# PUBLICATIONS

##### Journal Papers

[J33] Razavi-Far, R., Farajzadeh-Zanajni, M., Chakrabarti, S., Wang, B., Saif, M. “Imputation-based Ensemble Techniques for Class Imbalance Learning”. in IEEE Transactions on Knowledge and Data Engineering, 2020, in press.

[J32] Hassani, H., Razavi-Far, R., Saif, M., “Fault Location in Smart Grids through Multicriteria Analysis of Group Decision Support Systems”. in IEEE Transactions on Industrial Informatics, 16(12), pp. 7318-7327, 2020.

[J31] Hassani, H., Razavi-Far, R., Saif, M., Capolino, G.A., “Regression Models with Graph-Regularization Learning Algorithms for Accurate Fault Location in Smart Grids”. in IEEE Systems Journal, 2020, in press.

[J30] Sarrafan, N., Zarei, J., Razavi-Far, R., Saif, M., Khooban, M. “A Novel On-Board DC/DC Converter Controller Feeding Uncertain Constant Power Loads,” in IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020, in press.

[J29] Kowsari, E., Zarei, J. Razavi-Far, R., Khooban, M.H., Dragigević, T., “A Novel Stochastic Predictive Stabilizer for DC MicroGrids Feeding CPLs”. in IEEE Journal of Emerging and Selected Topics in Power Electronics, In Press, 2020, in press.

[J28] Kordestani, M., Saif, M., Orchard, M.E., Razavi-Far, R., Khorasani, K. “Failure Prognosis and Applications-A Survey of Recent Literature”. in IEEE Transactions on Reliability, 2020, in press.

[J27] Gharesi, N., Arefi, M.M., Razavi-Far, R., Zarei, J., Yin, S., “A Neuro-Wavelet Based Approach for Diagnosing Bearing Defects”. in Advanced Engineering Informatics, 46, 101172, 2020.

[J26] Ahmadi, E., Zarei, J., Razavi-Far, R., “Robust l1-Controller Design for Discrete-time Positive T-S Fuzzy Systems using Dual Approach,” in IEEE Transaction on Systems Man Cybernetics: Systems, 2020, in press.

[J25] Razavi-Far, R., Farajzadeh-Zanajni, M., Saif, M., Chakrabarti, S. “Correlation Clustering Imputation for Diagnosing Attacks and Faults with Missing Power Grid Data”. in IEEE Transactions on Smart Grid, 11(2), pp. 1453-1464, 2020.

[J24] Ahmadi, E., Zarei, J., Razavi-Far, R., Saif, M. “A dual approach for positive T–S fuzzy controller design and its application to cancer treatment under immunotherapy and chemotherapy”. in Biomedical Signal Processing and Control, 58, 101822, 2020.

[J23] Razavi-Far, R., Cheng, B., Saif, M., Ahmadi, M. “Similarity-learning information-fusion schemes for missing data imputation”. Knowledge-Based Systems, 187, pp. 104805, 2020.

[J22] Bahreini, M., Zarei, J., Razavi-Far, R., Saif, M. “Robust Finite–time Stochastic Stabilization and Fault tolerant Control for Uncertain Networked Control Systems Considering Random delays and Stochastic Actuator Faults”. Transactions of the Institute of Measurement and Control, 41(12), pp. 3550-3561, 2019.

[J21] Hassani, H., Zarei, J., Razavi-Far, R., Saif, M. “Robust Interval Type–2 Fuzzy Approach for Fault Detection of Networked Control Systems subject to Immeasurable Premise Variables”. In IEEE Systems Journal, 13(03), pp. 2954-2965.

[J20] Zarei, J., Kowsari, E., Razavi-Far, R. “Induction Motors Fault Detection Using Square–Root Transformed Cubature Quadrature Kalman Filter”. IEEE Transactions on Energy Conversion, 34(02), pp. 870-877, 2019.

