J. Hines

发表

Independent Component Analysis for Redundant Sensor Validation

Jun Ding, J. Hines, 2003 .

A logarithmic neural network architecture for unbounded non-linear function approximation

J. W. Hines, J. Hines, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

11 Use of Kernel Based Techniques for Sensor Validation in Nuclear Power Plants

A. Gribok, R. Uhrig, J. Hines, 2003 .

Dynamic Prognoser Architecture via the Path Classification and Estimation (PACE) Model

J. Wesley Hines, Dustin Garvey, J. Hines, 2007, AAAI Fall Symposium: Artificial Intelligence for Prognostics.

FAULT DETECTION AND ISOLATION : A HYBRID APPROACH

Don W. Miller, J. Hines, B. Hajek, 2000 .

Identifying Suitable Degradation Parameters for Individual-Based Prognostics

Jamie B. Coble, J. Wesley Hines, J. Hines, 2012 .

Sensor-Based Degradation Prediction and Prognostics for Remaining Useful Life Estimation: Validation on Experimental Data of Electric Motors

J. Hines, M. Venturini, F. Barbieri, 2020 .

Prognostics for Light Water Reactor Sustainability : Empirical Methods for Heat Exchanger Prognostic Lifetime Predictions

Belle R. Upadhyaya, J. Wesley Hines, Alan Nam, 2014 .

Pattern Recognition Techniques for Transient Detection to Enhance Nuclear Reactors’ Operational Safety

J. W. Hines, R. E. Uhrig, A. Gribok, 2000 .

Selection of Multiple Regularization Parameters in Local Ridge Regression Using Evolutionary Algorithms and Prediction Risk Optimization

A. Gribok, J. Hines, A. Urmanov, 2003 .

INVESTIGATION OF A FUZZY-NEURAL NETWORK APPLICATION IN CLASSIFICATION OF SOILS USING GROUND-PENETRATING RADAR IMAGERY

J. W. Hines, Robert S. Freeland, R. E. Yoder, 2004 .

Particulate Fouling and its Effect on U-Tube Steam Generator Thermal Performance

B. Upadhyaya, J. Hines, Xuedong Huang, 2003 .

Enhancing the Resilience of Key Equipment to False Data Injection Attacks in NPPs

Fan Zhang, Jamie B. Coble, J. Wesley Hines, 2019, Transactions of the American Nuclear Society - Volume 121.

Information complexity-based regularization parameter selection for solution of ill conditioned inverse problems

H. Bozdogan, A. Gribok, R. Uhrig, 2002 .

Techniques of trend analysis in degradation-based prognostics

J. Kobza, J. Hines, S. Niknam, 2016, The International Journal of Advanced Manufacturing Technology.

Sensor Validation and Fault Detection Using Neural Networks

Xiao Xu, Robert E. Uhrig, J. Wesley Hines, 1999 .

Online Support Vector Regression Approach for the Monitoring of Motor Shaft Misalignment and Feedwater Flow Rate

Adedeji B. Badiru, J. Wesley Hines, Olufemi A. Omitaomu, 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

MSET PERFORMANCE OPTIMIZATION THROUGH REGULARIZATION

J. Wesley Hines, Alexander Usynin, J. Hines, 2005 .

COMPUTATIONAL INTELLIGENCE IN NUCLEAR ENGINEERING

Robert E. Uhrig, J. Wesley Hines, R. Uhrig, 2005 .

Prediction interval estimation techniques for empirical modeling strategies and their applications to signal validation tasks

J. Wesley Hines, Brandon Rasmussen, J. Hines, 2003 .

Heuristic, systematic, and informational regularization for process monitoring

Andrei V. Gribok, Robert E. Uhrig, Aleksey M. Urmanov, 2002, Int. J. Intell. Syst..

Regularization of Feedwater Flow Rate Evaluation for Venturi Meter Fouling Problem in Nuclear Power Plants

Andrei V. Gribok, Robert E. Uhrig, J. Wesley Hines, 2001 .

