Karl Ezra S. Pilario
Cited by
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Canonical variate dissimilarity analysis for process incipient fault detection
KES Pilario, Y Cao
IEEE Transactions on Industrial Informatics 14 (12), 5308-5315, 2018
A review of kernel methods for feature extraction in nonlinear process monitoring
KE Pilario, M Shafiee, Y Cao, L Lao, SH Yang
Processes 8 (1), 24, 2019
Mixed kernel canonical variate dissimilarity analysis for incipient fault monitoring in nonlinear dynamic processes
KES Pilario, Y Cao, M Shafiee
Computers & Chemical Engineering 123, 143-154, 2019
Identification of gas-liquid flow regimes using a non-intrusive Doppler ultrasonic sensor and virtual flow regime maps
SG Nnabuife, KES Pilario, L Lao, Y Cao, M Shafiee
Flow Measurement and Instrumentation 68, 101568, 2019
Structural reliability assessment of offshore wind turbine support structures subjected to pitting corrosion‐fatigue: A damage tolerance modelling approach
AA Shittu, A Mehmanparast, M Shafiee, A Kolios, P Hart, K Pilario
Wind Energy 23 (11), 2004-2026, 2020
A kernel design approach to improve kernel subspace identification
KES Pilario, Y Cao, M Shafiee
IEEE Transactions on Industrial Electronics 68 (7), 6171-6180, 2020
Development of a Real-Time Objective Gas-Liquid Flow Regime Identifier Using Kernel Methods
EN Eyo, KES Pilario, L Lao, G Falcone
IEEE Transactions on Cybernetics, 2019
Comprehensive review on machine learning methodologies for modeling dye removal processes in wastewater
SK Bhagat, KE Pilario, OE Babalola, T Tiyasha, M Yaqub, CE Onu, ...
Journal of Cleaner Production 385, 135522, 2023
Incipient Fault Detection, Diagnosis, and Prognosis using Canonical Variate Dissimilarity Analysis
KES Pilario, Y Cao, M Shafiee
Computer Aided Chemical Engineering 46, 1195-1200, 2019
Feedback-controlled CSTR process for fault simulation
KE Pilario
MATLAB Central File Exchange, Retrieved, 2019
Explainable Artificial Intelligence for Fault Diagnosis of Industrial Processes
K Jang, KES Pilario, N Lee, I Moon, J Na
IEEE Transactions on Industrial Informatics, 2023
Geographical discrimination of propolis using dynamic time warping kernel principal components analysis
KE Pilario, A Tielemans, ERE Mojica
Expert Systems with Applications 187, 115938, 2022
Process Incipient Fault Detection using Canonical Variate Analysis
KE Pilario, Y Cao
23rd International Conference on Automation and Computing, 2017
Machine Learning Based Flow Regime Identification using Ultrasonic Doppler Data and Feature Relevance Determination
R Roxas II, MA Evangelista, JA Sombillo, SG Nnabuife, KE Pilario
Digital Chemical Engineering 3, 100024, 2022
Geographical and entomological differentiation of Philippine honey by multivariate analysis of FTIR spectra
JR Grabato, KE Pilario, JRL Micor, ERE Mojica
Journal of Food Composition and Analysis 114, 104853, 2022
Predicting drying curves in algal biorefineries using gaussian process autoregressive models
KES Pilario, PML Ching, AMA Calapatia, AB Culaba
Digital Chemical Engineering 4, 100036, 2022
Reconstruction based fault prognosis in dynamic processes using canonical variate analysis
KES Pilario, Y Cao, M Shafiee, L Lao
2019 25th International Conference on Automation and Computing (ICAC), 1-6, 2019
Spatio-temporal solar–wind complementarity assessment in the Province of Kalinga-Apayao, Philippines using canonical correlation analysis
KES Pilario, JA Ibaņez, XN Penisa, JB Obra, CMF Odulio, JD Ocon
Sustainability 14 (6), 3253, 2022
Nonlinear dynamic data reconciliation with gross error identification: a dynamic MINLP solved using a hybrid Nelder–Mead simplex and particle swarm optimization
KES Pilario, J Munoz
Proceedings of the joint international symposium on regional revitalization …, 2015
Nonlinear Data Reconciliation and Gross Error Detection using Branch-and-Bound Technique.
KE Pilario
GSTF Journal of Engineering Technology 3 (2), 2015
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