[J19] Razavi-Far, R., Hallaji, E., Farajzadeh-Zanajni, M., Saif, M., Hedayati-Kia, S., Heano, H., Capolino, G. “Information Fusion and Semi-Supervised Deep Learning Scheme for Diagnosing Gear Faults in Induction Machine Systems”. IEEE Transactions on Industrial Electronics, 66(08), pp. 6331-6342, 2019.

[J18] Razavi-Far, R., Chakrabarti, S., Saif, M., Zio, E. “An integrated imputation-prediction scheme for prognostics of battery data with missing observations”. Expert Systems with Applications, 115, pp. 709-723, 2019.

[J17] Razavi-Far, R., Chakrabarti, S., Saif, M., Zio, E., Palade, V. “Extreme Learning Machines for Batteries Condition Prognosis”. International Journal of Artificial Intelligence Tools, 27(08), pp. 1850036:1-1850036:22, 2018.

[J16] Razavi-Far, Hallaji, E., Farajzadeh-Zanajni, M., Saif, M., “A Semi-supervised Diagnostic Framework Based On the Surface Estimation of Faulty Distributions”. IEEE Transactions on Industrial Informatics, 15(3), pp. 1277-1286, 2019.

[J15] Kargar, H., Zarei, J., Razavi-Far, R. “Robust Fault Detection Filter Design for Nonlinear Networked Control Systems with Time-varying Delays and Packet Dropout”. Journal of Circuits, Systems, and Signal Processing, 38(1), pp. 63-84, 2019.

[J14] Razavi-Far, R., Hallaji, E., Saif, M., Ditzler, G. “A Novelty Detector and Extreme Verification Latency Model for Nonstationary Environments”. IEEE Transactions on Industrial Electronics, 66(1), pp. 561-570, 2019.

[J13] Razavi-Far, R., Farajzadeh-Zanjani, M., Saif, M. “An Integrated Class-Imbalance Learning Scheme for Diagnosing Bearing Defects in Induction Motors”. IEEE Transactions on Industrial Informatics, 13(06), pp. 2758-2769, 2017.

[J12] Hassani, H., Zarei, J., Arefi, M.M., Razavi-Far, R. “zSlices-Based General Type-2 Fuzzy Fusion of Support Vector Machines with Application to Bearing Fault Detection”. IEEE Transactions on Industrial Electronics, 64(09), pp. 7210-7217, 2017.

[J11] Razavi-Far, R., Palade, V., Zio, E. “Invasive weed classification”. Neural Computing and Applications, 26(3), pp. 525-539, 2015.

[J10] Razavi-Far, R., Zio, E., Palade, V. “Efficient residuals pre-processing for diagnosing multi-class faults in a doubly fed induction generator, under missing data scenarios”. Expert Systems with Applications, 41(14), pp. 6386-6399, 2014.

[J9] Green, T., Izadi-Zamanabadi, R., Razavi-Far, R., Niemann, H. “Plant-wide dynamic and static optimisation of supermarket refrigeration systems”. International J. of Refrigeration, 38, pp. 106-117, 2014.

[J8] Razavi-Far, R., Kinnaert, M. “A multiple observers and dynamic weighting ensembles scheme for diagnosing new class faults in wind turbines”. Control Engineering Practice, 21(9), pp. 1165–1177, 2013.

[J7] Razavi-Far, R., Zio, E., “Dynamic Learning of Latent Residuals for Diagnosing New Class Drifts in Wind Turbines”. Transactions of the American Nuclear Society. 109(2): pp. 2144-2145.

[J6] Razavi-Far, R., Baraldi, P., Zio, E. “Dynamic weighting ensembles for incremental learning and diagnosing new concept class faults in nuclear power systems”. IEEE Transactions on Nuclear Science, 59(5), pp. 2520-2530, 2012.

