{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:07:53Z","timestamp":1742911673495,"version":"3.40.3"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030042202"},{"type":"electronic","value":"9783030042219"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-030-04221-9_6","type":"book-chapter","created":{"date-parts":[[2018,11,16]],"date-time":"2018-11-16T12:32:16Z","timestamp":1542371536000},"page":"58-69","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Applying Macroclimatic Variables to Improve Flow Rate Forecasting Using Neural Networks Techniques"],"prefix":"10.1007","author":[{"given":"Breno","family":"Santos","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bruna","family":"Aguiar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M\u00eauser","family":"Valen\u00e7a","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,11,17]]},"reference":[{"key":"6_CR1","unstructured":"Valen\u00e7a, M.J.S., Ludermir, T.B., Valen\u00e7a, A., Vasconcelos, I.: Sistema de Apoio a Decis\u00e3o para a Opera\u00e7\u00e3o Hidr\u00e1ulica de Sobradinho Incorporando Tend\u00eancias Macro-Clim\u00e1ticas Utilizando Redes Neurais (2009)"},{"key":"6_CR2","unstructured":"Brooks, K.N., Ffolliott, P.F., Magner, J.A.: Hydrology and the Management of Watersheds, 3 edn. (2003)"},{"key":"6_CR3","unstructured":"Valen\u00e7a, M.J.S.: Proposta de Alerta Ambiental baseada na Previs\u00e3o de Volumes M\u00e1ximos Afluentes ao reservat\u00f3rio de Sobradinho"},{"key":"6_CR4","unstructured":"Ag\u00eancia Nacional de \u00c1guas (ANA): http:\/\/www2.ana.gov.br\/Paginas\/servicos\/saladesituacao\/v2\/saofrancisco.aspx\/"},{"key":"6_CR5","unstructured":"What is Air Temperature? https:\/\/www.fondriest.com\/news\/airtemperature.htm"},{"key":"6_CR6","doi-asserted-by":"crossref","unstructured":"Mendon\u00e7a, F., Dubreuil, V.: Termografiada superf\u00edcie e temperatura do ar na rmc (regi\u00e3ometropolitana de curitiba\/pr). Editora UFPR, pp. 25\u201335 (2005)","DOI":"10.5380\/raega.v9i0.3444"},{"key":"6_CR7","doi-asserted-by":"crossref","unstructured":"Cavalcanti, E.P., de Silva, V.P.R., de Sousa, A.S.F.: Programa computacional para a estimativa da temperatura do ar para a regi\u00e3o nordeste do Brazil. Revista Brasileira de Engenharia Agr\u00edcola e Ambiental, pp. 140\u2013147 (2006)","DOI":"10.1590\/S1415-43662006000100021"},{"key":"6_CR8","unstructured":"Embrapa: http:\/\/www.agencia.cnptia.embrapa.br\/Agencia22\/AG01\/arvore\/AG01_79_24112005115223.html"},{"issue":"4","key":"6_CR9","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1590\/S0102-261X2006000400005","volume":"24","author":"Tiago Nicolosi Bomventi","year":"2006","unstructured":"Bomventi, T.N., Wainer, I.E.K.C., Taschetto, A.S.: Rela\u00e7\u00e3o entre a radia\u00e7\u00e3o de onda longa, precipita\u00e7\u00e3o e temperatura da superf\u00edcie do mar no oceano atl\u00e2ntico tropical. Revista Brasileira de Geof\u00edsica 24, 513\u2013524, 12 2006. http:\/\/www.scielo.br\/scielo.php?script=sci_arttext&pid=S0102-261X2006000400005&nrm=iso","journal-title":"Revista Brasileira de Geof\u00edsica"},{"key":"6_CR10","doi-asserted-by":"crossref","unstructured":"Susskind, J., Molnar, G., Iredell, L.: Contributions to Climate Research Using the AIRS Science Team Version-5 Products (2011)","DOI":"10.1117\/12.893576"},{"key":"6_CR11","unstructured":"de Stefano Ermenegildo, L.F., Pereira, S.B., Arai, F.K., Rosa, D.B.C.J.: Vaz\u00e3o espec\u00edfica e precipita\u00e7\u00e3o m\u00e9dia na bacia do ivinhema. Dourados, pp. 428\u2013432 (2012)"},{"key":"6_CR12","unstructured":"Tucci, C.E.M.: Hidrologia: ci\u00eancia e aplica\u00e7\u00e3o. ABRH, 3 edn. (2002)"},{"key":"6_CR13","unstructured":"Rodrigues, A.L.: Informa\u00e7\u00f5es macroclim\u00e1ticas aplicadas na previs\u00e3o de vaz\u00f5es. S\u00e3o Paulo (2016)"},{"key":"6_CR14","unstructured":"Valen\u00e7a, M.J.S.: Fundamentos das Redes Neurais. Livro R\u00e1pido, Brazil (2016)"},{"key":"6_CR15","doi-asserted-by":"publisher","first-page":"1078","DOI":"10.1016\/j.ins.2015.11.039","volume":"367\u2013368","author":"PN Ye Rena","year":"2016","unstructured":"Ye Rena, P.N., Suganthana, N.S., Amaratungac, G.: Random vector functional link network for short-term electricity load demand forecasting. Inf. Sci. 367\u2013368, 1078\u20131093 (2016)","journal-title":"Inf. Sci."},{"key":"6_CR16","unstructured":"Ferreira, A.A., Ludermir, T.B.: Um M\u00e9todo para Design e Treinamento de Reservoir Computing Aplicado \u00e0 Previs\u00e3o de S\u00e9ries Temporais. Pernambuco (2011)"},{"key":"6_CR17","unstructured":"Jaeger, H.: The \u201cecho state\u201d approach to analyzing and training recurrent neural networks (2011)"},{"key":"6_CR18","doi-asserted-by":"publisher","first-page":"2531","DOI":"10.1162\/089976602760407955","volume":"14","author":"W Mass","year":"2002","unstructured":"Mass, W., Natschl\u00e4ger, T., Markram, H.: Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput. 14, 2531\u20132560 (2002)","journal-title":"Neural Comput."