{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T19:11:25Z","timestamp":1725909085929},"publisher-location":"Cham","reference-count":25,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319569901"},{"type":"electronic","value":"9783319569918"}],"license":[{"start":{"date-parts":[[2017,8,23]],"date-time":"2017-08-23T00:00:00Z","timestamp":1503446400000},"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":[[2018]]},"DOI":"10.1007\/978-3-319-56991-8_38","type":"book-chapter","created":{"date-parts":[[2017,8,21]],"date-time":"2017-08-21T23:57:16Z","timestamp":1503359836000},"page":"499-516","source":"Crossref","is-referenced-by-count":1,"title":["Integration of Fuzzy C-Means and Artificial Neural Network for Short-Term Localized Rainfall Forecast in Tropical Climate"],"prefix":"10.1007","author":[{"given":"Noor Zuraidin","family":"Mohd-Safar","sequence":"first","affiliation":[]},{"given":"David","family":"Ndzi","sequence":"additional","affiliation":[]},{"given":"David","family":"Sanders","sequence":"additional","affiliation":[]},{"given":"Hassanuddin Mohamed","family":"Noor","sequence":"additional","affiliation":[]},{"given":"Latifah Munirah","family":"Kamarudin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,8,23]]},"reference":[{"key":"38_CR1","first-page":"1","volume":"9","author":"B Pradhan","year":"2009","unstructured":"Pradhan, B.: Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. J. Spat. Hydrol. 9, 1\u201318 (2009)","journal-title":"J. Spat. Hydrol."},{"key":"38_CR2","first-page":"556","volume":"5","author":"A Shahi","year":"2009","unstructured":"Shahi, A.: An effective fuzzy C-mean and type-2 fuzzy. J. Theor. Appl. Inf. Technol. 5, 556\u2013567 (2009)","journal-title":"J. Theor. Appl. Inf. Technol."},{"key":"38_CR3","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1007\/s00521-004-0413-4","volume":"13","author":"I Maqsood","year":"2004","unstructured":"Maqsood, I., Khan, M., Abraham, A.: An ensemble of neural networks for weather forecasting. Neural Comput. Appl. 13, 112\u2013122 (2004)","journal-title":"Neural Comput. Appl."},{"issue":"5","key":"38_CR4","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1175\/1520-0450(1964)003<0513:AADPSF>2.0.CO;2","volume":"3","author":"MJC Hu","year":"1964","unstructured":"Hu, M.J.C., Root, H.E.: An adaptive data processing system for weather forecasting. J. Appl. Meteorol. 3(5), 513\u2013523 (1964)","journal-title":"J. Appl. Meteorol."},{"issue":"8","key":"38_CR5","doi-asserted-by":"crossref","first-page":"1413","DOI":"10.5194\/hess-13-1413-2009","volume":"13","author":"NQ Hung","year":"2008","unstructured":"Hung, N.Q., Babel, M.S., Weesakul, S., Tripathi, N.K.: An artificial neural network model for rainfall forecasting in Bangkok, Thailand. Hydrol. Earth Syst. Sci. 13(8), 1413\u20131425 (2008)","journal-title":"Hydrol. Earth Syst. Sci."},{"issue":"5","key":"38_CR6","doi-asserted-by":"crossref","first-page":"812","DOI":"10.20965\/jaciii.2014.p0812","volume":"18","author":"CNA Klent Gomez Abistado","year":"2014","unstructured":"Klent Gomez Abistado, C.N.A., Maravillas, E.A.: Weather forecasting using artificial neural network and bayesian network. J. Adv. Computat. Intell. Intell. Inf. 18(5), 812\u2013817 (2014)","journal-title":"J. Adv. Computat. Intell. Intell. Inf."},{"issue":"3","key":"38_CR7","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1080\/01969727308546046","volume":"3","author":"JC Dunn","year":"1973","unstructured":"Dunn, J.C.: A fuzzy relative of the ISODATA process and its use in detecting compact well-separated clusters. J. Cybern. 3(3), 32\u201357 (1973)","journal-title":"J. Cybern."},{"issue":"2","key":"38_CR8","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/0098-3004(84)90020-7","volume":"10","author":"JC Bezdek","year":"1984","unstructured":"Bezdek, J.C.: FCM: the fuzzy C-means clustering algorithm. Comput. Geosci. 10(2), 191\u2013203 (1984)","journal-title":"Comput. Geosci."},{"issue":"6","key":"38_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.14257\/ijdta.2013.6.6.01","volume":"6","author":"Y Lu","year":"2013","unstructured":"Lu, Y., Ma, T., Yin, C., Xie, X., Tian, W., Zhong, S.: Implementation of the fuzzy C-means clustering algorithm in meteorological data. Int. J. Database Theory Appl. 6(6), 1\u201318 (2013)","journal-title":"Int. J. Database Theory Appl."},{"key":"38_CR10","unstructured":"Vega-corona, A.: ANN and Fuzzy c-means applied to environmental pollution prediction, pp. 1\u20136 (2012)"},{"key":"38_CR11","unstructured":"Howard Demuth, M.B., Hagan, M.: Neural network toolbox user\u2019s guide (2012)"},{"key":"38_CR12","unstructured":"Neural Networks Training Based on Differential Evolution Algorithm Compared with Other Architectures for Weather Forecasting34. J. Comput. Sci. Netw. Secur. 