{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,30]],"date-time":"2026-01-30T08:09:41Z","timestamp":1769760581406,"version":"3.49.0"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319192215","type":"print"},{"value":"9783319192222","type":"electronic"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1007\/978-3-319-19222-2_46","type":"book-chapter","created":{"date-parts":[[2015,6,5]],"date-time":"2015-06-05T03:01:02Z","timestamp":1433473262000},"page":"549-563","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":23,"title":["A New Method for an Optimal SOM Size Determination in Neuro-Fuzzy for the Digital Forensics Applications"],"prefix":"10.1007","author":[{"given":"Andrii","family":"Shalaginov","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katrin","family":"Franke","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2015,6,6]]},"reference":[{"issue":"3","key":"46_CR1","doi-asserted-by":"publisher","first-page":"1203","DOI":"10.3982\/ECTA8968","volume":"81","author":"SC Ahn","year":"2013","unstructured":"Ahn, S.C., Horenstein, A.R.: Eigenvalue ratio test for the number of factors. Econometrica 81(3), 1203\u20131227 (2013)","journal-title":"Econometrica"},{"issue":"3","key":"46_CR2","doi-asserted-by":"publisher","first-page":"601","DOI":"10.1109\/72.846732","volume":"11","author":"D Alahakoon","year":"2000","unstructured":"Alahakoon, D., Halgamuge, S., Srinivasan, B.: Dynamic self-organizing maps with controlled growth for knowledge discovery. IEEE Transactions on Neural Networks 11(3), 601\u2013614 (2000)","journal-title":"IEEE Transactions on Neural Networks"},{"key":"46_CR3","doi-asserted-by":"crossref","unstructured":"Alahakoon, D., Halgamuge, S., Srinivasan, B.: A self-growing cluster development approach to data mining. In: 1998 IEEE International Conference on Systems, Man, and Cybernetics, vol. 3, pp. 2901\u20132906, October 1998","DOI":"10.1109\/ICSMC.1998.725103"},{"key":"46_CR4","unstructured":"Alonso, J.M., Cordn, O., Quirin, A., Magdalena, L.: Analyzing interpretability of fuzzy rule-based systems by means of fuzzy inference-grams. In: World Congress on Soft Computing (2011)"},{"key":"46_CR5","doi-asserted-by":"crossref","unstructured":"Altyeb Altaher, A.A., Ramadass, S.: Application of adaptive neuro-fuzzy inference system for information secuirty. Journal of Computer Science 8(6), 983\u2013986 (2012)","DOI":"10.3844\/jcssp.2012.983.986"},{"key":"46_CR6","unstructured":"Baltimore, R.: An Analytic investigation into self organizing maps and their network topologies. Ph.D. thesis, Rochester Institute of Technology (2010)"},{"key":"46_CR7","unstructured":"Castellano, G., Fanelli, A.M., Mencar, C.: Discovering interpretable classification rules from neural processed data (2002)"},{"key":"46_CR8","doi-asserted-by":"crossref","unstructured":"Chattopadhyay, M., Dan, P.K., Mazumdar, S.: Application of visual clustering properties of self organizing map in machine-part cell formation. Appl. Soft Comput. 12(2), 600\u2013610 (2012). http:\/\/dx.doi.org\/10.1016\/j.asoc.2011.11.004","DOI":"10.1016\/j.asoc.2011.11.004"},{"key":"46_CR9","unstructured":"Clark, M.: A comparison of correlation measures. University of Notre Dame, Tech. rep. (2013)"},{"key":"46_CR10","doi-asserted-by":"crossref","unstructured":"Dickerson, J.A., Kosko, B.: Fuzzy function approximation with ellipsoidal rules. Trans. Sys. Man Cyber. Part B 26(4), 542\u2013560 (1996). http:\/\/dx.doi.org\/10.1109\/3477.517030","DOI":"10.1109\/3477.517030"},{"key":"46_CR11","doi-asserted-by":"crossref","unstructured":"Est\u00e9vez, P., Pr\u00edncipe, J., Zegers, P.: Advances in Self-Organizing Maps: 9th International Workshop, WSOM 2012. AISC, vol. 198. Springer, Heidelberg (2012). https:\/\/books.google.no\/books?id=vHgnfKFpIFUC","DOI":"10.1007\/978-3-642-35230-0"},{"key":"46_CR12","unstructured":"Feldman, E.R.: Criteria for admissibility of expert opinion testimony under daubert and its progeny. Tech. rep, Cozen OConnor (2001)"},{"key":"46_CR13","doi-asserted-by":"crossref","unstructured":"Gacto, M., Alcal, R., Herrera, F.: Interpretability of linguistic fuzzy rule-based systems: An overview of interpretability measures. Information Sciences 181(20), 4340\u20134360 (2011). http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0020025511001034, special Issue on Interpretable Fuzzy