{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T06:31:47Z","timestamp":1763533907185},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2014,12,24]],"date-time":"2014-12-24T00:00:00Z","timestamp":1419379200000},"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":["Neural Comput &amp; Applic"],"published-print":{"date-parts":[[2015,7]]},"DOI":"10.1007\/s00521-014-1794-7","type":"journal-article","created":{"date-parts":[[2014,12,23]],"date-time":"2014-12-23T05:58:30Z","timestamp":1419314310000},"page":"1203-1215","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Wavelet and adaptive neuro-fuzzy inference system conjunction model for groundwater level predicting in a coastal aquifer"],"prefix":"10.1007","volume":"26","author":[{"given":"Xiaohu","family":"Wen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haijiao","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianhua","family":"Si","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zongqiang","family":"Chang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haiyang","family":"Xi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2014,12,24]]},"reference":[{"key":"1794_CR1","doi-asserted-by":"crossref","unstructured":"Barlow PM (2003) Groundwater in freshwater-saltwater environments of the Atlantic coast. USGS Circular 1262. U.S. Geological Survey","DOI":"10.3133\/cir1262"},{"key":"1794_CR2","unstructured":"Li FM (2005) Monitoring and numerical simulation of saltwater intrusion in the Eastern Coast of Laizhou Bay, China. Ph.D. dissertation, Ocean University of China (in Chinese)"},{"issue":"1\u20132","key":"1794_CR3","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.jhydrol.2010.11.002","volume":"396","author":"H Yoon","year":"2011","unstructured":"Yoon H, Jun SC, Hyun Y, Bae GO, Lee KK (2011) A comparative study of artificial neural networks and support vector machines for predicting groundwater levels in a coastal aquifer. J Hydrol 396(1\u20132):128\u2013138","journal-title":"J Hydrol"},{"issue":"9","key":"1794_CR4","doi-asserted-by":"crossref","first-page":"1845","DOI":"10.1007\/s11269-009-9527-x","volume":"24","author":"S Mohanty","year":"2010","unstructured":"Mohanty S, Jha MK, Kumar A, Sudheer KP (2010) Artificial neural network modeling for groundwater level forecasting in a River Island of Eastern India. Water Resour Manag 24(9):1845\u20131865","journal-title":"Water Resour Manag"},{"issue":"1","key":"1794_CR5","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.watres.2003.09.026","volume":"38","author":"YM Kuo","year":"2004","unstructured":"Kuo YM, Liu CW, Lin KH (2004) Evaluation of the ability of an artificial neural network model to assess the variation of groundwater quality in an area of blackfoot disease in Taiwan. Water Res 38(1):148\u2013158","journal-title":"Water Res"},{"issue":"2","key":"1794_CR6","doi-asserted-by":"crossref","first-page":"259","DOI":"10.1007\/s00477-009-0315-1","volume":"24","author":"M Firat","year":"2009","unstructured":"Firat M, G\u00fcng\u00f6r M (2009) Monthly total sediment forecasting using adaptive neuro fuzzy inference system. Stoch Environ Res Risk Assess 24(2):259\u2013270","journal-title":"Stoch Environ Res Risk Assess"},{"issue":"4","key":"1794_CR7","doi-asserted-by":"crossref","first-page":"523","DOI":"10.1016\/j.envsoft.2010.10.016","volume":"26","author":"S Alvisi","year":"2011","unstructured":"Alvisi S, Franchini M (2011) Fuzzy neural networks for water level and discharge forecasting with uncertainty. Environ Modell Softw 26(4):523\u2013537","journal-title":"Environ Modell Softw"},{"issue":"7","key":"1794_CR8","doi-asserted-by":"crossref","first-page":"4355","DOI":"10.1007\/s10661-011-2269-2","volume":"184","author":"A Bayram","year":"2012","unstructured":"Bayram A, Kankal M, Onsoy H (2012) Estimation of suspended sediment concentration from turbidity measurements using artificial neural networks. Environ Monit Assess 184(7):4355\u20134365","journal-title":"Environ Monit Assess"},{"issue":"4","key":"1794_CR9","doi-asserted-by":"crossref","first-page":"885","DOI":"10.1029\/2000WR900368","volume":"37","author":"P Coulibaly","year":"2001","unstructured":"Coulibaly P, Anctil F, Aravena R, Bobee B (2001) Artificial neural network modeling of water table depth fluctuations. Water Resour Res 37(4):885\u2013896","journal-title":"Water Resour