{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,5]],"date-time":"2024-09-05T15:53:29Z","timestamp":1725551609930},"publisher-location":"Berlin, Heidelberg","reference-count":24,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540304623"},{"type":"electronic","value":"9783540316527"}],"license":[{"start":{"date-parts":[[2005,1,1]],"date-time":"2005-01-01T00:00:00Z","timestamp":1104537600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2005]]},"DOI":"10.1007\/11589990_119","type":"book-chapter","created":{"date-parts":[[2005,11,26]],"date-time":"2005-11-26T01:28:03Z","timestamp":1132968483000},"page":"954-958","source":"Crossref","is-referenced-by-count":0,"title":["A Comparative Study for Assessing the Reliability of Complex Networks Using Rules Extracted from Different Machine Learning Approaches"],"prefix":"10.1007","author":[{"given":"Douglas E.","family":"Torres D.","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Claudio M.","family":"Rocco S.","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"119_CR1","unstructured":"Jacobsen, H.A.: A Generic Architecture for Hybrid Intelligent Systems. In: IEEE Fuzzy Systems IEEE Fuzzy Systems, Anchorage, Alaska (1998)"},{"key":"119_CR2","volume-title":"Fusion of Neural Networks, Fuzzy Sets, and Genetic Algorithms, Industrial Applications","author":"L.C. Jain","year":"1998","unstructured":"Jain, L.C., Martin, N.M.: Fusion of Neural Networks, Fuzzy Sets, and Genetic Algorithms, Industrial Applications. CRC Press, Boca Raton (1998)"},{"key":"119_CR3","unstructured":"http:\/\/www.comp.nus.edu.sg\/~pris\/HybridSystems\/DescriptionDetailed1.html"},{"key":"119_CR4","unstructured":"Craven, M.W.: Extracting Comprehensible Models from Trained Neural Networks. Ph.D. Thesis. University of Wisconsin- Madison (1996)"},{"key":"119_CR5","unstructured":"http:\/\/www.biostat.wisc.edu\/~craven\/"},{"key":"119_CR6","volume-title":"A Computational Approach to Learning and Machine Intelligence","author":"J.S. Jang","year":"1997","unstructured":"Jang, J.S., Sun, C.T.: Neuro-Fuzzy and Soft Computing. In: A Computational Approach to Learning and Machine Intelligence. Prentice Hall, NJ (1997)"},{"key":"119_CR7","doi-asserted-by":"publisher","first-page":"202","DOI":"10.1137\/S0036144596306782","volume":"40","author":"N. Lynn","year":"1998","unstructured":"Lynn, N., Singpurwalla, N.: Bayesian assessment of network reliability. SIAM Review\u00a040, 202\u2013227 (1998)","journal-title":"SIAM Review"},{"key":"119_CR8","doi-asserted-by":"crossref","DOI":"10.1007\/978-1-4899-0685-4","volume-title":"Reliability Evaluation of Engineering Systems, Concepts and Techniques","author":"R. Billinton","year":"1992","unstructured":"Billinton, R., Allan, R.: Reliability Evaluation of Engineering Systems, Concepts and Techniques, 2nd edn. Plenum Press, New York (1992)","edition":"2"},{"key":"119_CR9","unstructured":"Marseguerra, M., Zio, E.: Basics of the Monte Carlo Method with Application to System Reliability. LiLoLe-Verlag GmbH (Publ. Co. Ltd.) (2002)"},{"key":"119_CR10","unstructured":"Grimaldi, R.P., Shier, D.R.: Redundancy and reliability of communication networks, \n                    \n                      www.math.clemson.edu\/~shierd\/Shier\/abstracts\/randr.html"},{"key":"119_CR11","volume-title":"Combinatorial Algorithms: Theory and Practice","author":"E. Reingold","year":"1977","unstructured":"Reingold, E., Nievergelt, J., Deo, N.: Combinatorial Algorithms: Theory and Practice. Prentice Hall, New Jersey (1977)"},{"key":"119_CR12","volume-title":"Combinatorial Optimization: Algorithms and Complexity","author":"C.H. Papadimitriou","year":"1982","unstructured":"Papadimitriou, C.H., Steiglitz, K.: Combinatorial Optimization: Algorithms and Complexity. Prentice Hall, New Jersey (1982)"},{"key":"119_CR13","unstructured":"Foresee, F.D., Hagan, M.T.: Gauss-Newton Approximation to Bayesian Regularization. In: Proc. of IJCNN 1997 (1997)"},{"key":"119_CR14","first-page":"273","volume":"20","author":"C. Cortes","year":"1995","unstructured":"Cortes, C., Vapnik, V.: SVM. Machine Learning\u00a020, 273\u2013297 (1995)","journal-title":"Machine Learning"},{"key":"119_CR15","volume-title":"Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems","author":"C.T. Lin","year":"1996","unstructured":"Lin, C.T., Lee, C.S.G.: Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to Intelligent Systems. Prentice-Hall, NJ (1996)"},{"key":"119_CR16","unstructured":"http:\/\/divcom.otago.ac.nz\/infoscie\/kel\/cbiis.htm"},{"key":"119_CR17","unstructured":"Trepan \u2013 Matlab, Available at \n                    \n                      http:\/\/www.cmdmport.ac.uk\/biomine"},{"key":"119_CR18","unstructured":"MathWorks, MatLab 6.5 R13 (2002)"},{"key":"119_CR19","unstructured":"Kasabov, N.: Investigating the Adaptation and Forgetting in Fuzzy Neural Networks Through a Method of Training and Zeroing. In: ICNN 1996, pp. 118\u2013123 (1996)"},{"issue":"2","key":"119_CR20","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1109\/24.3743","volume":"37","author":"Y.B. Yoo","year":"1988","unstructured":"Yoo, Y.B., Deo, N.: A Comparison of Algorithm for Terminal-Pair Relia- bility. IEEE Transaction on Reliability\u00a037(2), 210\u2013215 (1988)","journal-title":"IEEE Transaction on Reliability"},{"key":"119_CR21","unstructured":"Veropoulos, K., Camppbell, C.N.: Controlling the Sensitivity of Support Vector Machines. In: Proceedings of the IJCAI 1999 (1999)"},{"key":"119_CR22","unstructured":"Cawley, G.C.: MATLAB Support Vector Machine Toolbox v. 0.54. University of East Anglia, Norwich, U.K, Available at \n                    \n                      http:\/\/theoval.sys.uea.ac.uk\/~gcc\/svm\/toolbox"},{"key":"119_CR23","unstructured":"Hsu, C.-W., Chang, C.-C., Lin, C.-J.: A Practical Guide to Support Vector Classification, Available at \n                    \n                      http:\/\/www.csie.ntu.edu.tw\/~cjlin\/papers\/guide\/guide.pdf"},{"key":"119_CR24","doi-asserted-by":"publisher","first-page":"301","DOI":"10.1016\/j.ress.2003.10.001","volume":"83","author":"C. Rocco","year":"2004","unstructured":"Rocco, C., Muselli, M.: Empirical models based on machine learning techniques for determining ARE. Reliability Engineering and Safety S\u00a083, 301\u2013309 (2004)","journal-title":"Reliability Engineering and Safety S"}],"container-title":["Lecture Notes in Computer Science","AI 2005: Advances in Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/11589990_119","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,19]],"date-time":"2019-05-19T14:05:24Z","timestamp":1558274724000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/11589990_119"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2005]]},"ISBN":["9783540304623","9783540316527"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/11589990_119","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2005]]}}}