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Min Xie Cyber-Physical Distributed Systems
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J. Liu, Y.F. Li, and E. Zio, “A SVM framework for fault detection of the braking system in a high speed train,” Mechan. Syst. Signal Process., vol. 87, pp. 401–409, Mar. 2017.
244
Tan, W., 2009. Unified tuning of PID load frequency controller for power systems via IMC. IEEE Transactions on power systems, 25(1), pp. 341–350.
245
Pham, H.T., Yang, B.S. and Nguyen, T.T., 2012. Machine performance degradation assessment and remaining useful life prediction using proportional hazard model and support vector machine. Mechanical Systems and Signal Processing, 32, pp. 320–330.
246
Pham, H.T., Yang, B.S. and Nguyen, T.T., 2012. Machine performance degradation assessment and remaining useful life prediction using proportional hazard model and support vector machine. Mechanical Systems and Signal Processing, 32, pp. 320–330.
247
Lin, Y.H., Li, Y.F. and Zio, E., 2015. A reliability assessment framework for systems with degradation dependency by combining binary decision diagrams and Monte Carlo simulation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(11), pp. 1556–1564.
248
Chen, B., Niu, Y. and Zou, Y., 2013. Adaptive sliding mode control for stochastic Markovian jumping systems with actuator degradation. Automatica, 49(6), pp. 1748–1754.
249
Jiang, H., Chen, J. and Dong, G., 2016. Hidden Markov model and nuisance attribute projection based bearing performance degradation assessment. Mechanical systems and signal processing, 72, pp. 184–205.
250
Li, J., Wang, Z., Zhang, Y., Fu, H., Liu, C. and Krishnaswamy, S., 2017. Degradation data analysis based on a generalized Wiener process subject to measurement error. Mechanical Systems and Signal Processing, 94, pp. 57–72.
251
Debbarma, S. and Dutta, A., 2016. Utilizing electric vehicles for LFC in restructured power systems using fractional order controller. IEEE transactions on smart grid, 8(6), pp. 2554–2564.
252
Li, Y.G. and Nilkitsaranont, P., 2009. Gas turbine performance prognostic for condition‐based maintenance. Applied energy, 86(10), pp. 2152–2161.
253
Becejac, T., Dehghanian, P. and Kezunovic, M., 2016, October. Probabilistic assessment of PMU integrity for planning of periodic maintenance and testing. In 2016 International Conference on Probabilistic Methods Applied to Power Systems (PMAPS) (pp. 1–6). IEEE.
254
Peng, C.Y. and Tseng, S.T., 2009. Mis‐specification analysis of linear degradation models. IEEE Transactions on Reliability, 58(3), pp. 444–455.
255
STANDARD, B. and ISO, B., 2006. Reciprocating internal combustion engine driven alternating current generating sets— (Doctoral dissertation, Institute of Technology Tallaght).
256
Sun, J., Zuo, H., Wang, W. and Pecht, M.G., 2012. Application of a state space modeling technique to system prognostics based on a health index for condition‐based maintenance. Mechanical Systems and Signal Processing, 28, pp. 585–596.
257
Beganovic, N. and Söffker, D., 2017. Remaining lifetime modeling using State‐of‐Health estimation. Mechanical Systems and Signal Processing, 92, pp. 107–123.
258
Caballé, N.C., Castro, I.T., Pérez, C.J. and Lanza‐Gutiérrez, J.M., 2015. A condition‐based maintenance of a dependent degradation‐threshold‐shock model in a system with multiple degradation processes. Reliability Engineering & System Safety, 134, pp. 98–109.
259
Si, X.S. and Zhou, D., 2013. A generalized result for degradation model‐based reliability estimation. IEEE Transactions on Automation Science and Engineering, 11(2), pp. 632–637.
260
Li, Y.G. and Nilkitsaranont, P., 2009. Gas turbine performance prognostic for condition‐based maintenance. Applied energy, 86(10), pp. 2152–2161.
261
Liu, K. and Huang, S., 2014. Integration of data fusion methodology and degradation modeling process to improve prognostics. IEEE Transactions on Automation Science and Engineering, 13(1), pp. 344–354.