Res"},{"issue":"1\u20134","key":"1794_CR10","doi-asserted-by":"crossref","first-page":"92","DOI":"10.1016\/j.jhydrol.2004.10.005","volume":"307","author":"S Lallahem","year":"2005","unstructured":"Lallahem S, Mania J, Hani A, Najjar Y (2005) On the use of neural networks to evaluate groundwater levels in fractured media. J Hydrol 307(1\u20134):92\u2013111","journal-title":"J Hydrol"},{"issue":"8","key":"1794_CR11","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1007\/s00521-010-0360-1","volume":"19","author":"NB Dash","year":"2010","unstructured":"Dash NB, Panda SN, Remesan R, Sahoo N (2010) Hybrid neural modeling for groundwater level prediction. Neural Comput Appl 19(8):1251\u20131263","journal-title":"Neural Comput Appl"},{"issue":"26","key":"1794_CR12","first-page":"5775","volume":"6","author":"J Amir","year":"2011","unstructured":"Amir J, Navid J (2011) Groundwater modeling using hybrid of artificial neural network with genetic algorithm. Afr J Agric Res 6(26):5775\u20135784","journal-title":"Afr J Agric Res"},{"issue":"1","key":"1794_CR13","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1007\/s11269-006-4007-z","volume":"20","author":"PC Nayak","year":"2006","unstructured":"Nayak PC, Rao YRS, Sudheer KP (2006) Groundwater level forecasting in a shallow aquifer using artificial neural network approach. Water Resour Manag 20(1):77\u201390","journal-title":"Water Resour Manag"},{"issue":"8","key":"1794_CR14","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.1002\/hyp.6686","volume":"22","author":"B Krishna","year":"2008","unstructured":"Krishna B, Rao YRS, Vijaya T (2008) Modelling groundwater levels in an urban coastal aquifer using artificial neural networks. Hydrol Process 22(8):1180\u20131188","journal-title":"Hydrol Process"},{"issue":"1","key":"1794_CR15","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.advwatres.2005.04.015","volume":"29","author":"FJ Chang","year":"2006","unstructured":"Chang FJ, Chang YT (2006) Adaptive neuro-fuzzy inference system for prediction of water level in reservoir. Adv Water Resour 29(1):1\u201310","journal-title":"Adv Water Resour"},{"issue":"1\u20132","key":"1794_CR16","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.jhydrol.2007.10.050","volume":"349","author":"C Shu","year":"2008","unstructured":"Shu C, Ouarda TBMJ (2008) Regional flood frequency analysis at ungauged sites using the adaptive neuro-fuzzy inference system. J Hydrol 349(1\u20132):31\u201343","journal-title":"J Hydrol"},{"issue":"3\u20134","key":"1794_CR17","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.jhydrol.2010.07.023","volume":"391","author":"A Talei","year":"2010","unstructured":"Talei A, Chua LHC, Wong TSW (2010) Evaluation of rainfall and discharge inputs used by adaptive network-based fuzzy inference systems (ANFIS) in rainfall-runoff modeling. J Hydrol 391(3\u20134):248\u2013262","journal-title":"J Hydrol"},{"issue":"6","key":"1794_CR18","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.jhydrol.2012.03.031","volume":"442\u2013443","author":"AK Lohani","year":"2012","unstructured":"Lohani AK, Kumar R, Singh RD (2012) Hydrological time series modeling: a comparison between adaptive neuro-fuzzy, neural network and autoregressive techniques. J Hydrol 442\u2013443(6):23\u201335","journal-title":"J Hydrol"},{"issue":"6","key":"1794_CR19","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1007\/s10666-008-9174-2","volume":"14","author":"M Kholghi","year":"2008","unstructured":"Kholghi M, Hosseini SM (2008) Comparison of groundwater level estimation using neuro-fuzzy and ordinary kriging. Environ Monit Assess 14(6):729\u2013737","journal-title":"Environ Monit Assess"},{"issue":"6","key":"1794_CR20","doi-asserted-by":"crossref","first-page":"1301","DOI":"10.1007\/s12665-010-0617-0","volume":"62","author":"PD Sreekanth","year":"2010","unstructured":"Sreekanth PD, Sreedevi PD, Ahmed S, Geethanjali N (2010) Comparison of FFNN and ANFIS models for estimating groundwater level. Environ Earth Sci 62(6):1301\u20131310","journal-title":"Environ Earth Sci"},{"issue":"10","key":"1794_CR21","doi-asserted-by":"crossref","first-page":"1692","DOI":"10.1016\/j.cageo.2010.11.010","volume":"37","author":"J Shiri","year":"2011","unstructured":"Shiri J, Ki\u015fi \u00d6 (2011) Comparison of genetic programming with neuro-fuzzy systems for predicting short-term water table depth