{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T03:04:06Z","timestamp":1761102246543,"version":"3.37.3"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2016,12,27]],"date-time":"2016-12-27T00:00:00Z","timestamp":1482796800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2018,9]]},"DOI":"10.1007\/s00521-016-2803-9","type":"journal-article","created":{"date-parts":[[2016,12,27]],"date-time":"2016-12-27T03:22:33Z","timestamp":1482808953000},"page":"1877-1887","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Water level forecasting using neuro-fuzzy models with local learning"],"prefix":"10.1007","volume":"30","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2523-3735","authenticated-orcid":false,"given":"Phuoc Khac-Tien","family":"Nguyen","sequence":"first","affiliation":[]},{"given":"Lloyd Hock-Chye","family":"Chua","sequence":"additional","affiliation":[]},{"given":"Amin","family":"Talei","sequence":"additional","affiliation":[]},{"given":"Quek Hiok","family":"Chai","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2016,12,27]]},"reference":[{"key":"2803_CR1","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1016\/j.jhydrol.2015.07.057","volume":"529","author":"H Badrzadeh","year":"2015","unstructured":"Badrzadeh H, Sarukkalige R, Jayawardena AW (2015) Hourly runoff forecasting for flood risk management: application of various computational intelligence models. J Hydrol 529:1633\u20131643","journal-title":"J Hydrol"},{"issue":"3\u20134","key":"2803_CR2","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1016\/S0925-2312(03)00388-6","volume":"55","author":"B Bazartseren","year":"2003","unstructured":"Bazartseren B, Hildebrandt G, Holz KP (2003) Short-term water level prediction using neural networks and neuro-fuzzy approach. Neurocomputing 55(3\u20134):439\u2013450","journal-title":"Neurocomputing"},{"key":"2803_CR3","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.jhydrol.2004.06.021","volume":"301","author":"GJ Bowden","year":"2005","unstructured":"Bowden GJ, Dandy GC, Maier HR (2005) Input determination for neural network models in water resources applications. Part 1. Background and methodology. J Hydrol 301:75\u201392","journal-title":"J Hydrol"},{"key":"2803_CR4","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.jhydrol.2004.06.020","volume":"301","author":"GJ Bowden","year":"2005","unstructured":"Bowden GJ, Maier HR et al (2005) Input determination for neural network models in water resources applications. Part 2. Case study: forecasting salinity in a river. J Hydrol 301:93\u2013107","journal-title":"J Hydrol"},{"key":"2803_CR5","doi-asserted-by":"publisher","DOI":"10.1029\/2012WR011984","author":"GJ Bowden","year":"2012","unstructured":"Bowden GJ, Maier HR, Dandy GC (2012) Real-time deployment of artificial neural network forecasting models: understanding the range of applicability. Water Resour Res. doi:\n                        10.1029\/2012WR011984","journal-title":"Water Resour Res"},{"key":"2803_CR6","unstructured":"Carrol DG (2007) URBS manual\u2014a rainfall runoff routing model for flood forecasting and design"},{"issue":"3","key":"2803_CR7","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1111\/jfr3.12089","volume":"8","author":"FJ Chang","year":"2015","unstructured":"Chang FJ, Chiang YM, Ho YH (2015) Multistep-ahead flood forecasts by neuro-fuzzy networks with effective rainfall-run-off patterns. J Flood Risk Manag 8(3):224\u2013236","journal-title":"J Flood Risk Manag"},{"key":"2803_CR8","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.jhydrol.2016.01.056","volume":"535","author":"FJ Chang","year":"2016","unstructured":"Chang FJ, Tsai MJ (2016) A nonlinear spatio-temporal lumping of radar rainfall for modeling multi-step-ahead inflow forecasts by data-driven techniques. J Hydrol 535:256\u2013269","journal-title":"J