[J5] Baraldi, P., Razavi-Far, R., Zio, E. “Classifier-ensemble incremental-learning procedure for nuclear transient identification at different operational conditions”. Reliability Engineering and System Safety, 96, pp. 480-488, 2011.

[J4] Baraldi, P., Razavi-Far, R., Zio, E. “Bagged ensemble of fuzzy c-means classifiers for nuclear transient identification”. Annals of Nuclear Energy, 38(5), pp. 1161-1171, 2010.

[J3] Razavi-Far, R., Davilu, H., Palade, V., Lucas, C. “Model-based fault detection and isolation of a steam generator using neuro-fuzzy networks”. Neurocomputing Journal, 72(13-15), pp. 2939–2951, 2009.

[J2] Razavi-Far, R., Davilu, H., Lucas, C. “Fuzzy logic based fault diagnosis of a PWR nuclear power plant”. International Journal of Nuclear Knowledge Management, 3(3), pp. 296-311, 2009.

[J1] Razavi-Far, R., Davilu, H., Lucas, C. “Model-based fault detection and isolation of a PWR nuclear power plant using neural networks”. ATW International Journal for Nuclear Power, 53(2), pp. 110-114, 2008.

##### Peer-Reviewed Conference Publications

[C53] Wan, D., Razavi-Far, R., Saif, M., “Cooperative Clustering Missing Data Imputation,” Accepted for Publication in IEEE International Conference on Systems, Man, and Cybernetics, 2020.

[C52] Hassani, H., Razavi-Far, R., Saif, M., “A Comparative Assessment of Dimensionality Reduction Techniques for Diagnosing Faults in Smart Grids,” Accepted for Publication in IEEE International Conference on Systems, Man, and Cybernetics, 2020.

[C51] Hassani, H., Razavi-Far, R., Saif, M., Zarei, J., “Unknown Input Observers Design For Real-Time Mitigation of the False Data Injection Attacks,” Accepted for Publication in IEEE International Conference on Systems, Man, and Cybernetics, 2020.

[C50] Hallaji, E., Razavi-Far, R., Saif, M., “Detection of Malicious SCADA Communications via Multi-Subspace Feature Selection”. in IEEE World Congress on Computational Intelligence (IEEE WCCI), International Joint Conference on Neural Networks (IJCNN), Glasgow, 2020.

[C49] Hallaji, E., Razavi-Far, R., Saif, M., “Enhancing Detection Accuracy of Cyber Attacks through Dimensionality Reduction,” in the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15), 2020.

[C48] Hassani, H., Razavi-Far, R., Saif, M., “Fault Diagnosis in Smart Grids Using a Deep Long Short-Term Memory-based Feature Learning Architecture,” in the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15), 2020.

[C47] Zaman, A., Zarei, J., Razavi-Far, R., Saif, M., “Optimal Attack Assignment on Remote State Estimation in Multi Nonlinear Systems: Structural and Asymptotic Policy,” in the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15), 2020.

[C46] Rostami, M.A., Zarei, J., Sarrafan, N., Razavi-Far, R., Saif, M., “Distributed Prescribed Finite-Time Frequency and Voltage Restoring of Inverter-Based Microgrids,” in the 30th European Safety and Reliability Conference and the 15th Probabilistic Safety Assessment and Management Conference (ESREL2020 PSAM15), 2020.

[C45] Askari, M., Zarei, J., Razavi-Far, R., Saif, M., “Robust Terminal Sliding Mode Observer-based Sensor Fault Estimation for Uncertain Nonlinear Systems”. in the 14th Annual IEEE International Systems Conference, pp. 1-6, Montreal, Canada, 2020.

[C44] Saeedi, M., Zarei, J., Razavi-Far, R., Saif, M., “Adaptive Sliding Mode Fuzzy PID Control: Supervisory Control”. in the 14th Annual IEEE International Systems Conference, pp. 1-6, Montreal, Canada, 2020.

