{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:13:27Z","timestamp":1742912007735,"version":"3.40.3"},"publisher-location":"Cham","reference-count":9,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030039271"},{"type":"electronic","value":"9783030039288"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"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":[[2018]]},"DOI":"10.1007\/978-3-030-03928-8_41","type":"book-chapter","created":{"date-parts":[[2018,11,8]],"date-time":"2018-11-08T11:21:01Z","timestamp":1541676061000},"page":"507-517","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Storm Runoff Prediction Using Rainfall Radar Map Supported by Global Optimization Methodology"],"prefix":"10.1007","author":[{"given":"Yoshitomo","family":"Yonese","sequence":"first","affiliation":[]},{"given":"Akira","family":"Kawamura","sequence":"additional","affiliation":[]},{"given":"Hideo","family":"Amaguchi","sequence":"additional","affiliation":[]}],"member":"297","reference":[{"key":"41_CR1","doi-asserted-by":"crossref","unstructured":"Tsuchiya, S., Kawasaki, M., Godo, H.: Improvement of the radar rainfall accuracy of XRAIN by modifying of rainfall attenuation correction and compositing radar rainfall. J. Jpn. Soc. Civ. Eng. Ser. B1 (Hydraul. Eng.) 71(4), I_457\u2013I_462 (2015)","DOI":"10.2208\/jscejhe.71.I_457"},{"key":"41_CR2","doi-asserted-by":"crossref","unstructured":"Yonese, Y., Kawamura, A., Amaguchi, H., Tonotsuka, A.: Precision evaluation of X-band MP radar rainfall in a small urban watershed by comparison to 1-minute ground observation rainfall data. J. Jpn. Soc. Civ. Eng. Ser. B1 (Hydraul. Eng.) 72(4), I_217\u2013I_222 (2016)","DOI":"10.2208\/jscejhe.72.I_217"},{"key":"41_CR3","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1007\/BF00939380","volume":"76","author":"QY Duan","year":"1993","unstructured":"Duan, Q.Y., Gupta, V.K., Sorooshian, S.: Shuffled complex evolution approach for effective and efficient global minimization. J. Optim. Theory Appl. 76, 501\u2013521 (1993). https:\/\/doi.org\/10.1007\/BF00939380","journal-title":"J. Optim. Theory Appl."},{"key":"41_CR4","doi-asserted-by":"crossref","unstructured":"Yonese, Y., Kawamura, A., Amaguchi, H., Tonotsuka, A.: Spatiotemporal charactaristic analysis of X-band MP radar rainfall in a small urban watershed focused on the movement of rainfall area. J. Jpn. Soc. Civ. Eng. Ser. B1 (Hydraul. Eng.) 73(4), I_217\u2013I_222 (2017)","DOI":"10.2208\/jscejhe.73.I_217"},{"issue":"3","key":"41_CR5","first-page":"217","volume":"65","author":"T Takasaki","year":"2009","unstructured":"Takasaki, T., Kawamura, A., Amaguchi, H., Araki, K.: New storage function model considering urban runoff process. J. Jpn. Soc. Civ. Eng. Ser. B 65(3), 217\u2013230 (2009)","journal-title":"J. Jpn. Soc. Civ. Eng. Ser. B"},{"key":"41_CR6","unstructured":"Kawamura, A., Morinaga, Y., Jinno, K., Dandy, G.C.: The comparison of runoff prediction accuracy among the various storage function models with loss mechanisms. In: Proceedings of the 2nd Asia Pacific Association of Hydrology and Water Resources Conference, vol. II, pp. 43\u201350 (2004)"},{"key":"41_CR7","unstructured":"Tanakamaru, H., Burges, S.J.: Application of global optimization to parameter estimation of the tank model. In: Proceedings of the International Conference on Water Resources and Environment Research, vol. II, pp. 39\u201346 (1996)"},{"key":"41_CR8","doi-asserted-by":"publisher","first-page":"657","DOI":"10.1016\/j.jhydrol.2018.06.035","volume":"563","author":"PG Saritha","year":"2018","unstructured":"Saritha, P.G., Akira, K., Tadakatsu, T., Hideo, A., Gubash, A.: An effective storage function model for an urban watershed in terms of hydrograph reproducibility and Akaike information criterion. J. Hydrol. 563, 657\u2013668 (2018)","journal-title":"J. Hydrol."},{"key":"41_CR9","unstructured":"Kanazuka, T.: Parameter identification of urban Storage function model by evolutionary computing methods. Master\u2019s Thesis, Tokyo Metropolitan University, Graduate School of Urban Environmental Sciences (2017)"}],"container-title":["Lecture Notes in Computer Science","Advances in Artificial Intelligence \u2013 IBERAMIA 2018"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-03928-8_41","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,19]],"date-time":"2024-10-19T18:05:56Z","timestamp":1729361156000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-03928-8_41"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030039271","9783030039288"],"references-count":9,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-03928-8_41","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"IBERAMIA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ibero-American Conference on Artificial Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Trujillo","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Peru","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 November 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 November 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iberamia2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.iberamia.org\/iberamia\/iberamia2018\/","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"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"92","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"41","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"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"}},{"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"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information"}}]}}