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Reservoir Stack Machines [article]

Benjamin Paaßen and Alexander Schulz and Barbara Hammer
2021 arXiv   pre-print
In our experiments, we validate the reservoir stack machine against deep and shallow networks from the literature on three benchmark tasks for Neural Turing machines and six deterministic context-free  ...  Our results show that the reservoir stack machine achieves zero error, even on test sequences longer than the training data, requiring only a few seconds of training time and 100 training sequences.  ...  Then, in Section 3.1, we prove that a reservoir stack machine with a sufficiently rich reservoir can simulate any LR(1)-automaton, while the reservoir memory machine cannot.  ... 
arXiv:2105.01616v1 fatcat:e4xpr6re6vajtmukmec3xrp4oy

Reservoir of diverse adaptive learners and stacking fast hoeffding drift detection methods for evolving data streams

Ali Pesaranghader, Herna Viktor, Eric Paquet
2018 Machine Learning  
We further incorporate two novel stacking-based drift detection methods, namely the FHDDMS and FHDDMS_add approaches.  ...  We introduce the Tornado framework that implements a reservoir of diverse classifiers, together with a variety of drift detection algorithms.  ...  In our current research, we implemented our Tornado framework on a single machine.  ... 
doi:10.1007/s10994-018-5719-z fatcat:lkeartys4nfo3ko7epdwaxlksy

Improving the prediction of petroleum reservoir characterization with a stacked generalization ensemble model of support vector machines

Fatai Anifowose, Jane Labadin, Abdulazeez Abdulraheem
2015 Applied Soft Computing  
Support vector machines (SVM) is one of the promising machine learning tools that have performed excellently well in most prediction problems.  ...  This paper proposes a stacked generalization ensemble model of SVM that incorporates different expert opinions on the optimal values of this parameter in the prediction of porosity and permeability of  ...  Support vector machines (SVM) is one of the promising machine learning tools that have performed excellently well in most prediction problems.  ... 
doi:10.1016/j.asoc.2014.10.017 fatcat:wvbbqdx7wjhb3jgipveioxpwva

Page 58 of Institute of Transportation Engineers. ITE Journal Vol. 23, Issue 2 [page]

1952 Institute of Transportation Engineers. ITE Journal  
of the other stack.  ...  When one stack of Cages ts raised one floor, the adjacent stack is lowered one floor.  ... 

Page 58 of Institute of Transportation Engineers. ITE Journal Vol. 23, Issue 2 [page]

1952 Institute of Transportation Engineers. ITE Journal  
of the other stack.  ...  When one stack of cages is raised one floor, the adjacent stack is lowered one floor.  ... 

A comparative study of heterogeneous ensemble methods for the identification of geological lithofacies

Saurabh Tewari, U. D. Dwivedi
2020 Journal of Petroleum Exploration and Production Technology  
Mudstone reservoirs demand accurate information about subsurface lithofacies for field development and production.  ...  Several data-driven machine learning models have been proposed in the literature to recognize mudstone lithofacies.  ...  Several machine learning models have been proposed to extract the facies information of conventional reservoir using well logs data.  ... 
doi:10.1007/s13202-020-00839-y fatcat:lh7w235d4zdwxmzl35nipzwtyy

Characterization of complex fluvio–deltaic deposits in Northeast China using multi-modal machine learning fusion

Cyril D. Boateng, Li-Yun Fu, Sylvester K. Danuor
2020 Scientific Reports  
First, acoustic-related seismic attributes from post-stack seismic data were used to characterize the reservoirs.  ...  Data analysis involves a bio-integrated framework called multi-modal machine learning fusion (MMMLF) based on neural networks.  ...  Therefore, machine learning data-based tools for predicting reservoir properties are effective.  ... 
doi:10.1038/s41598-020-70382-7 pmid:32770135 fatcat:qyd7rtoyvfhpraymdufllvnccu

A Novel Stacking Heterogeneous Ensemble Model with Hybrid Wrapper-Based Feature Selection for Reservoir Productivity Predictions

Changlin Zhou, Lang Zhou, Fei Liu, Weihua Chen, Qian Wang, Keliang Liang, Wenqiu Guo, Liying Zhou, M. Irfan Uddin
2021 Complexity  
Therefore, this study developed a stacking heterogeneous ensemble model with a hybrid wrapper-based feature selection strategy to forecast reservoir productivity, resolve the overfitting problem, and improve  ...  Acid fracturing is the most important stimulation method in the carbonate reservoir.  ...  regressor (random forest, Gradient boosting tree, and support vector machine) for productivity forecasting of shale reservoirs and validated the performance of their proposed model on the data set with  ... 
doi:10.1155/2021/6675638 fatcat:gneqczmmfngwhovgyom3kmk3la