[C43] Tabatabaei, M., Zarei, J., Razavi-Far, R., Saif, M., “Secure Communication Based on Fractional Chaotic by a Novel Robust Filter Algorithm”. in the 14th Annual IEEE International Systems Conference, pp. 1-6, Montreal, Canada, 2020.

[C42] Hassani, H., Farajzadeh-Zanjani, M., Razavi-Far, R., Saif, M., Palade, V., “Design of A Cost-Effective Deep Convolutional Neural Network–Based Scheme For Diagnosing Faults in Smart Grids”. in the Proceedings of 18th IEEE International Conference on Machine Learning and Applications, ICMLA2019, pp. 1420-1425, Boca Raton, Florida, USA, 2019.

[C41] Hassani, H., Razavi-Far, R., Saif, M., “Locating Faults in Smart Grids Using Neuro–Fuzzy Networks”. in the Proceedings of IEEE International Conference on Systems, Man and Cybernetics, SMC2019, pp. 3281-3286, Bari, Italy, 2019.

[C40] Gharesi, N., Arefi, M.M., Ebrahimi, Z., Razavi-Far, R., Saif, M., Zarei, J., “Analyzing the Vibration Signals for Bearing Defects Diagnosis Using the Combination of SGWT Feature Extraction and SVM”. in the Proceedings of the 10th IFAC Conference on Fault Detection, Supervision and Safety of Technical Processes, International Federation of Automatic Control (IFAC), Warsaw; Poland, 51-24, pp. 221-227, 2018.

[C39] Bahreini, M., Zarei, J., Razavi-Far, R., Saif, M., “Robust Finite-Time Fault-Tolerant Control of Uncertain Networked Control Systems Via Markovian Jump Linear Systems Approach”. in the Proceedings of the 10th IFAC Conference on Fault Detection, Supervision and Safety of Technical Processes, International Federation of Automatic Control (IFAC), Warsaw; Poland, 51-24, pp. 564-569, 2018.

[C38] Hedayati-Kia, S., Razavi-Far, R., Saif, M., “Torsional Vibration Identification Using Electrical Signatures Analysis in Induction Machine-Based Systems”. in the Proceedings of IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 813-816, Windsor; Canada, 2018.

[C37] Farajzadeh-Zanjani, M., Razavi-Far, R., Saif, M., “A Critical Study on the Importance of Feature Extraction and Selection for Diagnosing Bearing Defects”. in the Proceedings of IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 803-808, Windsor; Canada, 2018.

[C36] Tabatabaei, M., Zarei, J., Razavi-Far, R., Saif, M., “State Estimation and Fault Detection of Fractional Order Nonlinear Systems”. in the Proceedings of IEEE International Midwest Symposium on Circuits and Systems (MWSCAS), pp. 1086-1089, Windsor; Canada, 2018.

[C35] Zare, S., Razavi-Far, R., Saif, M., Zarei, J., “Ensemble of One-Class Classifiers for Detecting Faults in Induction Motors”. in the Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE CCECE), pp. 1-6, Quebec City; Canada, 2018.

[C34] Razavi-Far, R., Hallaji, E., Saif, M., Rueda, L., “A Hybrid Scheme for Fault Diagnosis with Partially Labeled Sets of Observations”. in the Proceedings of IEEE International Conference on Machine Learning and Applications, ICMLA2017, pp. 61-67, Cancun, Mexico, USA, 2017.

[C33] Zarei, J., Tabatabaei, M., Razavi-Far, R., Saif, M. “Fractional order unknown input filter design for fault detection of discrete fractional order linear systems”. in the Proceedings of IECON 2017, 43rd Annual Conference of the IEEE Industrial Electronics Society, pp. 4333-4338, Beijing; China, 2017.

[C32] Kowsari, E., Zarei, J., Razavi-Far, R., Saif, M., “Broken Rotor Bars Detection in Induction Motors Using Cubature Kalman Filter”. in the Proceedings of IECON 2017, 43rd Annual Conference of the IEEE Industrial Electronics Society, pp. 8567-8571, Beijing; China, 2017.

