation is required to represent the aircraft’s equations-of-motion. Such type of nonlinear function approximation is usually achieved using artificial neural-network which is trained with the aircraft input-output flight data using a training algorithm. The accuracy of estimated parameters, which is achieved using the trained network, is highly dependent on the generalisation capability of the network which can be improved using extreme learning machine based network in contrast to artificial neural-network. To estimate the unstable aircraft parameters from the simulated flight data, Gauss-Newton based optimisation method has been used with a predefined aerodynamic model using the trained network. Further, the confidence of the estimated parameters has been shown in comparison to that of the standard parameter estimation methods in terms of the Cramer-Rao bounds.</p>

Performance of Extreme Learning Machine Kernels in Classifying EEG Signal Pattern of Dyslexic Children in Writing

2019 ◽  
Vol 11 (3) ◽  
Author(s):  
A. Z. Ahmad Zainuddin ◽  
◽  
W. Mansor ◽  
Khuan Y. Lee ◽  
Z. Mahmoodin ◽  
...  
Keyword(s):  
Extreme Learning Machine ◽  
Eeg Signal ◽  
Signal Pattern ◽  
Learning Machine

Model selection of extreme learning machine based on latent feature space

2013 ◽  
Vol 33 (6) ◽  
pp. 1600-1603
Author(s):  
Wentao MAO ◽  
Zhongtang ZHAO ◽  
Huanhuan HE
Keyword(s):  
Model Selection ◽  
Extreme Learning Machine ◽  
Feature Space ◽  
Learning Machine ◽  
Selection Of

Sistema Híbrido Baseado Em Extreme Learning Machine E Harmony Search

2016 ◽  
Author(s):  
Edgar Wellington Marques de Almeida ◽  
Mêuser Jorge da Silva Valença
Keyword(s):  
Extreme Learning Machine ◽  
Harmony Search ◽  
Learning Machine
Sign in / Sign up

Export Citation Format

Share Document