262
Si, X.S., Wang, W., Hu, C.H. and Zhou, D.H., 2011. Remaining useful life estimation–a review on the statistical data driven approaches. European journal of operational research, 213(1), pp. 1–14.
263
Rougé, C., Mathias, J.D. and Deffuant, G., 2014. Relevance of control theory to design and maintenance problems in time‐variant reliability: The case of stochastic viability. Reliability Engineering & System Safety, 132, pp. 250–260.
264
Si, X.S., Wang, W., Hu, C.H., Chen, M.Y. and Zhou, D.H., 2013. A Wiener‐process‐based degradation model with a recursive filter algorithm for remaining useful life estimation. Mechanical Systems and Signal Processing, 35(1‐2), pp. 219–237.
265
Liu, B., Xu, Z., Xie, M. and Kuo, W., 2014. A value‐based preventive maintenance policy for multi‐component system with continuously degrading components. Reliability Engineering & System Safety, 132, pp. 83–89.
266
Huang, Z., Xu, Z., Ke, X., Wang, W. and Sun, Y., 2017. Remaining useful life prediction for an adaptive skew‐Wiener process model. Mechanical Systems and Signal Processing, 87, pp. 294–306.
267
Chen, B., Niu, Y. and Zou, Y., 2013. Adaptive sliding mode control for stochastic Markovian jumping systems with actuator degradation. Automatica, 49(6), pp. 1748–1754.
268
Mo, H. and Xie, M., 2015. A dynamic approach to performance analysis and reliability improvement of control systems with degraded components. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(10), pp. 1404–1414.
269
Mo, H. and Xie, M., 2015. A dynamic approach to performance analysis and reliability improvement of control systems with degraded components. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(10), pp. 1404–1414.
270
Rougé, C., Mathias, J.D. and Deffuant, G., 2014. Relevance of control theory to design and maintenance problems in time‐variant reliability: The case of stochastic viability. Reliability Engineering & System Safety, 132, pp. 250–260.
271
Langeron, Y., Grall, A. and Barros, A., 2015. A modeling framework for deteriorating control system and predictive maintenance of actuators. Reliability Engineering & System Safety, 140, pp. 22–36.
272
Langeron, Y., Grall, A. and Barros, A., 2015. A modeling framework for deteriorating control system and predictive maintenance of actuators. Reliability Engineering & System Safety, 140, pp. 22–36.
273
Si, X.S., Wang, W., Hu, C.H., Chen, M.Y. and Zhou, D.H., 2013. A Wiener‐process‐based degradation model with a recursive filter algorithm for remaining useful life estimation. Mechanical Systems and Signal Processing, 35(1‐2), pp. 219–237.
274
Crowder, M. and Lawless, J., 2007. On a scheme for predictive maintenance. European Journal of Operational Research, 176(3), pp. 1713–1722.
275
Huang, Z., Xu, Z., Ke, X., Wang, W. and Sun, Y., 2017. Remaining useful life prediction for an adaptive skew‐Wiener process model. Mechanical Systems and Signal Processing, 87, pp. 294–306.
276
Gebraeel, N.Z., Lawley, M.A., Li, R. and Ryan, J.K., 2005. Residual‐life distributions from component degradation signals: A Bayesian approach. IIE Transactions, 37(6), pp. 543–557.
277
Si, X.S., Wang, W., Hu, C.H., Chen, M.Y. and Zhou, D.H., 2013. A Wiener‐process‐based degradation model with a recursive filter algorithm for remaining useful life estimation. Mechanical Systems and Signal Processing, 35(1‐2), pp. 219–237.
278
Si, X.S., Wang, W., Chen, M.Y., Hu, C.H. and Zhou, D.H., 2013. A degradation path‐dependent approach for remaining useful life estimation with an exact and closed‐form solution. European Journal of Operational Research, 226(1), pp. 53–66.
279
Si, X.S., Wang, W., Hu, C.H. and Zhou, D.H., 2014. Estimating remaining useful life with three‐source variability in degradation modeling. IEEE Transactions on Reliability, 63(1), pp. 167–190.
