{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T15:30:37Z","timestamp":1778167837599,"version":"3.51.4"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031159336","type":"print"},{"value":"9783031159343","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-3-031-15934-3_45","type":"book-chapter","created":{"date-parts":[[2022,9,6]],"date-time":"2022-09-06T00:02:53Z","timestamp":1662422573000},"page":"544-555","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Analytical Comparison Between the Pattern Classifiers Based upon a Multilayered Perceptron and Probabilistic Neural Network in Parallel Implementation"],"prefix":"10.1007","author":[{"given":"Katsumi","family":"Takahashi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shunpei","family":"Morita","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tetsuya","family":"Hoya","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,15]]},"reference":[{"key":"45_CR1","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y., Hinton, G.: Deep learning. Nature 521, 436\u2013444 (2015)","journal-title":"Nature"},{"key":"45_CR2","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.neunet.2014.09.003","volume":"61","author":"J Schmidhuber","year":"2015","unstructured":"Schmidhuber, J.: Deep learning in neural networks: an overview. Neural Netw. 61, 85\u2013117 (2015)","journal-title":"Neural Netw."},{"key":"45_CR3","doi-asserted-by":"publisher","first-page":"318","DOI":"10.7551\/mitpress\/5236.001.0001","volume-title":"Parallel Distributed Processing","author":"DE Rumelhart","year":"1986","unstructured":"Rumelhart, D.E., Hinton, G.E., Williams, R.J.: Learning internal representations by error propagation. In: Rumelhart, D.E., McClelland, J.L. (eds.) Parallel Distributed Processing, vol. 1, pp. 318\u2013362. MIT Press, Cambridge (1986)"},{"key":"45_CR4","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1016\/0893-6080(90)90049-Q","volume":"3","author":"DF Specht","year":"1990","unstructured":"Specht, D.F.: Probabilistic neural networks. Neural Netw. 3, 109\u2013118 (1990)","journal-title":"Neural Netw."},{"key":"45_CR5","doi-asserted-by":"crossref","unstructured":"Azema-Barac, M.E.: A conceptual framework for implementing neural networks on massively parallel machines. In: 6th International Parallel Processing Symposium, pp. 527\u2013530 (1992)","DOI":"10.1109\/IPPS.1992.222973"},{"key":"45_CR6","unstructured":"Pethick, M., Liddle, M., Werstein, P., Huang, Z., Parallelization of a backpropagation neural network on a cluster computer. In: 15th IASTED International Conference on Parallel and Distributed Computing and Systems, CA, USA, pp. 574\u2013582. ACTA Press (2003)"},{"issue":"1","key":"45_CR7","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1109\/TPDS.2005.11","volume":"16","author":"S Suresh","year":"2005","unstructured":"Suresh, S., Omkar, S.N., Mani, V.: Parallel implementation of back-propagation algorithm in networks of workstations. IEEE Trans. Parallel Distrib. Syst. 16(1), 24\u201334 (2005)","journal-title":"IEEE Trans. Parallel Distrib. Syst."},{"key":"45_CR8","doi-asserted-by":"crossref","unstructured":"Turchenko, V., Golovko, V.: Parallel batch pattern training algorithm for deep neural network. In: International Conference on High Performance Computing & Simulation (HPCS), pp. 697\u2013702 (2014)","DOI":"10.1109\/HPCSim.2014.6903757"},{"key":"45_CR9","doi-asserted-by":"crossref","unstructured":"Secretan, J., Georgiopoulos, M., Maidhof, I., Shibly, P., Hecker, J.: Methods for parallelizing the probabilistic neural network on a Beowulf cluster computer. In: IEEE International Joint Conference on Neural Network, pp. 2378\u20132385 (2006)","DOI":"10.1109\/IJCNN.2006.247062"},{"key":"45_CR10","unstructured":"Bastke, S., Deml, M., Schmidt, S.: Combining statistical network data, probabilistic neural networks and the computational power of GPUs for anomaly detection in computer networks. In: 19th International Conference on Automated Planning and Scheduling, Workshop on Intelligent Security (SecArt 2009), Thessaloniki, Greece (2009)"},{"key":"45_CR11","doi-asserted-by":"crossref","unstructured":"Kokkinos, Y., Margaritis, K.: A parallel radial basis probabilistic neural network for scalable data