9(3), 92\u201399 (2009)"},{"issue":"1","key":"38_CR13","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1214\/ss\/1177010638","volume":"9","author":"B Cheng","year":"1994","unstructured":"Cheng, B., Titterington, D.M.: Neural Networks: A Review from a Statistical Perspective. Stat. Sci. 9(1), 2\u201330 (1994)","journal-title":"Stat. Sci."},{"issue":"3","key":"38_CR14","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1016\/0378-7206(93)90064-Z","volume":"24","author":"DFE Goss","year":"1993","unstructured":"Goss, D.F.E.: Forecasting with neural networks: an application using bankruptcy data. Inf. Manage. 24(3), 159\u2013167 (1993)","journal-title":"Inf. Manage."},{"key":"38_CR15","unstructured":"Abraham, A., Philip, N.S., Joseph, K.B.: Will we have a wet summer\u202f? In: Soft Computing Models for Long-term Rainfall Forecasting (1992)"},{"issue":"3","key":"38_CR16","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1049\/ip-g-2.1992.0050","volume":"139","author":"C Charalambous","year":"1992","unstructured":"Charalambous, C.: Conjugate gradient algorithm for efficient training of artificial neural networks. IEE Proc. G Circuits, Devices Syst. 139(3), 301 (1992)","journal-title":"IEE Proc. G Circuits, Devices Syst."},{"key":"38_CR17","doi-asserted-by":"crossref","unstructured":"Foresee, F.D., Hagan, M.T.: Gauss-Newton approximation to Bayesian learning. In: Proceedings of International Conference on Neural Networks (ICNN 1997) (1997)","DOI":"10.1109\/ICNN.1997.614194"},{"key":"38_CR18","unstructured":"Pellakuri, V., Rajeswara Rao, D., Lakshmi Prasanna, P., Santhi, M.V.B.T.: A conceptual framework for approaching predictive modeling using multivariate regression analysis vs artificial neural network. J. Theor. Appl. Inf. Technol. 77(2), 287\u2013290 (2015)"},{"key":"38_CR19","doi-asserted-by":"crossref","unstructured":"Mor\u00e9, J.J.: The Levenberg-Marquardt algorithm: implementation and theory. In: Lecture Notes in Mathematics, pp. 105\u2013116. Springer, Berlin (1978)","DOI":"10.1007\/BFb0067700"},{"issue":"3","key":"38_CR20","doi-asserted-by":"crossref","first-page":"448","DOI":"10.1162\/neco.1992.4.3.448","volume":"4","author":"DJC MacKay","year":"1992","unstructured":"MacKay, D.J.C.: A practical bayesian framework for back propagation networks. Neural Comput. 4(3), 448\u2013472 (1992)","journal-title":"Neural Comput."},{"issue":"3","key":"38_CR21","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1162\/neco.1992.4.3.415","volume":"4","author":"DJC MacKay","year":"1992","unstructured":"MacKay, D.J.C.: Bayesian interpolation. Neural Comput. 4(3), 415\u2013447 (1992)","journal-title":"Neural Comput."},{"key":"38_CR22","unstructured":"Shewchuk, J.R.: An introduction to the conjugate gradient method without the agonizing pain. Science 49(CS-94\u2013125), 64 (1994)"},{"issue":"4","key":"38_CR23","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1016\/S0893-6080(05)80056-5","volume":"6","author":"MF M\u00f8ller","year":"1993","unstructured":"M\u00f8ller, M.F.: A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw. 6(4), 525\u2013533 (1993)","journal-title":"Neural Netw."},{"issue":"2","key":"38_CR24","doi-asserted-by":"crossref","first-page":"87","DOI":"10.2478\/v10117-011-0021-1","volume":"30","author":"J Hauke","year":"2011","unstructured":"Hauke, J., Kossowski, T.: Comparison of values of Pearson\u2019s and Spearman\u2019s correlation coefficients on the same sets of data. Quaestiones Geographicae 30(2), 87\u201393 (2011)","journal-title":"Quaestiones Geographicae"},{"issue":"6","key":"38_CR25","doi-asserted-by":"crossref","first-page":"1287","DOI":"10.1175\/2007WAF2006114.1","volume":"22","author":"HL Yuan","year":"2007","unstructured":"Yuan, H.L., Gao, X.G., Mullen, S.L., Sorooshian, S., Du, J., Juang, H.M.H.: Calibration of probabilistic quantitative precipitation forecasts with an artificial neural network. Weather Forecast. 22(6), 1287\u20131303 (2007)","journal-title":"Weather Forecast."}],"container-title":["Lecture Notes in Networks and Systems","Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-56991-8_38","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,8,22]],"date-time":"2017-08-22T00:14:51Z","timestamp":1503360891000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-56991-8_38"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,23]]},"ISBN":["9783319569901","9783319569918"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-56991-8_38","relation":{},"ISSN":["2367-3370","2367-3389"],"issn-type":[{"type":"print","value":"2367-3370"},{"type":"electronic","value":"2367-3389"}],"subject":[],"published":{"date-parts":[[2017,8,23]]}}}