Unsupervised Machine Learning, Multi-Attribute Analysis for Identifying Low Saturation Gas Reservoirs within the Deepwater Gulf of Mexico, and Offshore Australia

Julian Chenin, Heather Bedle
2022 Geosciences  
To address this problem, an unsupervised machine learning multi-attribute analysis is performed on 3D post-stack seismic data over several blocks within the deepwater Gulf of Mexico and within the Carnarvon  ...  Results reveal that low-saturation gas (LSG) reservoirs can be discriminated from high-saturation gas (HSG) reservoirs by using a combination of instantaneous attributes that are sensitive to small amplitude  ...  Therefore, a new methodology is proposed, which uses unsupervised machine learning multiattribute analysis on 3D, post-stack seismic data with principal component analysis (PCA) and self-organizing maps  ... 
doi:10.3390/geosciences12030132 fatcat:6oaidsl4l5hvvmmdtdghejr6dm

Augmented Virtuality for Coastal Management: A Holistic Use of In Situ and Remote Sensing for Large Scale Definition of Coastal Dynamics

Sandro Bartolini, Alessandro Mecocci, Alessandro Pozzebon, Claudia Zoppetti, Duccio Bertoni, Giovanni Sarti, Andrea Caiti, Riccardo Costanzi, Filippo Catani, Andrea Ciampalini, Sandro Moretti
2018 ISPRS International Journal of Geo-Information  
Stacking Stacking, sometimes called stacked generalization, is an ensemble machine learning method that combines multiple heterogeneous base or component models via a metamodel.  ...  Test: GBM > RF > bagged MARS > Cubist > Stacking (RF) > Stacking (GBM) For machine learning, it is more appropriate to judge ML models' performance by the unseen test data.  ... 
doi:10.3390/ijgi7030092 fatcat:c6acb5fsl5hadbfellaur3toj4

Two Forms of a New Dish-Washing Machine

1900 Scientific American  
The machine is the reservoir. Within the water-reservoir two carrier frames are mounted, the one rotating within the other.  ...  The water-reservoir can be heated in any desired man ner. The inventors claim a speed of more than one dish per second for their power-driven machine. J titutiflt �Ultritau.  ... 
doi:10.1038/scientificamerican02241900-116 fatcat:k2x2sdkv4vairbartdawzxclzq

Implementation of a Microcode-controlled State Machine and Simulator in AVR Microcontrollers (MICoSS)

S. Korbel, V. Jáneš
2005 Acta Polytechnica  
This paper describes the design of a microcode-controlled state machine and its software implementation in Atmel AVR microcontrollers.  ...  This simulator communicates with the designed state machine and presents a complete design environment for microcode development and debugging.  ...  Therefore the depth of the stack memory was enlarged up to 16 items.  ... 
doaj:108c87cc3d89484b918352449fa015c3 fatcat:uhbylznqlndp7embblkbh4xxxy

Page 711 of POWER Vol. 69, Issue 18 [page]

1929 POWER  
One of the fur- nace stacks is shown in the background and machines in the mill, and for the supply of the building heating system.  ...  The lubricating oil is fed to the upper on-side of the bearing at a pressure of 15 lb. gage and is continuously circulated from the oil reservoir to the test journal and back to the oil reservoir.  ... 

A Mechanical Stoker for Furnaces

1900 Scientific American  
The machine is the reservoir. Within the water-reservoir two carrier frames are mounted, the one rotating within the other.  ...  The water-reservoir can be heated in any desired man ner. The inventors claim a speed of more than one dish per second for their power-driven machine. J titutiflt �Ultritau.  ... 
doi:10.1038/scientificamerican02241900-116b fatcat:xwiuexiy2ngfdbhoapin2kycsm

A World's Record in Bridge Building

1900 Scientific American  
The machine is the reservoir. Within the water-reservoir two carrier frames are mounted, the one rotating within the other.  ...  The water-reservoir can be heated in any desired man ner. The inventors claim a speed of more than one dish per second for their power-driven machine. J titutiflt �Ultritau.  ... 
doi:10.1038/scientificamerican02241900-116a fatcat:fhksmiegffbffanh65gw3alhmm
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