280
Tang, J. and Su, T.S., 2008. Estimating failure time distribution and its parameters based on intermediate data from a Wiener degradation model. Naval Research Logistics (NRL), 55(3), pp. 265–276.
281
Li, J., Wang, Z., Zhang, Y., Fu, H., Liu, C. and Krishnaswamy, S., 2017. Degradation data analysis based on a generalized Wiener process subject to measurement error. Mechanical Systems and Signal Processing, 94, pp. 57–72.
282
Caballé, N.C., Castro, I.T., Pérez, C.J. and Lanza‐Gutiérrez, J.M., 2015. A condition‐based maintenance of a dependent degradation‐threshold‐shock model in a system with multiple degradation processes. Reliability Engineering & System Safety, 134, pp. 98–109.
283
Caballé, N.C., Castro, I.T., Pérez, C.J. and Lanza‐Gutiérrez, J.M., 2015. A condition‐based maintenance of a dependent degradation‐threshold‐shock model in a system with multiple degradation processes. Reliability Engineering & System Safety, 134, pp. 98–109.
284
Tang, J. and Su, T.S., 2008. Estimating failure time distribution and its parameters based on intermediate data from a Wiener degradation model. Naval Research Logistics (NRL), 55(3), pp. 265–276.
285
Si, X.S., Wang, W., Hu, C.H. and Zhou, D.H., 2011. Remaining useful life estimation–a review on the statistical data driven approaches. European journal of operational research, 213(1), pp. 1–14.
286
Hu, Y., Baraldi, P., Di Maio, F. and Zio, E., 2017. A Systematic Semi‐Supervised Self‐adaptable Fault Diagnostics approach in an evolving environment. Mechanical Systems and Signal Processing, 88, pp. 413–427.
287
Wang, X., 2010. Wiener processes with random effects for degradation data. Journal of Multivariate Analysis, 101(2), pp. 340–351.
288
Ye, Z.S., Chen, N. and Shen, Y., 2015. A new class of Wiener process models for degradation analysis. Reliability Engineering & System Safety, 139, pp. 58–67.
289
Peng, C.Y., 2015. Inverse Gaussian processes with random effects and explanatory variables for degradation data. Technometrics, 57(1), pp. 100–111.
290
Si, X.S., Wang, W., Hu, C.H., Chen, M.Y. and Zhou, D.H., 2013. A Wiener‐process‐based degradation model with a recursive filter algorithm for remaining useful life estimation. Mechanical Systems and Signal Processing, 35(1‐2), pp. 219–237.
291
Si, X.S., Wang, W., Hu, C.H. and Zhou, D.H., 2014. Estimating remaining useful life with three‐source variability in degradation modeling. IEEE Transactions on Reliability, 63(1), pp. 167–190.
292
Hu, Y., Baraldi, P., Di Maio, F. and Zio, E., 2017. A Systematic Semi‐Supervised Self‐adaptable Fault Diagnostics approach in an evolving environment. Mechanical Systems and Signal Processing, 88, pp. 413–427.
293
Wang, X., 2010. Wiener processes with random effects for degradation data. Journal of Multivariate Analysis, 101(2), pp. 340–351.
294
Ye, Z.S., Chen, N. and Shen, Y., 2015. A new class of Wiener process models for degradation analysis. Reliability Engineering & System Safety, 139, pp. 58–67.
295
Peng, C.Y., 2015. Inverse Gaussian processes with random effects and explanatory variables for degradation data. Technometrics, 57(1), pp. 100–111.
296
Bier, V.M., Nagaraj, A. and Abhichandani, V., 2005. Protection of simple series and parallel systems with components of different values. Reliability Engineering & System Safety, 87(3), pp. 315–323.
297
Zhang, C. and Ramirez‐Marquez, J.E., 2013. Protecting critical infrastructures against intentional attacks: A two‐stage game with incomplete information. IIE Transactions, 45(3), pp. 244–258.
298
Nikoofal, M.E. and Zhuang, J., 2015. On the value of exposure and secrecy of defense system: First‐mover advantage vs. robustness. European Journal of Operational Research, 246(1), pp. 320–330.
299
Xu, Z., Ji, Y. and Zhou, D., 2009. A new real‐time reliability prediction method for dynamic systems based on on‐line fault prediction. IEEE transactions on reliability, 58(3), pp. 523–538.