[C31] Razavi-Far, R., Farajzadeh-Zanjani, M., Saif, M., Palade, V., “A Hybrid Ensemble Scheme for Diagnosing New Class Defects under Non-stationary and Class Imbalance Conditions in Induction Motors”. in the Proceedings of IEEE International Conference on Sensing, Diagnostics, Prognostics, and Control (IEEE SDPC), pp. 355-360, Shanghai; China, pp. 355-360, 2017.

[C30] Bahreini, M., Zarei, J., Razavi-Far, R., Saif, M., “Robust Fault–Tolerant Control of Uncertain Networked Control Systems Subject to Random Delays and Data Packet Dropouts”. in the Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC), pp. 2459-2464, Banff, Canada, 2017.

[C29] Farajzadeh-Zanjani, M., Razavi-Far, R., Saif, M. “Dimensionality reduction-based diagnosis of bearing defects in induction motors”. in the Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC), pp. 2539-2544, Banff, Canada, 2017.

[C28] Razavi-Far, R., Saif, M., Zio, E., “Adaptive incremental ensemble of extreme learning machines for fault diagnosis in induction motors”. in the Proceedings of IEEE Joint Congress on Neural Networks (IEEE IJCNN), pp. 1615-1622, May 14-19, Alaska, 2017.

[C27] Razavi-Far, R., Saif, M., “Multi-step-ahead parallel prediction strategy for Lithium-ion batteries condition prognosis”. in the Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE CCECE), pp. 1-4, Windsor; Canada, 2017.

[C26] Razavi-Far, R., Farajzadeh-Zanjani, M., Zare, S., Saif, M., Zarei, J., “One-class classifiers for detecting faults in induction motors”. in the Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE CCECE), pp. 1-4, Windsor; Canada, 2017.

[C25] Chakrabarti, S., Razavi-Far, R., Saif, M., “Multi-class heteroscedastic linear dimensionality reduction scheme for diagnosing process faults”. in the Proceedings of IEEE Canadian Conference on Electrical and Computer Engineering (IEEE CCECE), pp. 1-4, Windsor; Canada, 2017.

[C24] Razavi-Far, R., Saif, M. “Ensemble of extreme learning machines for diagnosing bearing defects in non-stationary environments under class imbalance condition”. in the Proceedings of IEEE Symposium Series on Computational Intelligence (IEEE SSCI), pp. 1-7, Athens; Greece; 6-9 December, 2016.

[C23] Farajzadeh-Zanjani, M., Razavi-Far, R., Saif, M. “Efficient sampling techniques for ensemble learning and diagnosing bearing defects under class imbalanced condition”. in the Proceedings of IEEE Symposium Series on Computational Intelligence (IEEE SSCI), pp. 1-6, Athens; Greece; 6-9 December, 2016.

[C22] Razavi-Far, R., Chakrabarti, S., Saif, M. “Multi-step-ahead prediction techniques for Lithium-ion batteries condition prognosis”. in the Proceedings of IEEE International Conference on Systems, Man, and Cybernetics (IEEESMC), pp. 4675-4680, Budapest, Hungary, 2016.

[C21] Razavi-Far, R., Farajzadeh-Zanjani, M., Chakrabarti, S., Saif, M. “Data-driven prognostic techniques for estimation of the remaining useful life of Lithium-ion batteries”. in the Proceedings of IEEE International Conference on Prognostics and Health Management (ICPHM), pp. 1-8, Ottawa, ON, Canada, 2016.

[C20] Razavi-Far, R., Saif, M. “Imputation of missing data using fuzzy neighborhood density-based clustering”. IEEE World Congress on Computational Intelligence, in the Proceedings of IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), pp. 1834-1841, July 25-29, Vancouver, 2016.

