{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,4]],"date-time":"2026-02-04T17:46:31Z","timestamp":1770227191587,"version":"3.49.0"},"publisher-location":"Cham","reference-count":29,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030916985","type":"print"},{"value":"9783030916992","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-91699-2_14","type":"book-chapter","created":{"date-parts":[[2021,11,27]],"date-time":"2021-11-27T05:03:29Z","timestamp":1637989409000},"page":"193-207","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Weapon Engagement Zone Maximum Launch Range Estimation Using a Deep Neural Network"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0300-8027","authenticated-orcid":false,"given":"Joao P. A.","family":"Dantas","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2309-9248","authenticated-orcid":false,"given":"Andre N.","family":"Costa","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1389-9142","authenticated-orcid":false,"given":"Diego","family":"Geraldo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2944-4476","authenticated-orcid":false,"given":"Marcos\u00a0R.\u00a0O.\u00a0A.","family":"Maximo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5375-1076","authenticated-orcid":false,"given":"Takashi","family":"Yoneyama","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,11,28]]},"reference":[{"key":"14_CR1","unstructured":"Air Land Sea Application Center: Brevity: Multi-Service Tactics, Techniques, and Procedures for Multi-Service Brevity Codes (2020)"},{"issue":"10","key":"14_CR2","doi-asserted-by":"publisher","first-page":"1908","DOI":"10.2514\/1.G000776","volume":"38","author":"D Alkaher","year":"2015","unstructured":"Alkaher, D., Moshaiov, A.: Dynamic-escape-zone to avoid energy-bleeding coasting missile. J. Guidance Control Dyn. 38(10), 1908\u20131921 (2015)","journal-title":"J. Guidance Control Dyn."},{"key":"14_CR3","volume-title":"Deep learning","author":"Y Bengio","year":"2017","unstructured":"Bengio, Y., Goodfellow, I., Courville, A.: Deep learning, vol. 1. MIT press Massachusetts, USA (2017)"},{"key":"14_CR4","doi-asserted-by":"crossref","unstructured":"Birkmire, B., Gallagher, J.: Air-to-air missile maximum launch range modeling using a multilayer perceptron. In: AIAA Modeling and Simulation Technologies Conference, p. 4942 (2012)","DOI":"10.2514\/6.2012-4942"},{"key":"14_CR5","doi-asserted-by":"crossref","unstructured":"Birkmire, B.M.: Weapon engagement zone maximum launch range approximation using a multilayer perceptron. Master\u2019s thesis, Wright State University (2011)","DOI":"10.2514\/6.2012-4942"},{"key":"14_CR6","doi-asserted-by":"crossref","unstructured":"Bock, S., Wei\u00df, M.: A proof of local convergence for the Adam optimizer. In: 2019 International Joint Conference on Neural Networks (IJCNN), pp. 1\u20138. IEEE (2019)","DOI":"10.1109\/IJCNN.2019.8852239"},{"key":"14_CR7","unstructured":"Bonaccorso, G.: Machine Learning Algorithms. Packt Publishing Ltd, Birmingham (2017)"},{"key":"14_CR8","doi-asserted-by":"publisher","unstructured":"Cai, G., Chen, B.M., Lee, T.H.: Coordinate Systems and Transformations. In: Unmanned Rotorcraft Systems, pp. 23\u201334. Springer, London (2011). https:\/\/doi.org\/10.1007\/978-0-85729-635-1_2","DOI":"10.1007\/978-0-85729-635-1_2"},{"key":"14_CR9","unstructured":"Costa, A.N.: Sequential Optimization of Formation Flight Control Method Based on Artificial Potential Fields. Master\u2019s Thesis, Instituto Tecnol\u00f3gico de Aeron\u00e1utica, S\u00e3o Jos\u00e9 dos Campos, SP, Brazil (2019)"},{"key":"14_CR10","doi-asserted-by":"crossref","unstructured":"Dantas, J.P.A., Costa, A.N., Geraldo, D., Maximo, M.R.A.O., Yoneyama, T.: Engagement decision support for beyond visual range air combat. In: 2021 Latin American Robotics Symposium (LARS), pp. 1\u20136 (2021), Accepted for publication","DOI":"10.1109\/LARS\/SBR\/WRE54079.2021.9605380"},{"key":"14_CR11","unstructured":"Dantas, J.P.A.: Apoio \u00e0 decis\u00e3o para o combate a\u00e9reo al\u00e9m do alcance visual: uma abordagem por redes neurais artificiais. Master\u2019s Thesis, Instituto Tecnol\u00f3gico de Aeron\u00e1utica, S\u00e3o Jos\u00e9 dos Campos, SP, Brazil (2018)"},{"key":"14_CR12","unstructured":"Departament of Defense: Military Handbook: Missile Flight Simulation Part One: Surface-to-Air Missiles (MIL-HDBK-1211) (1995)"},{"issue":"3","key":"14_CR13","doi-asserted-by":"publisher","first-page":"763","DOI":"10.1016\/j.jspi.2011.09.016","volume":"142","author":"JL Deutsch","year":"2012","unstructured":"Deutsch, J.L., Deutsch, C.V.: Latin hypercube sampling with multidimensional uniformity. J. Stat. Planning Infer. 142(3), 763\u2013772 (2012)","journal-title":"J. Stat. Planning Infer."