{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T06:29:54Z","timestamp":1725863394647},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319447803"},{"type":"electronic","value":"9783319447810"}],"license":[{"start":{"date-parts":[[2016,1,1]],"date-time":"2016-01-01T00:00:00Z","timestamp":1451606400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016]]},"DOI":"10.1007\/978-3-319-44781-0_37","type":"book-chapter","created":{"date-parts":[[2016,8,12]],"date-time":"2016-08-12T15:20:37Z","timestamp":1471015237000},"page":"308-316","source":"Crossref","is-referenced-by-count":2,"title":["Using Reservoir Computing and Trend Information for Short-Term Streamflow Forecasting"],"prefix":"10.1007","author":[{"given":"Sabrina G. T. A.","family":"Bezerra","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Camila B.","family":"de Andrade","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M\u00eauser J. S.","family":"Valen\u00e7a","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,8,13]]},"reference":[{"key":"37_CR1","unstructured":"Brooks, K., Ffolliott, P., Gregersen, H., DeBani, L.: Hydrology and the Management of Watersheds (2003)"},{"key":"37_CR2","unstructured":"Box, G., Jenkins, G.: Time Series Analysis - Forecasting and Control (1976)"},{"key":"37_CR3","unstructured":"Haykin, S.: Neural Networks: A Comprehensive Foundation (1998)"},{"key":"37_CR4","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1016\/j.jhydrol.2013.06.011","volume":"498","author":"O Ki\u015fi","year":"2013","unstructured":"Ki\u015fi, O.: Evolutionary neural networks for monthly pan evaporation modeling. J. Hydrol. 498, 36\u201345 (2013)","journal-title":"J. Hydrol."},{"key":"37_CR5","doi-asserted-by":"crossref","first-page":"836","DOI":"10.1016\/j.jhydrol.2014.06.013","volume":"517","author":"FJ Chang","year":"2014","unstructured":"Chang, F.J., Chen, P.A., Lu, Y.-R., Huang, E., Chang, K.Y.: Real-time multi-step-ahead water level forecasting by recurrent neural networks for urban flood control. J. Hydrol. 517, 836\u2013846 (2014)","journal-title":"J. Hydrol."},{"key":"37_CR6","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.jhydrol.2015.04.047","volume":"527","author":"X He","year":"2015","unstructured":"He, X., Guan, H., Qin, J.: A hybrid wavelet neural network model with mutual information and particle swarm optimization for forecasting monthly rainfall. J. Hydrol. 527, 88\u2013100 (2015)","journal-title":"J. Hydrol."},{"key":"37_CR7","unstructured":"Verstraeten, D.: Reservoir Computing: computation with dynamical systems. Ph.D. Dissertation (2009)"},{"issue":"3","key":"37_CR8","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.cosrev.2009.03.005","volume":"3","author":"M Luko\u0161evi\u010dius","year":"2009","unstructured":"Luko\u0161evi\u010dius, M., Jaeger, H.: Reservoir computing approaches to recurrent neural network training. Comput. Sci. Rev. 3(3), 127\u2013149 (2009)","journal-title":"Comput. Sci. Rev."},{"issue":"2","key":"37_CR9","doi-asserted-by":"crossref","first-page":"1653","DOI":"10.1061\/(ASCE)HE.1943-5584.0000709","volume":"18","author":"JF Joseph","year":"2013","unstructured":"Joseph, J.F., Falcon, H.E., Sharif, H.O.: Hydrologic trends and correlations in south texas river basins: 1950\u20132009. J. Hydrol. Eng. 18(2), 1653\u20131662 (2013)","journal-title":"J. Hydrol. Eng."},{"issue":"2","key":"37_CR10","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1016\/j.ejor.2003.08.037","volume":"160","author":"G Zhang","year":"2005","unstructured":"Zhang, G., Qi, M.: Neural network forecasting for seasonal and trend time series. European Journal of Operational Research 160(2), 501\u2013514 (2005)","journal-title":"European Journal of Operational Research"},{"key":"37_CR11","series-title":"Smart Innovation, Systems and Technologies","first-page":"229","volume-title":"Knowledge-Based Information Systems in Practice","author":"FJ Chang","year":"2015","unstructured":"Chang, F.J., Lo, Y.C., Chen, P.A., Chang, L.C., Shieh, M.C.: Multi-step-ahead reservoir inflow forecasting by artificial intelligence techniques. In: Tweedale, J., Jain, L.C., Watada, J., Howlett, R.J. (eds.) Knowledge-Based Information Systems in Practice. SIST, vol. 30, pp. 229\u2013242. Springer, Heidelberg (2015)"},{"key":"37_CR12","unstructured":"Jaeger, H.: The \u201cecho state\u201d approach to analysing and training recurrent neural networks. Technical report, German National Research Center for Information Technology (2001)"},{"issue":"11","key":"37_CR13","doi-asserted-by":"crossref","first-page":"2531","DOI":"10.1162\/089976602760407955","volume":"14","author":"W Maass","year":"2002","unstructured":"Maass, W., Natschl\u00e4ger, T., Markram, H.: Real-time computing without stable states: a new framework for neural computation based on perturbations. Neural Comput. 14(11), 2531\u20132560 (2002)","journal-title":"Neural Comput."},{"issue":"2","key":"37_CR14","doi-asserted-by":"crossref","first-page":"1775","DOI":"10.1029\/97JD02551","volume":"103","author":"JA Marengo","year":"1998","unstructured":"Marengo, J.A., Tomasella, J.: Trends in streamflow and rainfall in tropical South America: Amazonia, eastern Brazil, and northwestern Peru. J. Geophys. Res. 103(2), 1775\u20131783 (1998)","journal-title":"J. Geophys. Res."},{"key":"37_CR15","doi-asserted-by":"crossref","unstructured":"Moura, L.Z.: Evaluation of monotonic trends for streamflow in austral Amazon, Brazil: a case study for the Xingu and Tapaj\u00f3s rivers. In: Proceedings of the International Association of Hydrological Sciences, vol. 371, pp. 125\u2013130, June 2015","DOI":"10.5194\/piahs-371-125-2015"},{"key":"37_CR16","unstructured":"Baldwin, J.F., Martin, T.P., Rossiter, J.: Time series modelling and prediction using fuzzy trend information. In: Proceedings of the 5th International Conference on Soft Computing and Information Intelligent Systems, pp. 499\u2013502 (1998)"},{"key":"37_CR17","doi-asserted-by":"crossref","unstructured":"Brockwell, P.J., Davis, R.A.: Introduction to Time Series and Forecasting, 2nd edn. Springer, New York (2002)","DOI":"10.1007\/b97391"}],"container-title":["Lecture Notes in Computer Science","Artificial Neural Networks and Machine Learning \u2013 ICANN 2016"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-44781-0_37","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,6,24]],"date-time":"2017-06-24T20:36:56Z","timestamp":1498336616000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-44781-0_37"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016]]},"ISBN":["9783319447803","9783319447810"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-44781-0_37","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2016]]}}}