Hydrol"},{"issue":"7","key":"2803_CR9","doi-asserted-by":"crossref","first-page":"1525","DOI":"10.1002\/hyp.5942","volume":"20","author":"SH Chen","year":"2006","unstructured":"Chen SH, Lin YH, Chang LC, Chang FJ (2006) The strategy of building a flood forecast model by neuro-fuzzy network. Hydrol Process 20(7):1525\u20131540","journal-title":"Hydrol Process"},{"key":"2803_CR10","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1109\/91.324806","volume":"2","author":"SL Chiu","year":"1994","unstructured":"Chiu SL (1994) Fuzzy model identification based on cluster estimation. J Intell Fuzzy Syst 2:267\u2013278","journal-title":"J Intell Fuzzy Syst"},{"issue":"4","key":"2803_CR11","first-page":"3","volume":"48","author":"DK Gautam","year":"2001","unstructured":"Gautam DK, Holz KP, Meyer Z (2001) Real-time forecasting of water levels using adaptive neuro-fuzzy systems. Arch Hydroeng Environ Mech 48(4):3\u201321","journal-title":"Arch Hydroeng Environ Mech"},{"key":"2803_CR12","volume-title":"Adaptive filtering prediction and control","author":"GC Goodwin","year":"1984","unstructured":"Goodwin GC, Sin KS (1984) Adaptive filtering prediction and control. Prentice-Hall, Upper Saddle River"},{"issue":"1","key":"2803_CR13","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.advwatres.2008.10.006","volume":"32","author":"YST Hong","year":"2009","unstructured":"Hong YST, White PA (2009) Hydrological modeling using a dynamic neuro-fuzzy system with on-line and local learning algorithm. Adv Water Resour 32(1):110\u2013119","journal-title":"Adv Water Resour"},{"issue":"3","key":"2803_CR14","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1109\/21.256541","volume":"23","author":"J-SR Jang","year":"1993","unstructured":"Jang J-SR (1993) ANFIS: adaptive-network-based fuzzy inference system. IEEE Trans Syst Man Cybern 23(3):665\u2013685","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"2803_CR15","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.jhydrol.2014.03.064","volume":"514","author":"AW Jayawardena","year":"2014","unstructured":"Jayawardena AW, Perera EDP, Zhu B (2014) A comparative study of fuzzy logic systems approach for river discharge prediction. J Hydrol 514:85\u2013101","journal-title":"J Hydrol"},{"issue":"2","key":"2803_CR16","doi-asserted-by":"crossref","first-page":"144","DOI":"10.1109\/91.995117","volume":"10","author":"NK Kasabov","year":"2002","unstructured":"Kasabov NK, Song Q (2002) DENFIS: dynamic evolving neural-fuzzy inference system and its application for time-series prediction. IEEE Trans Fuzzy Syst 10(2):144\u2013154","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"6","key":"2803_CR17","doi-asserted-by":"crossref","first-page":"1034","DOI":"10.1029\/WR016i006p01034","volume":"16","author":"PK Kitanidis","year":"1980","unstructured":"Kitanidis PK, Bras RL (1980) Real-time forecasting with a conceptual hydrologic model 2. Applications and results. Water Resour Res 16(6):1034\u20131044","journal-title":"Water Resour Res"},{"issue":"3","key":"2803_CR18","doi-asserted-by":"crossref","first-page":"282","DOI":"10.1016\/0022-1694(70)90255-6","volume":"10","author":"JE Nash","year":"1970","unstructured":"Nash JE, Sutcliffe JV (1970) River flow forecasting through conceptual models part I\u2014a discussion of principles. J Hydrol 10(3):282\u2013290","journal-title":"J Hydrol"},{"key":"2803_CR19","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2004WR003562","volume":"41","author":"PC Nayak","year":"2005","unstructured":"Nayak PC, Sudheer KP, Rangan DM, Ramasastri KS (2005) Short-term flood forecasting with a neurofuzzy model. Water Resour Res 41:1\u201316","journal-title":"Water Resour Res"},{"issue":"19","key":"2803_CR20","doi-asserted-by":"crossref","first-page":"2878","DOI":"10.1002\/hyp.8347","volume":"26","author":"PKT Nguyen","year":"2012","unstructured":"Nguyen PKT, Chua LHC (2012) The data-driven approach as an operational real-time flood forecasting model. Hydrol Process 26(19):2878\u20132893","journal-title":"Hydrol Process"},{"issue":"1","key":"2803_CR21","doi-asserted-by":"crossref","first-page":"767","DOI":"10.1007\/s11069-013-0920-7","volume":"71","author":"PKT Nguyen","year":"2014","unstructured":"Nguyen PKT, Chua LHC (2014) Flood forecasting in large rivers with data driven models. Nat Hazards 71(1):767\u2013784","journal-title":"Nat Hazards"},{"issue":"3","key":"2803_CR22","doi-asserted-by":"crossref","first-page":"465","DOI":"10.1016\/0893-6080(92)90008-7","volume":"5","author":"AV Ooyen","year":"1992","unstructured":"Ooyen AV, Nienhuis B (1992) Improving the convergence of the back-propagation algorithm. Neural Networks 5(3):465\u2013471","journal-title":"Neural Networks"},{"issue":"6","key":"2803_CR23","doi-asserted-by":"crossref","first-page":"865","DOI":"10.1080\/02626660209492996","volume":"47","author":"MP Rajurkar","year":"2002","unstructured":"Rajurkar MP, Kothyari UC, Chaube UC (2002) Artificial neural networks for daily rainfall-runoff modelling. Hydrol Sci J 47(6):865\u2013878","journal-title":"Hydrol Sci J"},{"issue":"1","key":"2803_CR24","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s00521-013-1443-6","volume":"25","author":"M Rezaeianzadeh","year":"2014","unstructured":"Rezaeianzadeh M, Tabari H, Yazdi AA (2014) Flood flow forecasting using ANN, ANFIS and regression models. Neural Comput Appl 25(1):25\u201337","journal-title":"Neural Comput Appl"},{"issue":"4","key":"2803_CR25","doi-asserted-by":"crossref","first-page":"313","DOI":"10.5194\/hess-9-313-2005","volume":"9","author":"RR Shrestha","year":"2005","unstructured":"Shrestha RR, Theobald S, Nestmann F (2005) Simulation of flood flow in a river system using artificial neural networks. Hydrol Earth Syst Sci 9(4):313\u2013321","journal-title":"Hydrology and Earth System Sciences"},{"issue":"1","key":"2803_CR26","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1109\/TSMC.1985.6313399","volume":"15","author":"T Takagi","year":"1985","unstructured":"Takagi T, Sugeno M (1985) Fuzzy identification of systems and its applications to modeling and control. IEEE Trans Syst Man Cybern 15(1):116\u2013132","journal-title":"IEEE Trans Syst Man Cybern"},{"key":"2803_CR27","doi-asserted-by":"publisher","DOI":"10.1016\/j.jhydrol.2013.02.022","author":"A Talei","year":"2013","unstructured":"Talei A, Chua LHC, Quek C, Jansson P-E (2013) Runoff forecasting using a Takagi\u2013Sugeno neuro-fuzzy model with online learning. J Hydrol. doi:\n                        10.1016\/j.jhydrol.2013.02.022","journal-title":"J Hydrol"},{"issue":"7","key":"2803_CR28","doi-asserted-by":"crossref","first-page":"1631","DOI":"10.1007\/s00521-015-1832-0","volume":"26","author":"CC Young","year":"2015","unstructured":"Young CC, Liu WC, Chung CE (2015) Genetic algorithm and fuzzy neural networks combined with the hydrological modeling system for forecasting watershed runoff discharge. Neural Comput Appl 26(7):1631\u20131643","journal-title":"Neural Comput Appl"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-016-2803-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-016-2803-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-016-2803-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2018,8,31]],"date-time":"2018-08-31T05:35:57Z","timestamp":1535693757000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-016-2803-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,27]]},"references-count":28,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2018,9]]}},"alternative-id":["2803"],"URL":"https:\/\/doi.org\/10.1007\/s00521-016-2803-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"type":"print","value":"0941-0643"},{"type":"electronic","value":"1433-3058"}],"subject":[],"published":{"date-parts":[[2016,12,27]]}}}