[C19] Anvaripour M., Soltanpour, S., Razavi-Far, R. Saif, M., Jonathan Wu, Q.M. “Supervised cooperative clustering for fault diagnosis in power systems”. IEEE World Congress on Computational Intelligence, in the Proceedings of IEEE Congress on Evolutionary Computation (IEEE CEC), pp. 160-167, July 25-29, Vancouver, 2016.

[C18] Farajzadeh-Zanjani, M., Razavi-Far, R., Saif, M. Rueda, L. “Efficient feature extraction of vibration signals for diagnosing bearing defects in induction motors”. IEEE World Congress on Computational Intelligence, in the Proceedings of IEEE Joint Congress on Neural Networks (IEEE IJCNN), pp. 4505-4511, July 25-29, Vancouver, 2016.

[C17] Farajzadeh-Zanjani, M., Razavi-Far, R., Saif, M., Zarei, J., Palade, V. “Diagnosis of bearing defects in induction motors by fuzzy-neighborhood density-based clustering”. in the Proceedings of IEEE International Conference on Machine Learning and Applications, ICMLA2015, pp. 935-940, December 9-11, Miami, Florida, USA, 2015.

[C16] Nejad, E.M., Razavi-Far, R., Jonathan Wu, Q.M., Saif, M. “Multiple imputation of missing data for diagnosing sensor faults in a wind turbine”. in the Proceedings of IEEE International Conference on Machine Learning and Applications, ICMLA2015, pp. 677-680, December 9-11, Miami, Florida, USA, 2015.

[C15] Razavi-Far, R., Saif, M. “Imputation of missing data for diagnosing sensor faults in a wind turbine”. in the Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, SMC2015, Big Data Analytic for Human-Centric Systems, pp. 99-104, October 9-12, Hong Kong, 2015.

[C14] Razavi-Far, R., Palade, V., Zio, E. “Optimal detection of new classes of faults by an invasive weed optimization method”. IEEE World Congress on Computational Intelligence, in the Proceedings of the International Joint Conference on Neural Networks, IJCNN 2014, pp. 91-98, July 6-11, Beijing, 2014.

[C13] Razavi-Far, R., Zio, E. “Dynamic learning of latent residuals for diagnosing new class drifts in wind turbines”. Transactions of the American Nuclear Society, Volume 109, Issue PART 2, The Topical Meeting - Risk Management for Complex Socio-technical Systems (RM4CSS), pp. 2144-2145, 2013.

[C12] Razavi-Far, R., Palade, V., Sun, J. “Optimizing performance of a refrigeration system using an invasive weed optimization algorithm”. 20th European Conference on Artificial Intelligence (ECAI 2012), 3rd International Workshop/Special Track on Combinations of Intelligent Methods and Applications (CIMA 2012), pp. 43-48, Montpellier, France, August 27-28, 2012.

[C11] Razavi-Far, R., Baraldi, P., Zio, E. “Ensemble of neural networks for detecting and classifying faults in nuclear power systems”. 10th International FLINS Conference on Uncertainty Modeling in Knowledge Engineering and Decision Making, ISI book, World Scientific Proceedings series on computer engineering and information science 7, pp. 1202-1207, Istanbul, Turkey, August 26-29, 2012.

[C10] Razavi-Far, R., Kinnaert, M. “Incremental design of a decision system for residual evaluation: a wind turbine application”. 8th IFAC Conference on Fault Detection, Supervision and Safety of Technical Processes, International Federation of Automatic Control, pp. 343-348, Mexico City, 29-31 August 2012.

[C9] Green, T., Kinnaert, M., Razavi-Far, R., Izadi-Zamanabadi, R., Niemann, H.H. “Optimizing performance in steady state for a supermarket refrigeration system”. 20th Mediterranean Conference on Control & Automation (MED), pp. 1061-1066, Barcelona, July 3-6, 2012.