Systems","DOI":"10.1016\/j.ins.2011.02.021"},{"key":"46_CR14","doi-asserted-by":"crossref","unstructured":"Guarino, A.: Digital forensics as a big data challenge. In: ISSE 2013 Securing Electronic Business Processes, pp. 197\u2013203. Springer (2013)","DOI":"10.1007\/978-3-658-03371-2_17"},{"key":"46_CR15","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1155\/2011\/121787","volume":"2011","author":"S Hasan","year":"2011","unstructured":"Hasan, S., Shamsuddin, S.M.: Multistrategy self-organizing map learning for classification problems. Computational Intelligence and Neuroscience 2011, 11 (2011)","journal-title":"Computational Intelligence and Neuroscience"},{"key":"46_CR16","doi-asserted-by":"crossref","unstructured":"Herrera, L., Pomares, H., Rojas, I., Valenzuela, O., Prieto, A.: Tase, a taylor series-based fuzzy system model that combines interpretability and accuracy. Fuzzy Sets and Systems 153(3), 403\u2013427 (2005). http:\/\/www.sciencedirect.com\/science\/article\/pii\/S0165011405000333","DOI":"10.1016\/j.fss.2005.01.012"},{"key":"46_CR17","unstructured":"Ishibuchi, H., Nojima, Y.: Discussions on interpretability of fuzzy systems using simple examples (2009)"},{"issue":"2","key":"46_CR18","doi-asserted-by":"publisher","first-page":"212","DOI":"10.1109\/91.842154","volume":"8","author":"Y Jin","year":"2000","unstructured":"Jin, Y.: Fuzzy modeling of high-dimensional systems: complexity reduction and interpretability improvement. IEEE Transactions on Fuzzy Systems 8(2), 212\u2013221 (2000)","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"46_CR19","unstructured":"Kosko, B.: Fuzzy Engineering. No. v. 1 in Fuzzy Engineering. Prentice Hall (1997). http:\/\/books.google.no\/books?id=8QwoAQAAMAAJ"},{"key":"46_CR20","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1088\/0004-637X\/781\/1\/39","volume":"781","author":"E Mart\u00ednez-G\u00f3mez","year":"2014","unstructured":"Mart\u00ednez-G\u00f3mez, E., Richards, M.T., Richards, D.S.P.: Distance correlation methods for discovering associations in large astrophysical databases. The Astrophysical Journal 781, 39 (2014)","journal-title":"The Astrophysical Journal"},{"key":"46_CR21","doi-asserted-by":"crossref","unstructured":"Piegat, A.: Fuzzy Modeling and Control. STUDFUZZ, vol. 69. Physica-Verlag, Heidelberg (2001). http:\/\/books.google.no\/books?id=329oSfh-vxsC","DOI":"10.1007\/978-3-7908-1824-6"},{"key":"46_CR22","doi-asserted-by":"crossref","unstructured":"Fei Qiao, J., Gui Han, H.: An Adaptive Fuzzy Neural Network Based on Self-Organizing Map (SOM). INFTECH, April 2010, iSBN 978-953-307-074-2","DOI":"10.5772\/9158"},{"key":"46_CR23","unstructured":"Schmidt, C.R.: Effect of irregular topology in shperical Self-Organizing Maps. Ph.D. thesis, San Diego State University (December 2008)"},{"key":"46_CR24","unstructured":"Singh, R., Kumar, H., Singla, R.: Review of soft computing in malware detection. Special Issues on IP Multimedia Communications (1), 55\u201360 (2011), full text available"},{"key":"46_CR25","unstructured":"Smith, L.I.: A tutorial on principal components analysis. Tech. rep., Cornell University, USA (February 26, 2002). http:\/\/www.cs.otago.ac.nz\/cosc453\/student_tutorials\/principal_components.pdf"},{"key":"46_CR26","unstructured":"Szkely, J., Rizzo, M.L., Bakirov, N.K.: Measuring and testing dependence by correlation of distances"},{"key":"46_CR27","doi-asserted-by":"crossref","unstructured":"Vesanto, J., Alhoniemi, E.: Clustering of the self-organizing map (2000)","DOI":"10.1109\/72.846731"},{"key":"46_CR28","unstructured":"Vesanto, J., Himberg, J., Alhoniemi, E., Parhankangas, J.: Self-organizing map in matlab: the som toolbox. In: Proceedings of the Matlab DSP Conference, pp. 35\u201340 (2000)"},{"key":"46_CR29","unstructured":"Zhang, Y. (ed.) Machine Learning. INFTECH (February 2010), isbn 978-953-307-033-9"}],"container-title":["Lecture Notes in Computer Science","Advances in Computational Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-19222-2_46","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,28]],"date-time":"2025-05-28T10:27:36Z","timestamp":1748428056000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-19222-2_46"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319192215","9783319192222"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-19222-2_46","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"6 June 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}