300
Levitin, G. and Hausken, K., 2009. Redundancy vs. protection in defending parallel systems against unintentional and intentional impacts. IEEE transactions on reliability, 58(4), pp. 679–690.
301
Levitin, G. and Hausken, K., 2011. Defense resource distribution between protection and redundancy for constant resource stockpiling pace. Risk Analysis: An International Journal, 31(10), pp. 1632–1645.
302
Ramirez‐Marquez, J.E. and Rocco, C.M., 2012. Vulnerability based robust protection strategy selection in service networks. Computers & Industrial Engineering, 63(1), pp. 235–242.
303
Haphuriwat, N. and Bier, V.M., 2011. Trade‐offs between target hardening and overarching protection. European Journal of Operational Research, 213(1), pp. 320–328.
304
Perea, F. and Puerto, J., 2013. Revisiting a game theoretic framework for the robust railway network design against intentional attacks. European Journal of Operational Research, 226(2), pp. 286–292.
305
Zhuang, J. and Bier, V.M., 2007. Balancing terrorism and natural disasters ‐ Defensive strategy with endogenous attacker effort. Operations Research, 55(5), pp. 976–991.
306
Bilis, E.I., Kröger, W. and Nan, C., 2013. Performance of electric power systems under physical malicious attacks. IEEE Systems Journal, 7(4), pp. 854–865.
307
Levitin, G. and Hausken, K., 2011. Defense resource distribution between protection and redundancy for constant resource stockpiling pace. Risk Analysis: An International Journal, 31(10), pp. 1632–1645.
308
Qiao, J., Jeong, D., Lawley, M., Richard, J.P.P., Abraham, D.M. and Yih, Y., 2007. Allocating security resources to a water supply network. IIE Transactions, 39(1), pp. 95–109.
309
Levitin, G. and Ben‐Haim, H., 2008. Importance of protections against intentional attacks. Reliability Engineering & System Safety, 93(4), pp. 639–646.
310
Hausken, K. and Levitin, G., 2009. Minmax defense strategy for complex multi‐state systems. Reliability Engineering & System Safety, 94(2), pp. 577–587.
311
Hausken, K. and Zhuang, J., 2011. Governments' and terrorists' defense and attack in a T‐period game. Decision Analysis, 8(1), pp. 46–70.
312
Guikema, S.D. and Aven, T., 2010. Assessing risk from intelligent attacks: A perspective on approaches. Reliability Engineering & System Safety, 95(5), pp. 478–483.
313
Hausken, K. and Zhuang, J., 2011. Governments' and terrorists' defense and attack in a T‐period game. Decision Analysis, 8(1), pp. 46–70.
314
Peng, R., Levitin, G., Xie, M. and Ng, S.H., 2010. Defending simple series and parallel systems with imperfect false targets. Reliability Engineering & System Safety, 95(6), pp. 679–688.
315
Levitin, G. and Hausken, K., 2011. Defense resource distribution between protection and redundancy for constant resource stockpiling pace. Risk Analysis: An International Journal, 31(10), pp. 1632–1645.
316
Peng, R., Levitin, G., Xie, M. and Ng, S.H., 2010. Defending simple series and parallel systems with imperfect false targets. Reliability Engineering & System Safety, 95(6), pp. 679–688.
317
Wang, L., Ren, S., Korel, B., Kwiat, K.A. and Salerno, E., 2013. Improving system reliability against rational attacks under given resources. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(4), pp. 446–456.
318
Levitin, G., Hausken, K. and Dai, Y., 2014. Optimal defense with variable number of overarching and individual protections. Reliability Engineering & System Safety, 123, pp. 81–90.
319
Mo, H., Xie, M. and Levitin, G., 2015. Optimal resource distribution between protection and redundancy considering the time and uncertainties of attacks. European Journal of Operational Research, 243(1), pp. 200–210.
320
Bricha, N. and Nourelfath, M., 2013. Critical supply network protection against intentional attacks: A game‐theoretical model. Reliability Engineering & System Safety, 119, pp. 1–10.
