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Mariela Cerrada-Lozada
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2020 – today
- 2024
- [j40]Fannia Pacheco
, Mariela Cerrada
Threshold-guided multi-objective Generative Adversarial Networks for constructing artificial yet representative driving cycles. Eng. Appl. Artif. Intell. 129: 107665 (2024) - [j39]Rubén Medina
Scale-Fractal Detrended Fluctuation Analysis for Fault Diagnosis of a Centrifugal Pump and a Reciprocating Compressor. Sensors 24(2): 461 (2024) - [j38]René-Vinicio Sánchez
Evaluation of Hand-Crafted Feature Extraction for Fault Diagnosis in Rotating Machinery: A Survey. Sensors 24(16): 5400 (2024) - 2023
- [j37]Diego Cabrera, María J. Quinteros, Mariela Cerrada, René-Vinicio Sánchez, Mario Guallpa, Fernando Sancho, Chuan Li:
Rainfall Forecasting using a Bayesian framework and Long Short-Term Memory Multi-model Estimation based on an hourly meteorological monitoring network. Case of study: Andean Ecuadorian Tropical City. Earth Sci. Informatics 16(2): 1373-1388 (2023) - [j36]Mario Peña, Mariela Cerrada, Rubén Medina
Poincaré Plot Features and Statistical Features From Current and Vibration Signals for Fault Severity Classification of Helical Gear Tooth Breaks. J. Comput. Inf. Sci. Eng. 23(2) (2023) - 2022
- [j35]Fannia Pacheco
Deep Ensemble-Based Classifier for Transfer Learning in Rotating Machinery Fault Diagnosis. IEEE Access 10: 29778-29787 (2022) - [j34]Rodrigo de Paula Monteiro
A hybrid prototype selection-based deep learning approach for anomaly detection in industrial machines. Expert Syst. Appl. 204: 117528 (2022) - [j33]Rubén Medina
Gear and bearing fault classification under different load and speed by using Poincaré plot features and SVM. J. Intell. Manuf. 33(4): 1031-1055 (2022) - 2021
- [j32]Chuan Li
One-Shot Fault Diagnosis of Three-Dimensional Printers Through Improved Feature Space Learning. IEEE Trans. Ind. Electron. 68(9): 8768-8776 (2021) - 2020
- [j31]Diego Cabrera, Adriana Guamán, Shaohui Zhang, Mariela Cerrada
Bayesian approach and time series dimensionality reduction to LSTM-based model-building for fault diagnosis of a reciprocating compressor. Neurocomputing 380: 51-66 (2020) - [j30]Diego Cabrera
Knowledge extraction from deep convolutional neural networks applied to cyclo-stationary time-series classification. Inf. Sci. 524: 1-14 (2020)
2010 – 2019
- 2019
- [j29]Diego Cabrera
Generative Adversarial Networks Selection Approach for Extremely Imbalanced Fault Diagnosis of Reciprocating Machinery. IEEE Access 7: 70643-70653 (2019) - [j28]Rodrigo P. Monteiro
Using a Support Vector Machine Based Decision Stage to Improve the Fault Diagnosis on Gearboxes. Comput. Intell. Neurosci. 2019: 1383752:1-1383752:13 (2019) - [j27]Mariela Cerrada
A hybrid heuristic algorithm for evolving models in simultaneous scenarios of classification and clustering. Knowl. Inf. Syst. 61(2): 755-798 (2019) - [j26]Chuan Li
A Systematic Review of Fuzzy Formalisms for Bearing Fault Diagnosis. IEEE Trans. Fuzzy Syst. 27(7): 1362-1382 (2019) - 2018
- [j25]Mariela Cerrada
A fuzzy transition based approach for fault severity prediction in helical gearboxes. Fuzzy Sets Syst. 337: 52-73 (2018) - [j24]Carlos Ramón Rangel, Junior Altamiranda, Mariela Cerrada
Procedure Based on Semantic Similarity for Merging Ontologies by Non-Redundant Knowledge Enrichment. Int. J. Knowl. Manag. 14(2): 16-36 (2018) - [j23]Mario Peña, Mariela Cerrada
Feature engineering based on ANOVA, cluster validity assessment and KNN for fault diagnosis in bearings. J. Intell. Fuzzy Syst. 34(6): 3451-3462 (2018) - [j22]René-Vinicio Sánchez
Feature ranking for multi-fault diagnosis of rotating machinery by using random forest and KNN. J. Intell. Fuzzy Syst. 34(6): 3463-3473 (2018) - [j21]Chuan Li
A comparison of fuzzy clustering algorithms for bearing fault diagnosis. J. Intell. Fuzzy Syst. 34(6): 3565-3580 (2018) - [j20]Mariela Cerrada
A semi-supervised approach based on evolving clusters for discovering unknown abnormal condition patterns in gearboxes. J. Intell. Fuzzy Syst. 34(6): 3581-3593 (2018) - [j19]Rubén Medina
Gearbox fault classification using dictionary sparse based representations of vibration signals. J. Intell. Fuzzy Syst. 34(6): 3605-3618 (2018) - [j18]Diego Cabrera, Fernando Sancho, Mariela Cerrada
Echo state network and variational autoencoder for efficient one-class learning on dynamical systems. J. Intell. Fuzzy Syst. 34(6): 3799-3809 (2018) - 2017
- [j17]Diego Cabrera
Automatic feature extraction of time-series applied to fault severity assessment of helical gearbox in stationary and non-stationary speed operation. Appl. Soft Comput. 58: 53-64 (2017) - [j16]Juan Terán, José Aguilar-Castro, Mariela Cerrada
