A new technique for highly efficient sensor-less control of electric vehicles by using neural networks

2002 ◽  
Author(s):  
B. Asaii ◽  
D.F. Gosden ◽  
S. Sathiakumar
Keyword(s):  
Neural Networks ◽  
Electric Vehicles ◽  
New Technique ◽  
Highly Efficient ◽  
A New Technique

TUNING DIVERSITY IN BAGGED ENSEMBLES

2000 ◽  
Vol 10 (04) ◽  
pp. 267-279 ◽  
Author(s):  
JOHN G. CARNEY ◽  
PÁDRAIG CUNNINGHAM
Keyword(s):  
Neural Networks ◽  
New Technique ◽  
Data Sets ◽  
Generalization Performance ◽  
A New Technique

In this paper, we investigate how the level of diversity amongst individual neural networks in a bagged ensemble can significantly influence overall ensemble generalization performance. We propose a new technique that tunes this diversity so that ensemble generalization performance is optimized and evaluate its performance on benchmark regression data-sets.

A NEW TECHNIQUE TO PREDICT THE FRACTURES DIP USING ARTIFICIAL NEURAL NETWORKS AND IMAGE LOGS DATA

2015 ◽  
Vol 75 (11) ◽  
Author(s):  
Mostafa Alizadeh ◽  
Zohreh Movahed ◽  
Radzuan Junin ◽  
Rahmat Mohsin ◽  
Mehdi Alizadeh ◽  
...  
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Oil And Gas ◽  
Back Propagation ◽  
Learning Rule ◽  
The Other ◽  
New Technique ◽  
Ann Model ◽  
Artificial Neural ◽  
A New Technique

Fractures provide the place for oil and gas to be reserved and they also can provide the pathway for them to move into the well, so having a proper knowledge of them is essential and every year the companies try to improve the existed softwares in this technology. In this work, the new technique is introduced to be added as a new application to the existed softwares such as Petrel and geoframe softwares. The data used in this work are image logs and the other geological logs data of tree wells located in Gachsaran field, wells number GS-A, GS-B and GS-C. The new technique by using the feed-forward artificial neural networks (ANN) with back-propagation learning rule can predict the fracture dip data of the third well using the data from the other 2 wells. The result obtained showed that the ANN model can simulate the relationship between fractures dips in these 3 wells which the multiple R of training and test sets for the ANN model is 0.95099 and 0.912197, respectively.

scholarly journals Imaging a positronium cloud in a 1 Tesla

2019 ◽  
Vol 198 ◽  
pp. 00004 ◽  
Author(s):  
Antoine Camper ◽  
Stefano Aghion ◽  
Claude Amsler ◽  
Massimiliano Antonello ◽  
Alexander Belov ◽  
...  
Keyword(s):  
Charge Exchange ◽  
New Technique ◽  
Doppler Velocimetry ◽  
Highly Efficient ◽  
Laser Manipulation ◽  
Recent Developments ◽  
Antihydrogen Production ◽  
A New Technique

We report on recent developments in positronium work in the frame of antihydrogen production through charge exchange in the AEgIS collaboration [1]. In particular, we present a new technique based on spatially imaging a cloud of positronium by collecting the positrons emitted by photoionization. This background free diagnostic proves to be highly efficient and opens up new opportunities for spectroscopy on antimatter, control and laser manipulation of positronium clouds as well as Doppler velocimetry.

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