321
Zhang, C., Ramirez‐Marquez, J.E. and Wang, J., 2015. Critical infrastructure protection using secrecy–A discrete simultaneous game. European Journal of Operational Research, 242(1), pp. 212–221.
322
Peng, R., Zhai, Q.Q. and Levitin, G., 2016. Defending a single object against an attacker trying to detect a subset of false targets. Reliability Engineering & System Safety, 149, pp. 137–147.
323
Hausken, K. and He, F., 2016. On the effectiveness of security countermeasures for critical infrastructures. Risk Analysis, 36(4), pp. 711–726.
324
Ramirez‐Marquez, J.E., Rocco, C.M. and Levitin, G., 2011. Optimal network protection against diverse interdictor strategies. Reliability Engineering & System Safety, 96(3), pp. 374–382.
325
Peng, R., Levitin, G., Xie, M. and Ng, S.H., 2010. Defending simple series and parallel systems with imperfect false targets. Reliability Engineering & System Safety, 95(6), pp. 679–688.
326
Wang, L., Ren, S., Korel, B., Kwiat, K.A. and Salerno, E., 2013. Improving system reliability against rational attacks under given resources. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 44(4), pp. 446–456.
327
Levitin, G., Hausken, K. and Dai, Y., 2014. Optimal defense with variable number of overarching and individual protections. Reliability Engineering & System Safety, 123, pp. 81–90.
328
Ouyang, M., Zhao, L., Hong, L. and Pan, Z., 2014. Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability. Reliability Engineering & System Safety, 123, pp. 38–46.
329
Xie, G., Hei, X., Mochizuki, H., Takahashi, S. and Nakamura, H., 2014. Safety and reliability estimation of automatic train protection and block system. Quality and Reliability Engineering International, 30(4), pp. 463–472.
330
Xu, Z., Ji, Y. and Zhou, D., 2009. A new real‐time reliability prediction method for dynamic systems based on on‐line fault prediction. IEEE transactions on reliability, 58(3), pp. 523–538.
331
Levitin, G. and Hausken, K., 2009. Redundancy vs. protection in defending parallel systems against unintentional and intentional impacts. IEEE transactions on reliability, 58(4), pp. 679–690.
332
Lee, P., Clark, A., Bushnell, L. and Poovendran, R., 2014. A passivity framework for modeling and mitigating wormhole attacks on networked control systems. IEEE Transactions on Automatic Control, 59(12), pp. 3224–3237.
333
Mitchell, R. and Chen, R., 2015. Modeling and analysis of attacks and counter defense mechanisms for cyber physical systems. IEEE Transactions on Reliability, 65(1), pp. 350–358.
334
Mitchell, R. and Chen, R., 2013. Effect of intrusion detection and response on reliability of cyber physical systems. IEEE Transactions on Reliability, 62(1), pp. 199–210.
335
Almalawi, A., Fahad, A., Tari, Z., Alamri, A., AlGhamdi, R. and Zomaya, A.Y., 2015. An efficient data‐driven clustering technique to detect attacks in SCADA systems. IEEE Transactions on Information Forensics and Security, 11(5), pp. 893–906.
336
Shuang, Q., Zhang, M. and Yuan, Y., 2014. Node vulnerability of water distribution networks under cascading failures. Reliability Engineering & System Safety, 124, pp. 132–141.
337
Ryan, P.C., Stewart, M.G., Spencer, N. and Li, Y., 2014. Reliability assessment of power pole infrastructure incorporating deterioration and network maintenance. Reliability Engineering & System Safety, 132, pp. 261–273.
338
Srikantha, P. and Kundur, D., 2015. A DER attack‐mitigation differential game for smart grid security analysis. IEEE Transactions on Smart Grid, 7(3), pp. 1476–1485.
339
Rocco, C.M., Ramirez‐Marquez, J.E., Salazar, D.E. and Yajure, C., 2011. Assessing the vulnerability of a power system through a multiple objective contingency screening approach. IEEE Transactions on Reliability, 60(2), pp. 394–403.
340
Hausken, K. and Zhuang, J., 2011. Governments' and terrorists' defense and attack in a T‐period game. Decision Analysis, 8(1), pp. 46–70.
