Next Article in Journal
Embedded Palmprint Recognition System Using OMAP 3530
Next Article in Special Issue
AURP: An AUV-Aided Underwater Routing Protocol for Underwater Acoustic Sensor Networks
Previous Article in Journal
An Aluminum Microfluidic Chip Fabrication Using a Convenient Micromilling Process for Fluorescent Poly(DL-lactide-co-glycolide) Microparticle Generation
Previous Article in Special Issue
Use of a Real-Time Remote Monitoring Network (RTRM) to Characterize the Guadalquivir Estuary (Spain)
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sensors
Volume 12
Issue 2
10.3390/s120201468
sensors-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Performance Study of the Application of Artificial Neural Networks to the Completion and Prediction of Data Retrieved by Underwater Sensors

by
Carlos Baladrón
1,*,
Javier M. Aguiar
1,
Lorena Calavia
1,
Belén Carro
1,
Antonio Sánchez-Esguevillas
1 and
Luis Hernández
2
1
Universidad de Valladolid, Dpto. TSyCeIT, ETSIT, Paseo de Belén 15, 47011 Valladolid, Spain
2
CIEMAT, Autovía de Navarra A15, salida 56, Lubia, 42290 Soria, Spain
*
Author to whom correspondence should be addressed.
Sensors 2012, 12(2), 1468-1481; https://doi.org/10.3390/s120201468
Submission received: 27 December 2011 / Revised: 23 January 2012 / Accepted: 30 January 2012 / Published: 2 February 2012
(This article belongs to the Special Issue Underwater Sensor Nodes and Underwater Sensor Networks)
Browse Figures
Versions Notes

Abstract

This paper presents a proposal for an Artificial Neural Network (ANN)-based architecture for completion and prediction of data retrieved by underwater sensors. Due to the specific conditions under which these sensors operate, it is not uncommon for them to fail, and maintenance operations are difficult and costly. Therefore, completion and prediction of the missing data can greatly improve the quality of the underwater datasets. A performance study using real data is presented to validate the approach, concluding that the proposed architecture is able to provide very low errors. The numbers show as well that the solution is especially suitable for cases where large portions of data are missing, while in situations where the missing values are isolated the improvement over other simple interpolation methods is limited.
Keywords: artificial intelligence; artificial neural networks; data completion; data prediction; underwater sensors artificial intelligence; artificial neural networks; data completion; data prediction; underwater sensors

Share and Cite

MDPI and ACS Style

Baladrón, C.; Aguiar, J.M.; Calavia, L.; Carro, B.; Sánchez-Esguevillas, A.; Hernández, L. Performance Study of the Application of Artificial Neural Networks to the Completion and Prediction of Data Retrieved by Underwater Sensors. Sensors 2012, 12, 1468-1481. https://doi.org/10.3390/s120201468

AMA Style

Baladrón C, Aguiar JM, Calavia L, Carro B, Sánchez-Esguevillas A, Hernández L. Performance Study of the Application of Artificial Neural Networks to the Completion and Prediction of Data Retrieved by Underwater Sensors. Sensors. 2012; 12(2):1468-1481. https://doi.org/10.3390/s120201468

Chicago/Turabian Style

Baladrón, Carlos, Javier M. Aguiar, Lorena Calavia, Belén Carro, Antonio Sánchez-Esguevillas, and Luis Hernández. 2012. "Performance Study of the Application of Artificial Neural Networks to the Completion and Prediction of Data Retrieved by Underwater Sensors" Sensors 12, no. 2: 1468-1481. https://doi.org/10.3390/s120201468

APA Style

Baladrón, C., Aguiar, J. M., Calavia, L., Carro, B., Sánchez-Esguevillas, A., & Hernández, L. (2012). Performance Study of the Application of Artificial Neural Networks to the Completion and Prediction of Data Retrieved by Underwater Sensors. Sensors, 12(2), 1468-1481. https://doi.org/10.3390/s120201468

Article Metrics

Back to TopTop