fluctuations. Comput Geosci 37(10):1692\u20131701","journal-title":"Comput Geosci"},{"issue":"5","key":"1794_CR22","doi-asserted-by":"crossref","first-page":"961","DOI":"10.1109\/18.57199","volume":"36","author":"I Dabuechies","year":"1990","unstructured":"Dabuechies I (1990) The wavelet transform, time-frequency localization and signal analysis. IEEE Trans Inf Theory 36(5):961\u20131005","journal-title":"IEEE Trans Inf Theory"},{"issue":"6","key":"1794_CR23","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1061\/(ASCE)1084-0699(2003)8:6(319)","volume":"8","author":"TW Kim","year":"2003","unstructured":"Kim TW, Valdes JB (2003) Nonlinear model for drought forecasting based on a conjunction of wavelet transforms and neural networks. J Hydrol Eng 8(6):319\u2013328","journal-title":"J Hydrol Eng"},{"issue":"3\u20134","key":"1794_CR24","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.jhydrol.2008.02.013","volume":"353","author":"JF Adamowski","year":"2008","unstructured":"Adamowski JF (2008) Development of a short-term river flood forecasting method for snowmelt driven floods based on wavelet and cross-wavelet analysis. J Hydrol 353(3\u20134):247\u2013266","journal-title":"J Hydrol"},{"issue":"3\u20134","key":"1794_CR25","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.jhydrol.2010.10.039","volume":"395","author":"M \u00d6zger","year":"2010","unstructured":"\u00d6zger M, Mishra AK, Singh VP (2010) Scaling characteristics of precipitation data in conjunction with wavelet analysis. J Hydrol 395(3\u20134):279\u2013288","journal-title":"J Hydrol"},{"issue":"6","key":"1794_CR26","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.jhydrol.2012.03.038","volume":"442\u2013443","author":"A Prokoph","year":"2012","unstructured":"Prokoph A, Adamowski J, Adamowski K (2012) Influence of the 11\u00a0year solar cycle on annual streamflow maxima in Southern Canada. J Hydrol 442\u2013443(6):55\u201362","journal-title":"J Hydrol"},{"issue":"14","key":"1794_CR27","doi-asserted-by":"crossref","first-page":"2877","DOI":"10.1007\/s11269-009-9414-5","volume":"23","author":"V Nourani","year":"2009","unstructured":"Nourani V, Komasi M, Mano A (2009) A multivariate ANN-wavelet approach for rainfall-runoff modeling. Water Resour Manag 23(14):2877\u20132894","journal-title":"Water Resour Manag"},{"issue":"1","key":"1794_CR28","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1139\/L08-090","volume":"36","author":"T Partal","year":"2009","unstructured":"Partal T (2009) River flow forecasting using different artificial neural network algorithms and wavelet transform. Can J Civil Eng 36(1):26\u201338","journal-title":"Can J Civil Eng"},{"issue":"17","key":"1794_CR29","doi-asserted-by":"crossref","first-page":"4916","DOI":"10.1016\/j.scitotenv.2009.05.016","volume":"407","author":"T Rajaee","year":"2009","unstructured":"Rajaee T, Mirbagheri SA, Zounemat-Kermani M, Nourani V (2009) Daily suspended sediment concentration simulation using ANN and neuro-fuzzy models. Sci Total Environ 407(17):4916\u20134927","journal-title":"Sci Total Environ"},{"issue":"1\u20132","key":"1794_CR30","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.jhydrol.2010.06.033","volume":"390","author":"J Adamowski","year":"2010","unstructured":"Adamowski J, Sun K (2010) Development of a coupled wavelet transform and neural network method for flow forecasting of non-perennial rivers in semi-arid watersheds. J Hydrol 390(1\u20132):85\u201391","journal-title":"J Hydrol"},{"issue":"10","key":"1794_CR31","doi-asserted-by":"crossref","first-page":"3697","DOI":"10.1007\/s11269-013-0374-4","volume":"27","author":"RV Ramana","year":"2013","unstructured":"Ramana RV, Krishna B, Kumar SR, Pandey NG (2013) Monthly rainfall prediction using wavelet neural network analysis. Water Resour Manag 27(10):3697\u20133711","journal-title":"Water Resour Manag"},{"issue":"1\u20134","key":"1794_CR32","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.jhydrol.2011.06.013","volume":"407","author":"J Adamowski","year":"2011","unstructured":"Adamowski J, Chan HF (2011) A wavelet neural network conjunction model for groundwater level forecasting. J Hydrol 407(1\u20134):28\u201340","journal-title":"J Hydrol"},{"issue":"3","key":"1794_CR33","doi-asserted-by":"crossref","first-page":"665","DOI":"10.1109\/21.256541","volume":"23","author":"JSR Jang","year":"1993","unstructured":"Jang