},{"key":"6_CR19","unstructured":"Verstraeten, D.: Reservoir computing: computation with dynamical systems. Belgium (2009)"},{"key":"6_CR20","unstructured":"A Gentle Introduction to Backpropagation Through Time. https:\/\/machinelearningmastery.com\/gentle-introduction-backpropagation-time\/"},{"key":"6_CR21","unstructured":"Time Series Prediction with LSTM Recurrent Neural Networks in Python with Keras. https:\/\/machinelearningmastery.com\/time-series-prediction-lstm-recurrent-neural-networks-python-keras\/"},{"issue":"8","key":"6_CR22","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"Sepp Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 1735\u20131780 (1997)","journal-title":"Neural Computation"},{"key":"6_CR23","doi-asserted-by":"crossref","DOI":"10.1561\/9781601988157","volume-title":"Deep Learning Methods and Applications, Foundations and Trends in Signal Processing","author":"L Deng","year":"2014","unstructured":"Deng, L., Yu, D.: Deep Learning Methods and Applications, Foundations and Trends in Signal Processing, 7th edn. Now Publishers Inc., Boston (2014)","edition":"7"},{"key":"6_CR24","volume-title":"Deep Learning","author":"I Goodfellow","year":"2016","unstructured":"Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016). http:\/\/www.deeplearningbook.org"},{"key":"6_CR25","unstructured":"National Oceanic and Atmospheric Administration (NOAA). http:\/\/www.noaa.gov\/"},{"key":"6_CR26","unstructured":"Eletrobras. http:\/\/eletrobras.com\/pt\/Paginas\/home.aspx"},{"key":"6_CR27","unstructured":"Companhia Hidroel\u00e9trica do S\u00e3o Francisco (Chesf). http:\/\/www.chesf.gov.br"},{"key":"6_CR28","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-28803-1","volume-title":"Data Mining with Computational Intelligence","author":"L Wang","year":"2005","unstructured":"Wang, L., Fu, X.: Data Mining with Computational Intelligence. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/3-540-28803-1"},{"key":"6_CR29","volume-title":"Linear Regression And Correlation: A Beginner\u2019s Guide","author":"S Hartshorn","year":"2017","unstructured":"Hartshorn, S.: Linear Regression And Correlation: A Beginner\u2019s Guide, 1st edn. Amazon Digital Services LLC, Seattle (2017)","edition":"1"},{"key":"6_CR30","volume-title":"Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners","author":"S Hartshorn","year":"2016","unstructured":"Hartshorn, S.: Machine Learning With Random Forests And Decision Trees: A Visual Guide For Beginners, 1st edn. Amazon Digital Services LLC, Seattle (2016)","edition":"1"},{"key":"6_CR31","doi-asserted-by":"crossref","unstructured":"Kok Keong Teo, L.W., Lin, Z.: Wavelet packet multi-layer perceptron for chaotic time series prediction: effects of weight initialization. In: International Conference on Computational Science, vol. 2074, pp. 310\u2013317, 7 2001","DOI":"10.1007\/3-540-45718-6_35"},{"key":"6_CR32","unstructured":"Keras. https:\/\/keras.io\/"},{"key":"6_CR33","unstructured":"Python. https:\/\/www.python.org\/"},{"key":"6_CR34","unstructured":"Kingma, D.P., Ba, J.L.: Adam: a method for stochastic optimization. In: International Conference for Learning Representations (2014)"},{"key":"6_CR35","unstructured":"A simple deep learning model for stock price prediction using TensorFlow. https:\/\/medium.com\/mlreview\/a-simple-deep-learning-model-for-stock-price-prediction-using-tensorflow-30505541d877"},{"key":"6_CR36","unstructured":"Tensorflow. https:\/\/www.tensorflow.org\/"},{"key":"6_CR37","volume-title":"Basics of Software Engineering Experimentation","author":"AM Moreno","year":"2001","unstructured":"Moreno, A.M., Juristo, N.: Basics of Software Engineering Experimentation. Kluwer Academic Publisher, Dordrecht (2001)"},{"key":"6_CR38","unstructured":"Venables, W.N., Smith, D.M., the R Core Team: An Introduction to R. Network Theory Ltd, Hershey (2009)"}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-04221-9_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,13]],"date-time":"2024-03-13T12:38:56Z","timestamp":1710333536000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-04221-9_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783030042202","9783030042219"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-04221-9_6","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":"17 November 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Siem Reap","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cambodia","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 December 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 December 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/conference.cs.cityu.edu.hk\/iconip\/","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":"575","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":"401","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":"70% - 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":"4","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":"6","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)"}}]}}