[C8] Green, T., Razavi-Far, R., Izadi-Zamanazabdi, R., Niemann, H.H. “Plant-wide performance optimization, the refrigeration system case”. IEEE Multi-Conference on Systems and Control (MSC), pp. 208-213, Dubrovnik, Croatia, October 3-5, 2012.

[C7] Baraldi, P., Razavi-Far, R., Zio, E. “A method for estimating the confidence in the identification of nuclear transients by a bagged ensemble of FCM classifiers”. 7th American Nuclear Society International Topical Meeting on Nuclear Plant Instrumentation, Control and Human-Machine Interface Technologies (NPIC&HMIT), pp. 283-293, Las Vegas, Nevada, November 7-11, 2010.

[C6] Razavi-Far, R., Davilu, H., Palade, V., Lucas, C. “Neuro-fuzzy based fault diagnosis of a steam generator”. 7th IFAC Conference on Fault Detection, Supervision and Safety of Technical Processes, International Federation of Automatic Control (IFAC). pp. 1180-1185, Barcelona, Spain, June 30 - July 3, 2009.

[C5] Razavi-Far, R., Davilu, H., Lucas, C. “Model-based fault diagnosis of a PWR nuclear power plant using fuzzy inference approach”. 8th International FLINS Conference on Computational Intelligence in Decision and Control. pp. 945-950, ISI book, Madrid, Spain, 21-24 September, 2008.

[C4] Razavi-Far, R., Davilu, H., Lucas, C. “Neural networks for fault detection and isolation of a nonlinear dynamic system”. 1st Joint Conference on Fuzzy and Intelligent Systems. pp. 275-281, Ferdowsi University of Mashhad, 29-31 Aug, 2007.

[C3] Razavi-Far, R., Lucas, C., Davilu, H. “Genetic algorithms optimization and sensitivity analysis of neural networks for fault detection and isolation in nuclear systems”. 13th National Symposium of Nuclear Engineering in Iran, 2006.

[C2] Razavi-Far, R., Davilu, H., Lucas, C. “Nuclear power plant fault diagnostics using modular neural networks”. 2nd International Conference on Nuclear Science and Technology in Iran, Shiraz University, 27-30 April, 2004.

[C1] Razavi-Far, R., Davilu, H., Lucas, C. “Fault diagnosis and transient identification of a nuclear power plant using neural networks”. 10th National Symposium of Nuclear Engineering in Iran, 2003.

##### Book Chapters

[B1] Razavi-Far, R., Palade, V., Sun, J. “Optimizing performance of a refrigeration system using an invasive weed optimization algorithm”. Combinations of Intelligent Methods and Applications, Springer series book: “Smart Innovation, Systems and Technologies”. Vol. 23, pp. 79-93, 2013.

##### Technical/Research Reports:

[T15] Naderi, E., Khorasani, K., Hashtrudi Zad, S., Razavi-Far, R., Saif, M. 2015. “Prognosis of Multi Functional Spoiler Subsystem - Literature Review and Survey of Fault Prognosis”. CARIC Project DPHM-702.

[T14] Razavi-Far, R., Saif, M. 2015. “A survey of prognostic systems”. Literature Rev., University of Windsor.

[T13] Razavi-Far, R., 2014. “Missing data imputation”. Tech. Report, CanmetEnergy, NRCan.

[T12] Razavi-Far, R., 2013. “Predicting electricity consumption in smart buildings”. Tech. Report, CanmetEnergy, NRCan.

[T11] Razavi-Far, R., 2010. “Development of a novel class detector using dynamic weighting ensembles algorithm for new class fault detection and diagnosis”. Tech. Report, Politecnico di Milano.

[T10] Razavi-Far, R., 2010. “Experimental comparison between FCM clustering, decision tree classifier, multi-layer perceptron and recurrent neuro-classifier as base-classifiers of the dynamic weighting ensembles algorithm”. Tech. Report, Politecnico di Milano.