JSR (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":"1794_CR34","volume-title":"Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence","author":"JSR Jang","year":"1997","unstructured":"Jang JSR, Sun CT, Mizutani E (1997) Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence. Prentice-Hall, New Jersey"},{"key":"1794_CR35","unstructured":"Drake JT (2000) Communications phase synchronization using the adaptive network fuzzy inference system. Ph.D. Thesis, New Mexico State University, Las Cruces, New Mexico, USA"},{"key":"1794_CR36","volume-title":"Wavelets algorithms applications","author":"Y Meyer","year":"1993","unstructured":"Meyer Y (1993) Wavelets algorithms applications. Society for Industrial and Applied Mathematics, Philadelphia"},{"issue":"32\u201334","key":"1794_CR37","doi-asserted-by":"crossref","first-page":"1387","DOI":"10.1016\/S1474-7065(02)00076-1","volume":"27","author":"AF Drago","year":"2002","unstructured":"Drago AF, Boxall SR (2002) Use of the wavelet transform on hydro-meteorological data. Phys Chem Earth 27(32\u201334):1387\u20131399","journal-title":"Phys Chem Earth"},{"key":"1794_CR38","volume-title":"A wavelet tour of signal processing","author":"SG Mallat","year":"1998","unstructured":"Mallat SG (1998) A wavelet tour of signal processing, 2nd edn. Academic Press, San Diego","edition":"2"},{"issue":"3\u20134","key":"1794_CR39","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1016\/j.jhydrol.2010.10.008","volume":"394","author":"J Shiri","year":"2010","unstructured":"Shiri J, Kisi O (2010) Short-term and long-term streamflow forecasting using a wavelet and neuro-fuzzy conjunction model. J Hydrol 394(3\u20134):486\u2013493","journal-title":"J Hydrol"},{"key":"1794_CR40","volume-title":"Neural networks: a comprehensive foundation","author":"S Haykin","year":"1999","unstructured":"Haykin S (1999) Neural networks: a comprehensive foundation, 2nd edn. Prentice-Hall, Englewood Cliffs","edition":"2"},{"issue":"1","key":"1794_CR41","first-page":"31","volume":"14","author":"MZ Fu","year":"1994","unstructured":"Fu MZ, Xu XSH, Cheng ZHB, Xu XW (1994) The seasonal desertification-climate environment in the coastal areas of the yellow sea and Bohai Sea. J Desert Res 14(1):31\u201340 (in Chinese)","journal-title":"J Desert Res"},{"key":"1794_CR42","volume-title":"Study on seawater intrusion in coastal area in Laizhou","author":"ZSH Yin","year":"1992","unstructured":"Yin ZSH (1992) Study on seawater intrusion in coastal area in Laizhou. Marine Publishing House, Beijing (in Chinese)"},{"issue":"1\u20132","key":"1794_CR43","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/j.jhydrol.2007.05.026","volume":"342","author":"T Partal","year":"2007","unstructured":"Partal T, Ki\u015fi \u00d6 (2007) Wavelet and neuro-fuzzy conjunction model for precipitation forecasting. J Hydrol 342(1\u20132):199\u2013212","journal-title":"J Hydrol"},{"issue":"1\u20132","key":"1794_CR44","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1016\/j.jhydrol.2003.12.010","volume":"291","author":"PC Nayak","year":"2004","unstructured":"Nayak PC, Sudhee KP, Rangan DM, Ramasastri KS (2004) A neuro-fuzzy computing technique for modeling hydrological time series. J Hydrol 291(1\u20132):52\u201366","journal-title":"J Hydrol"},{"issue":"1\u20134","key":"1794_CR45","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.jhydrol.2004.07.001","volume":"302","author":"H Vernieuwe","year":"2005","unstructured":"Vernieuwe H, Georgieva O, De Baets B, Pauwels VRN, Verhoest NEC, De Troch FP (2005) Comparison of data-driven Takagi-Sugeno models of rainfall- discharge dynamics. J Hydrol 302(1\u20134):173\u2013186","journal-title":"J Hydrol"}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1794-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00521-014-1794-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-014-1794-7","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,8,18]],"date-time":"2019-08-18T18:54:00Z","timestamp":1566154440000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00521-014-1794-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12,24]]},"references-count":45,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2015,7]]}},"alternative-id":["1794"],"URL":"https:\/\/doi.org\/10.1007\/s00521-014-1794-7","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,12,24]]}}}