mining in distributed memory machines. In: IEEE 24th International Conference on Tools with Artificial Intelligence, pp. 1094\u20131099 (2012)","DOI":"10.1109\/ICTAI.2012.155"},{"key":"45_CR12","doi-asserted-by":"crossref","unstructured":"Phaudphut, C., So-In, C., Phusomsai, W.: A parallel probabilistic neural network ECG recognition architecture over GPU platforms. In: 13th International Joint Conference on Computer Science and Software Engineering (JCSSE), pp. 1\u20137 (2016)","DOI":"10.1109\/JCSSE.2016.7748842"},{"key":"45_CR13","unstructured":"MacQueen, J.B.: Some methods for classification and analysis of multivariate observations. In: 5th Berkeley Symposium on Mathematical Statistics and Probability, pp. 281\u2013297 (1967)"},{"key":"45_CR14","doi-asserted-by":"crossref","unstructured":"Chen, S., Grant, P.M., Cowan, C.F.N.: Orthogonal least squares algorithm for training multi-output radial basis function networks. In: Second International Conference on Artificial Neural Networks, pp. 336\u2013339 (1991)","DOI":"10.1109\/72.80341"},{"key":"45_CR15","doi-asserted-by":"crossref","unstructured":"Bessrour, M., Elouedi, Z., Lefevre, E.: E-DBSCAN: an evidential version of the DBSCAN method. In: IEEE Symposium - Series on Computational Intelligence (SSCI-2020), pp. 3073\u20133080 (2020)","DOI":"10.1109\/SSCI47803.2020.9308578"},{"issue":"3","key":"45_CR16","doi-asserted-by":"publisher","first-page":"442","DOI":"10.1109\/TETCI.2019.2961190","volume":"5","author":"W Luo","year":"2021","unstructured":"Luo, W., Zhu, W., Ni, L., Qiao, Y., Yuan, Y.: SCA2: novel efficient swarm clustering algorithm. IEEE Trans. Emerg. Top. Comput. Intell. 5(3), 442\u2013456 (2021)","journal-title":"IEEE Trans. Emerg. Top. Comput. Intell."},{"issue":"1","key":"45_CR17","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/s00500-016-2382-9","volume":"21","author":"M Kusy","year":"2016","unstructured":"Kusy, M., Kluska, J.: Assessment of prediction ability for reduced probabilistic neural network in data classification problems. Soft Comput. 21(1), 199\u2013212 (2016). https:\/\/doi.org\/10.1007\/s00500-016-2382-9","journal-title":"Soft Comput."},{"key":"45_CR18","unstructured":"Dua D., Graff, G.: UCI machine learning repository, School of Information and Computer Sciences, Univ. California Irvine, Irvine, CA (2019). https:\/\/archive.ics.uci.edu\/ml"},{"key":"45_CR19","unstructured":"LeCun, Y., Cortes, C., Burges, C.J.C.: The MNIST database. http:\/\/yann.lecun.com\/exdb\/mnist\/. Accessed Jan 2022"},{"key":"45_CR20","unstructured":"Kingma, D., Lei Ba, J.: Adam: a method for stochastic optimization. In: Third International Conference on Learning Representations, San Diego, arXiv:1412.6980 (2015)"},{"key":"45_CR21","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., et al.: Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825\u20132830 (2011)","journal-title":"J. Mach. Learn. Res."}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2022"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-15934-3_45","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,3]],"date-time":"2024-10-03T07:37:13Z","timestamp":1727941033000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-15934-3_45"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031159336","9783031159343"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-15934-3_45","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"15 September 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICANN","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial Neural Networks","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Bristol","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"United Kingdom","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"6 September 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"9 September 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"31","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icann2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/e-nns.org\/icann2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"561","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"255","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"45% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}