[T9] Razavi-Far, R., 2008-2009. “Experimental comparison between bagging ensemble and optimized FCM classifier in nuclear transient identification”. Tech. Report, Politecnico di Milano.

[T8] Razavi-Far, R., 2008. “Sensitivity analysis of ensemble performance to the change of base classifier parameters”. Tech. Report, Politecnico di Milano.

[T7] Razavi-Far, R., 2006. “Survey of computational intelligence methods for fault detection and isolation in NPPs”. Technical Note, Department of Nuclear Engineering, Tehran Polytechnic University.

[T6] Razavi-Far, R., 2004-2006. “Building a nonlinear MATLAB-based PWR simulator”. Research Report, Department of Nuclear Engineering, Tehran Polytechnic University.

[T5] Razavi-Far, R. 2004. “Fuzzy logic applications in nuclear power plants”. Tech. Report, Department of Nuclear Engineering, Tehran Polytechnic University.

[T4] Razavi-Far, R., Davilu, H. 2003-2004. “Generation IV nuclear energy systems”. Part 4: super critical water cooled reactor, Part 5: molten salt reactor, Part 6: very high temperature reactor. Tech. Report Series, Department of Nuclear Engineering, Tehran Polytechnic University.

[T3] Razavi-Far, R. 2003. “Self organized maps applied to input selection for FDI systems”. Tech. Report, Department of Nuclear Engineering, Tehran Polytechnic University.

[T2] Razavi-Far, R., Davilu, H. 2002. “Two phase natural circulation instabilities”. Tech. Report, Department of Nuclear Engineering, Tehran Polytechnic University.

[T1] Razavi-Far, R. 2001. “A survey study on Chernobyl and Three Mile Island accidents”. Research Report, Department of Nuclear Engineering, Tehran Polytechnic University.

##### Workshops/Poster Presentations:

[P8] Hallaji, E., Razavi-Far, R., Chakrabarti, S., Saif. M., “Prognosis of lithium-ion batteries by resorting to multi-step-ahead prediction techniques”. in HEVPD&D CREATE and EECOMOBILITY (ORF) Conference, University of Windsor, Windsor, Ontario, Canada, 2019.

[P7] Farajzadeh-Zanjani, M., Razavi-Far, R., Saif, M., “Proper features for diagnosing bearing defects”. in HEVPD&D CREATE and EECOMOBILITY (ORF) Conference, University of Windsor, Windsor, Ontario, Canada, 2019.

[P6] Razavi-Far, R., Hallaji, E., Saif, M., Rueda, L., “Hybrid diagnostic system design with partially labeled sets of samples”. in HEVPD&D CREATE and EECOMOBILITY (ORF) Conference, University of Windsor, Windsor, Ontario, Canada, 2018.

[P5] Farajzadeh-Zanjani, M., Razavi-Far, R., Saif, M., “A feature-reduction-based scheme for diagnosing faults in motors”. in HEVPD&D CREATE and EECOMOBILITY (ORF) Conference, University of Windsor, Windsor, Ontario, Canada, 2018.

[P4] Razavi-Far, R., Farajzadeh-Zanjani, M., Chakrabarti, S., Saif, M., “Prognostic system design for estimating the remaining useful life of lithium-ion batteries”. in HEVPD&D CREATE and EECOMOBILITY (ORF) Conference, University of Windsor, Windsor, Ontario, Canada, 2018.

[P3] Farajzadeh-Zanjani, M., Razavi-Far, R., Saif. M., “Design of the diagnostic system for induction machines”. in Collaborative Research and Development (CRD) Workshop, University of Windsor, Windsor, Ontario, Canada, 2016.

[P2] Razavi-Far., Lucas, C., “Fault detection, diagnosis and prognosis systems”. in Iranian Conference on Electrical Engineering (ICEE), Tehran, 2006.

[P1] Razavi-Far., Lucas, C., “Soft computing technologies applications in engineering”, Iranian Conference on Electrical Engineering (ICEE), Tehran, 2005.