Regularization Methods for Inferential Sensing in Nuclear Power Plants

Robert E. Uhrig, J. Wesley Hines, Andrei Gribok, 2000 .

IMPROVED METHODS FOR ON-LINE SENSOR CALIBRATION VERIFICATION

Robert E. Uhrig, J. Wesley Hines, Andrei Gribok, 2000 .

Current Computational Trends in Equipment Prognostics

J. Wesley Hines, Alexander Usynin, J. Hines, 2008, Int. J. Comput. Intell. Syst..

Redundant Sensor Calibration Monitoring Using Independent Component Analysis and Principal Component Analysis

Jun Ding, Andrei V. Gribok, J. Wesley Hines, 2004, Real-Time Systems.

A hybrid approach for detecting and isolating faults in nuclear power plant interacting systems

J. W. Hines, Don W. Miller, B. K. Hajek, 1996 .

A model for predicting lung cancer response to therapy.

Patrick A Kupelian, Katja M Langen, Sanford L Meeks, 2007, International Journal of Radiation Oncology, Biology, Physics.

An Integrated Fuzzy Inference-based Monitoring, Diagnostic, and Prognostic System for Intelligent Control and Maintenance

J. Wesley Hines, Dustin Garvey, J. Hines, 2007 .

An Adaptive Model for Expanded Process Monitoring

J. W. Hines, Matt Humberstone, B. Wood, 2011 .

Solar particle event dose prediction using kernel regression

J. Hines, L. Townsend, A. Usynin, 2009, 2009 IEEE Aerospace conference.

VALIDATION OF ON-LINE MONITORING TECHNIQUES TO NUCLEAR PLANT DATA

J. Wesley Hines, Dustin Garvey, R Seibert, 2007 .

Signal Validation Using an Adaptive Neural Fuzzy Inference System

Robert E. Uhrig, J. Wesley Hines, Darryl J. Wrest, 1997 .

IMPROVING THE CROSS CORRELATION METHOD OF INDIRECT FLOW MEASUREMENT BY WATER INJECTION AND MODELING

B. Upadhyaya, J. Hines, J. Coble, 2017 .

An information approach to regularization parameter selection under model misspecification

Robert E. Uhrig, Aleksey M. Urmanov, Andrei Gribok, 2002 .

Regularization of Ill-Posed Surveillance and Diagnostic Measurements

Andrei V. Gribok, Robert E. Uhrig, Aleksey M. Urmanov, 2002 .

Multi-objective design optimization of a fast spectrum nuclear experiment facility using artificial intelligence

J. Wesley Hines, Vladimir Sobes, Ondrej Chvala, 2021 .

INCORPORATING PRIOR BELIEF IN THE GENERAL PATH MODEL: A COMPARISON OF INFORMATION SOURCES

Jamie B. Coble, J. Wesley Hines, J. Hines, 2014 .

Prediction of energetic solar particle event dose-time profiles using artificial neural networks

Lawrence W. Townsend, J. W. Hines, Jennifer L. Hoff, 2003 .

Multilayer Data-Driven Cyber-Attack Detection System for Industrial Control Systems Based on Network, System, and Process Data

Jamie B. Coble, Fan Zhang, J. Wesley Hines, 2019, IEEE Transactions on Industrial Informatics.

Identifying Optimal Prognostic Parameters from Data : A Genetic Algorithms Approach

J. Wesley Hines, Jamie Coble, J. Hines, 2009 .

Uncertainty Analysis of Memory Based Sensor Validation Techniques

Andrei V. Gribok, Aleksey M. Urmanov, J. Wesley Hines, 2004, Real-Time Systems.

Applying the General Path Model to Estimation of Remaining Useful Life

Jamie B. Coble, J. Wesley Hines, J. Hines, 2011, International Journal of Prognostics and Health Management.

MATLAB Supplement to Fuzzy and Neural Approaches in Engineering

Lefteri H. Tsoukalas, Robert E. Uhrig, J. Wesley Hines, 1997 .