Integration in industrial automation based on multi-agent systems using cultural algorithms for optimizing the coordination mechanisms. Comput. Ind. 91: 11-23 (2017) - [j15]Fannia Pacheco
Attribute clustering using rough set theory for feature selection in fault severity classification of rotating machinery. Expert Syst. Appl. 71: 69-86 (2017) - [j14]Chuan Li
A Bayesian approach to consequent parameter estimation in probabilistic fuzzy systems and its application to bearing fault classification. Knowl. Based Syst. 129: 39-60 (2017) - [c13]Mariela Cerrada, Fannia Pacheco
SOA Based Integrated Software to Develop Fault Diagnosis Models Using Machine Learning in Rotating Machinery. SOSE 2017: 28-37 - 2016
- [j13]Mariela Cerrada
Hierarchical feature selection based on relative dependency for gear fault diagnosis. Appl. Intell. 44(3): 687-703 (2016) - [j12]Chuan Li
Observer-biased bearing condition monitoring: From fault detection to multi-fault classification. Eng. Appl. Artif. Intell. 50: 287-301 (2016) - [j11]Fannia Pacheco
A statistical comparison of neuroclassifiers and feature selection methods for gearbox fault diagnosis under realistic conditions. Neurocomputing 194: 192-206 (2016) - [j10]Chuan Li
Fuzzy determination of informative frequency band for bearing fault detection. J. Intell. Fuzzy Syst. 30(6): 3513-3525 (2016) - [j9]Chuan Li
Fault Diagnosis for Rotating Machinery Using Vibration Measurement Deep Statistical Feature Learning. Sensors 16(6): 895 (2016) - [c12]Fannia Pacheco
Clustering algorithm using rough set theory for unsupervised feature selection. IJCNN 2016: 3493-3499 - [c11]Fannia Pacheco
A methodological framework using statistical tests for comparing machine learning based models applied to fault diagnosis in rotating machinery. LA-CCI 2016: 1-6 - 2015
- [j8]Chuan Li
Multimodal deep support vector classification with homologous features and its application to gearbox fault diagnosis. Neurocomputing 168: 119-127 (2015) - [j7]Mariela Cerrada
Multi-Stage Feature Selection by Using Genetic Algorithms for Fault Diagnosis in Gearboxes Based on Vibration Signal. Sensors 15(9): 23903-23926 (2015) - [c10]Miguel Angel Ramirez Canelón, Eliézer Colina Morles, Mariela Cerrada-Lozada:
Invertible singleton fuzzy models: application to petroleum production control systems. FSKD 2015: 547-552 - 2014
- [j6]Juan Terán, José Aguilar, Mariela Cerrada:
Collective Learning in Multi-Agent Systems Based on Cultural Algorithms. CLEI Electron. J. 17(2) (2014) - [c9]Juan Terán, José Aguilar
Cultural learning for Multi-Agent System and its application to fault management. IEEE Congress on Evolutionary Computation 2014: 2188-2195 - [c8]Fannia Pacheco
Methodological framework for data processing based on the Data Science paradigm. CLEI 2014: 1-12 - 2013
- [j5]Juan Terán, José Aguilar-Castro, Mariela Cerrada:
Mathematical Models of Coordination Mechanisms in Multi-Agent Systems. CLEI Electron. J. 16(2) (2013) - [c7]Carlos Ramón Rangel, Fannia Pacheco
Methodology for detecting the feasibility of using data mining in an organization. CLEI 2013: 1-12 - [c6]Juan Terán, José Aguilar
Cultural Algorithms-based learning model for multi-agent systems. CLEI 2013: 1-12
2000 – 2009
- 2008
- [j4]José Aguilar, I. Bessembel, Mariela Cerrada, Francisco Hidrobo, F. Narciso:
A Methodology for Modeling Systems of Engineering based on Agents. Inteligencia Artif. 12(38): 39-60 (2008) - 2007
- [j3]Mariela Cerrada
Agents-based design for fault management systems in industrial processes. Comput. Ind. 58(4): 313-328 (2007) - [c5]José Aguilar
A Methodology to Specify Multiagent Systems. KES-AMSTA 2007: 92-101 - 2006
- [c4]Mariela Cerrada
Reinforcement Learning-Based Tuning Algorithm Applied to Fuzzy Identification. ISNN (1) 2006: 623-630 - 2005
- [j2]Mariela Cerrada
Dynamical membership functions: an approach for adaptive fuzzy modelling. Fuzzy Sets Syst. 152(3): 513-533 (2005) - [c3]José Aguilar, Mariela Cerrada
A Multiagent Model for Intelligent Distributed Control Systems. KES (1) 2005: 191-197 - 2004
- [c2]Mariela Cerrada-Lozada, Juan Cardillo, José Aguilar-Castro, Raúl Faneite:
Multi-Agents Based Reference Model for Fault Management System in Industrial Processes. ICINCO (1) 2004: 342-345 - 2002
- [c1]Mariela Cerrada, José Aguilar, Eliézer Colina Morles, André Titli:
An approach for dynamical adaptive fuzzy modeling. FUZZ-IEEE 2002: 156-161 - 2001
- [j1]José Aguilar-Castro, Mariela Cerrada-Lozada, Katiuska Morillo:
Intelligent Hybrid System: A Reliability-Based Failure Management Application. J. Adv. Comput. Intell. Intell. Informatics 5(6): 307-314 (2001)
Coauthor Index
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