},{"key":"14_CR14","doi-asserted-by":"crossref","unstructured":"Farlik, J., Casar, J., Stary, V.: Simplification of missile effective coverage zone in air defence simulations. In: 2017 International Conference on Military Technologies (ICMT), pp. 733\u2013737. IEEE (2017)","DOI":"10.1109\/MILTECHS.2017.7988853"},{"key":"14_CR15","doi-asserted-by":"crossref","unstructured":"Hancock, P.A., Vincenzi, D.A., Wise, J.A., Mouloua, M.: Human Factors in Simulation and Training. CRC Press, Boca Raton (2008)","DOI":"10.1201\/9781420072846"},{"key":"14_CR16","doi-asserted-by":"crossref","unstructured":"Hill, R.R., Miller, J.O., McIntyre, G.A.: Applications of discrete event simulation modeling to military problems. In: Proceeding of the 2001 Winter Simulation Conference (Cat. No. 01CH37304), vol. 1, pp. 780\u2013788. IEEE (2001)","DOI":"10.1109\/WSC.2001.977367"},{"issue":"1","key":"14_CR17","first-page":"56","volume":"19","author":"T Homem-de-Mello","year":"2014","unstructured":"Homem-de-Mello, T., Bayraksan, G.: Monte carlo sampling-based methods for stochastic optimization. Surv. Oper. Res. Manage. Sci. 19(1), 56\u201385 (2014)","journal-title":"Surv. Oper. Res. Manage. Sci."},{"issue":"4","key":"14_CR18","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/s11081-010-9129-8","volume":"12","author":"BG Husslage","year":"2011","unstructured":"Husslage, B.G., Rennen, G., Van Dam, E.R., Den Hertog, D.: Space-filling Latin hypercube designs for computer experiments. Optim. Eng. 12(4), 611\u2013630 (2011)","journal-title":"Optim. Eng."},{"issue":"3","key":"14_CR19","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1080\/10618600.1996.10474713","volume":"5","author":"R Ihaka","year":"1996","unstructured":"Ihaka, R., Gentleman, R.: R: a language for data analysis and graphics. J. Comput. Graph. Stat. 5(3), 299\u2013314 (1996)","journal-title":"J. Comput. Graph. Stat."},{"key":"14_CR20","unstructured":"Kingma, D.P., Ba, J.: Adam: a method for stochastic optimization. arXiv preprint arXiv:1412.6980 (2014)"},{"key":"14_CR21","doi-asserted-by":"crossref","unstructured":"Klee, H.: Simulation of Dynamic Systems with MATLAB and Simulink. CRC Press, Boca Raton (2018)","DOI":"10.1201\/9781420044195"},{"key":"14_CR22","unstructured":"Kravchenko, M.: Future UI. https:\/\/br.pinterest.com\/krava88\/future-ui\/. Accessed 06 Nov 2021"},{"key":"14_CR23","doi-asserted-by":"crossref","unstructured":"Li, A., Meng, Y., He, Z.: Simulation research on new model of air-to-air missile attack zone. In: 2020 IEEE 4th Information Technology, Networking, Electronic and Automation Control Conference (ITNEC), vol. 1, pp. 1998\u20132002. IEEE (2020)","DOI":"10.1109\/ITNEC48623.2020.9084793"},{"issue":"2","key":"14_CR24","first-page":"5070","volume":"7","author":"D Noaman","year":"2020","unstructured":"Noaman, D., Noaman, M., Mahir, D., Rami, A., Faiz, D., et al.: Boost-sustain missile motor performance with fixed predetermined coast time interval. Eur. J. Mol. Clin. Med. 7(2), 5070\u20135079 (2020)","journal-title":"Eur. J. Mol. Clin. Med."},{"key":"14_CR25","unstructured":"Office of the Chairman of the Joint Chiefs of Staff, Washington DC: DOD Dictionary of Military and Associated Terms (2021)"},{"key":"14_CR26","unstructured":"Petneh\u00e1zi, G.: Recurrent neural networks for time series forecasting. arXiv preprint arXiv:1901.00069 (2019)"},{"key":"14_CR27","unstructured":"Portrey, A.M., Schreiber, B., Winston, B.: The pairwise escape-g metric: a measure for air combat maneuvering performance. In: Proceedings of the Winter Simulation Conference, 2005. p. 8. IEEE (2005)"},{"key":"14_CR28","doi-asserted-by":"crossref","unstructured":"Priddy, K.L., Keller, P.E.: Artificial Neural Networks: an Introduction, vol. 68. SPIE Press, Bellingham (2005)","DOI":"10.1117\/3.633187"},{"key":"14_CR29","doi-asserted-by":"crossref","unstructured":"Yoon, K.S., Park, J.H., Kim, I.G., Ryu, K.S.: New modeling algorithm for improving accuracy of weapon launch acceptability region. In: 29th Digital Avionics Systems Conference, p. 6-D. IEEE (2010)","DOI":"10.1109\/DASC.2010.5655454"}],"container-title":["Lecture Notes in Computer Science","Intelligent Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-91699-2_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,13]],"date-time":"2024-09-13T03:47:36Z","timestamp":1726199256000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-91699-2_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030916985","9783030916992"],"references-count":29,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-91699-2_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"28 November 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BRACIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Brazilian Conference on Intelligent Systems","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 November 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bracis2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/c4ai.inova.usp.br\/bracis\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"JEMS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"192","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":"77","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":"0","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":"40% - 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":"3.1","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Due to COVID-19, the conference was held as an online event.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}