A Review of Prognostics and Health Management Applications in Nuclear Power Plants

Jamie B. Coble, Leonard J. Bond, J. Wesley Hines, 2020, International Journal of Prognostics and Health Management.

Differentiating between expanded and fault conditions using principal component analysis

J. Hines, B. Wood, J. Henkel, 2012, J. Intell. Manuf..

Analysis of Acoustic Emission Data for Bearings subject to Unbalance

Rapinder Sawhney, J. Wesley Hines, Seyed A. Niknam, 2020 .

A New Proposal Generalized Predictive Control Algorithm With Polynomial Reference Tracking Applied for Sodium Fast Reactors

B. Upadhyaya, J. Hines, L. F. S. C. Pereira, 2023, IEEE Access.

Optimization of Fuzzy Evapotranspiration Model Through Neural Training with Input-Output Examples

Daniel C. Yoder, J. W. Hines, R. E. Yoder, 2001 .

Techniques of trend analysis in degradation-based prognostics

J. Wesley Hines, John E. Kobza, Seyed A. Niknam, 2017 .

Use of Kernel Based Techniques for Sensor Validation in Nuclear Power Plants

Andrei V. Gribok, Robert E. Uhrig, Aleksey M. Urmanov, 2003 .

Application of Fuzzy-Neural Network in Classification of Soils using Ground-penetrating Radar Imagery

Robert S. Freeland, J. Wesley Hines, R. E. Yoder, 2002 .

A Novel Approach to Process Modeling for Instrument Surveillance and Calibration Verification

Robert E. Uhrig, J. Wesley Hines, Brandon Rasmussen, 2003 .

Nonlinear Partial Least Squares Modeling for Instrument Surveillance and Calibration Verification

Robert E. Uhrig, J. Wesley Hines, Brandon Rasmussen, 2000 .

Evaluating the Improvement of Cross-Correlation–Based Flow Measurement by Periodic Fluid Injection

B. Upadhyaya, J. Hines, J. Coble, 2021, Nuclear Technology.

In-situ Condition Monitoring of Components in Small Modular Reactors Using Process and Electrical Signature Analysis. Final report, volume 1. Development of experimental flow control loop, data analysis and plant monitoring

Belle R. Upadhyaya, Brian Damiano, Duygu Bayram, 2015 .

Operation and maintenance decision-making using prognostic information

John E. Kobza, J. Wesley Hines, Seyed A. Niknam, 2015, 2015 Annual Reliability and Maintainability Symposium (RAMS).

Verification of helical tomotherapy delivery using autoassociative kernel regressiona).

Rebecca M Seibert, Chester R Ramsey, Dustin R Garvey, 2007, Medical physics.

Advanced Instrumentation and Control Methods for Small and Medium Reactors with IRIS Demonstration

Belle R. Upadhyaya, Jamie B. Coble, K. D. Lewis, 2011 .

Adaptive Monitoring, Fault Detection and Diagnostics, and Prognostics System for the IRIS Nuclear Plant

Jamie B. Coble, J. W. Hines, Matt Humberstone, 2010 .

A Novel Method for Monitoring Single Variable Systems for Fault Detection, Diagnostics and Prognostics

Jamie B. Coble, J. Wesley Hines, B. Keith Bailey, 2010 .

Evaluation of instrument calibration monitoring using artificial neural networks

Xiao Xu, J. W. Hines, Robert E. Uhrig, 1997 .

Lessons learned from the U.S. nuclear power Plant on-line monitoring programs

E. Davis, J. W. Hines, J. Hines, 2005 .

SENSOR CALIBRATION AND MONITORING USING AUTOASSOCIATIVE NEURAL NETWORKS

D. J. Wrest, R. Uhrig, J. Hines, 2000 .

ON-LINE SENSOR CALIBRATION MONITORING AND FAULT DETECTION FOR CHEMICAL PROCESSES

Robert E. Uhrig, J. Wesley Hines, Xiao Xu, 1998 .

An information approach to regularization parameter selection under model misspecification

A. Gribok, R. Uhrig, J. Hines, 2002 .